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Recent trends in accounting and information system research: a literature review using textual analysis tools.

1. Introduction

2. literature analysis, 2.1. materials and methods, 2.2. results, 2.2.1. results for the first period (2000 to 2009).

• The dissemination of information via the Internet, such as web reporting, e-commerce models, or web-based business or services (e.g., [ 43 , 44 , 45 , 46 , 47 , 48 ]);
• The use, implementation, and implications of continuous auditing or continuous monitoring (for instance, [ 49 , 50 ]);
• The use or implementation of languages or taxonomies based on Extensible Markup Language (XML) or Extensible Business Reporting Language (XBRL), sometimes also linked to previous themes (e.g., [ 49 , 51 , 52 , 53 ]);
• The implementation of internal control system models in the IT area, such as control objectives for information and related technology (COBIT), the relevance of IT certification, such as WebTrust, and also the topics from the Information Systems Audit and Control Association (ISACA) curricula (for instance, [ 54 , 55 , 56 ]);
• Finally, although less incipient in this period, some studies on the emerging technologies from the beginning of this century, such as neural networks (e.g., [ 57 ]), or business intelligence (e.g., [ 21 ]).
• Accounting : accounting academics, accounting data points, accounting information, accounting knowledge, accounting research productivity, accounting system design, accounting systems research, accounting tasks , database accounting, differentiating accounting systems , financial accounting literature, leading accounting, managerial accounting perspective, quality accounting publication ;
• Audit : audit automation constructs, audit committees, audit documentation, audit engagement risk, audit opinion, audit trail, audit work, auditing education, auditing literature, computer-assisted auditing techniques, continuous audit, current audit environment , specific auditing concerns, various audit domains;
• Business : business clients, business information , business operations, business organizations, business process diagrams , business process level , business process modelling conventions , business world, Canadian business units, everyday business communications, extensible business, strategic business planning, web-based business;
• Control : control group, control objectives, control relationships, designing control systems , external controls, hierarchical control structures , informal controls, internal control, international control guideline, proper control procedures, using control charts;
• Data : accounting data points , data quality , data streams, data warehouses, electronic data interchange, financial data, including data flow diagrams, normal form data structure , numerical data increases, secondary data analysis, site data, specific data, spending data, underlying data trends, unnormalized data structure , using data;
• Decisions : bonus allocation decisions, decision aid research , decision aid use, decision aids, decision facilitation, decision process , investment decisions, management decision models , multiple decision, novice decision makers, operational decisions, repetitive choice decisions, repetitive valuation decisions, user decisions;
• Environment : alternative environments, continuous reporting environment, current audit environment, external environment, manufacturing environments, traditional reporting environment, virtual team environment;
• Individual : individual characteristics, individual decision-makers, individual determinants, individual faculty members, individual faculty productivity, individual level, individual provider attributes, individual units, judging individuals, perceiving individuals;
• Information : accounting information , advanced information technology , business information , computer-supported information systems , corporate reporting information, decision-making information, emerging information needs, emerging information technologies, financial reporting information, financial statement information, future-oriented information, human information processing, important information processing mechanism , information age, information content, information integrity attributes, information load, information location, information requests, information security, information system designs , information systems research , informationally equivalent, inter-organizational information sharing, low information quality seal , management information systems , management information value chain , nonfinancial information, online information, open information sharing, output information, preliminary information, specific information technology , supporting information technology , varied information, vast information source;
• Knowledge : accounting knowledge , additional knowledge, causing knowledge acquisition, expert-like knowledge structures , feedback impacts knowledge acquisition, filtering knowledge, improving knowledge workers, knowledge management focus , knowledge management practices , knowledge management system , procedural knowledge;
• Management : cost management systems, effective management , hybrid manager profile, impression management, knowledge management focus, knowledge management practices, knowledge management system, management decision models, management information systems, management information value chain , senior managers, top management support;
• Model : business process modelling conventions , conceptual model, contingency model, enterprise modelling, er model, management decision models , mathematical model, research model , residual income valuation model, task circumplex model , theoretical model;
• Performance : firm performance, managerial end-user performance , organisational performance, organizational performance, performance evaluation, performance outcomes, subsequent decision-making performance, superior performance, task performance , traditional performance measures;
• Process : assurance process, business process diagrams, business process level, business process modeling conventions , decision process, event process chains, extensive sample selection process, human information processing, important information processing mechanism , little processing, process level risk assessment, processing view, production processes, stable processes, standard development process;
• Quality : data quality , disseminating quality, low information quality seal , quality accounting publication , quality measurement component, quality outlets, quality perspective, service quality, system quality ;
• Research : accounting research productivity , accounting systems research , additional research, ais research, attitudinal ambivalence research, case research, current research work, decision aid research, development research, empirical research, field research, future research, information systems research , little research, past research, previous research, prior research, recent research, research community, research domain, research findings, research hypotheses, research instrument, research issues, research method opportunities, research model , research propositions, research prototype system , research questions, research survey, rich research opportunities, various research methods;
• System: accounting system design, accounting systems research , alternative measurement systems, automated record system, computer-supported information systems, cost management systems , current system, designing control systems, differentiating accounting systems, electronic audit-work paper system , enterprise systems implementation, expert system groups, expert system types, expert system users, information system designs, information systems research, key system components, knowledge management system, management information systems , medical record system, research prototype system , successful system, system acceptance, system acquisition, system design alternatives, system effectiveness , system implementation changes, system integration, system outputs, system quality , system transformation, system usage, systems design scenarios, tertiary assurance system, work systems;
• Task : accounting tasks , brainstorming tasks, complex tasks, decision-making tasks, financial tasks, optimisation tasks, querying tasks, simple tasks, specific design tasks , task accuracy, task characteristics, task circumplex model , task completion, task force, task performance , task requirements, task routineness;
• Technology: advanced information technology, emerging information technologies, emerging technologies, learning technology, specific information technology, supporting information technology, technological advances, technological determinism, technological discourse, technology complexities, technology features, technology fit, technology medium;
• Use: auditor use , continued use, decision aid use, expert system users , user acceptance, user decisions , user requests, user satisfaction, using activity, using control charts , using data , using eighty-nine, using paper methods.

2.2.2. Results for the Second Period (2010 to 2019)

• Continuous auditing or continuous monitoring (e.g., [ 68 , 69 , 70 , 71 , 72 ]);
• Languages or taxonomies based on XML (less expressive) or XBRL, in a more expressive number than those found in the previous period (e.g., [ 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 ]);
• Business intelligence or business analytics (mostly) (e.g., [ 19 , 81 , 82 , 83 ]);
• Artificial intelligence, data analytics, big data treatment, and the use of machine learning and data mining techniques (mostly), which are sometimes associated with previous themes and, in many cases, dedicated to the definition of processes related to the detection of fraud, misreporting or tax evasion (e.g., [ 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 ]);
• Cloud computing (e.g., [ 67 , 93 , 94 , 95 ]);
• Blockchain-based technologies, which are mostly evidenced at the end of this decade (for instance, [ 96 , 97 ]).
• Accounting : 129 accounting students, accounting benefits, accounting domains, accounting information systems academics , accounting information systems field , accounting journals, accounting literature, accounting processes , accounting publications, accounting researchers , accounting standards , annual bank account balances, especially management accounting, firm accounting performance, outsourcing accounting functions ;
• Audit : audit analytics, audit arena, audit fraud brainstorming , audit process , audit standards , audit support systems , audit team, auditing literature, budgeted audit hours, chief audit executives, computer audit specialist, continuous auditing methodology, current audit practice , financial audits, internal audit function , internal auditing department, prior year audit, reduced audit fee increases , small audit firms , traditional audit paradigm ;
• Business : business networks, business operations, business process agility , business process standards , business value research , computing-related business objectives, existing business processes , extensible business, hindering business efforts, intermediate business processes , overall business performance , reporting business information ;
• Control : control compliance, control issues, corrective controls, effective controls, ineffective controls, informal management control systems , internal control deficiencies, internal control environment, internal control overrides, internal control reporting requirements , internal control weakness, internal control weaknesses, it-related controls;
• Data: applying data mining techniques, corporate data, data analysis tool, data patterns, descriptive data mining approach, descriptive data mining strategy, financial data, global data ecosystem, journal entry data sets, out-of-sample data, panel data, perceptive field survey data, precise data values, prediction data mining techniques, process-level data, procurement data, proprietary data, quantitative data, researching journal entry data mining, semi-monthly data, soft copy data, tagged data, using data;
• Decisions : compared decisions, deception detection decision aid, decision aid reliability, decision aid reliance behavior, decision aids, decision problems, decision processes , decision trees, experimental decision aid research spans , governance decision making , optimal decision, outsourcing decision, reliance decision;
• Disclosure : cybersecurity disclosure guidance , cybersecurity risk disclosure , disclosure credibility, disclosure role, environmental disclosures, extensive disclosure, financial statement disclosures , improving disclosure timeliness, issuing video disclosures, unauthorized disclosure;
• Effective : brainstorming effectiveness, compromising regulation effectiveness, detrimental effect, differential effect, effective controls , halo effect, information environment effects , interactive effect, mean effects, positive effect, profound effect;
• Firm : aggregate firm level, appointing firms, durable goods industry firms, firm accounting performance , firm productivity, firm profitability, firm value , firm years, registered firms, small audit firms , superior firm performance , threatened firms;
• Function : bi-planning functionality, bi-reporting functionality , incompatible functions, internal audit function , outsourcing accounting functions;
• Information: accounting information systems academics, accounting information systems field, bank trading information systems , capturing context information, chief information officer, deceptive information, detail-tagged footnote information, financial reporting information, health information technology expenses , information asymmetry, information environment effects, information quality , information release, information security risk management, information systems professionals, information systems researchers, information technology literature, information technology outsourcing , integrating information, performance measurement information , qualitative information, recent high-profile information security breach incidents, reporting business information, risk information increases , supplemental information displays, ™ information processing costs, user satisfaction measure information system success, using information ;
• Management : bank management, cloud management committee, entail managers, environmental management approach, especially management accounting, informal management control systems, information security risk management , management assertions, management support, managing expectations, resource management;
• Measures : measuring spreadsheet infusion, perceptual measures, performance measurement capabilities, performance measurement information, quality measures , quantitative measure, strategic performance measurement system , subjective measures, user satisfaction measure information system success ;
• Performance : average performance, firm accounting performance, firm-level performance , future performance goals, internal process-level performance , organizational performance, overall business performance, performance measurement capabilities, performance measurement information, strategic performance measurement system, superior firm performance , supply chain performance;
• Process: accounting processes, assurance process, audit process, business process agility, business process standards , close process, decision processes , estimation process, existing business processes , implementation processes, intermediate business processes , labor process, manual process, natural language processing, order fulfilment processes, process efficiency, process level, strategic erm processes, ™ information processing costs , work processes;
• Reporting : annual reports, digital reporting, discretionary reporting, financial reporting information, financial reporting systems, internal control reporting requirements , internet reporting, reporting business information , reporting language, reporting timeliness, required reporting deadlines, standard reports, traditional business-to-government reporting ;
• Research : artificial intelligence research, broad research streams, business value research , collaborative design research, experimental decision aid research spans , expert systems research , future research, multi-method research, potential research, prior research, research discipline, research environments, research methodology, research perspectives, research program, research quality , research settings , researching journal entry data mining , right research, traditional research classification ;
• System : 43 expert systems, accounting information systems academics, accounting information systems field , accounting-related expert systems papers, audit support systems , automated systems, bank trading information systems , computer-mediated communication system, decision-aid system , enterprise resource planning systems adoption, enterprise systems results, expert system publications, expert systems research, financial reporting systems, incentive systems, informal management control systems, information systems professionals, information systems researchers , manual systems, restrictive systems, strategic performance measurement system, system quality , transparent system, user satisfaction measure information system success ;
• Technological: health information technology expenses, information technology literature, information technology outsourcing , supporting technologies, technological competence , technological domain, technological solutions, technology dominance;
• Using : emergent use, managerial use, media use, practice use , spreadsheet use, user satisfaction measure information system success, using activity theory, using data , using a hospital, using information , using responses.

2.2.3. Results for the Latest Period (2020 to 2022)

• Accounting : 136 accounting professionals, accounting context, accounting data, accounting fraud data mining literature, accounting fraud detection models, accounting information systems case study, accounting information systems scholars, accounting literature , aggregated accounting numbers, cloud-based client accounting, developing accounting information systems , different accounting standards, highest-ranked accounting journals, laggard accounting systems, management accounting , professional accounting bodies, recent accounting fraud theory, robust account;
• Audit : 4 audit firms , asset-related audits, audit conclusions, audit fee premiums, audit framework, audit hours, audit personnel, audit practice, audited entity, auditing parties, auditing profession, computer-assisted audit tools, contemporary audit standards, continuous audit procedures, cybersecurity audit effectiveness , digital audit evidence, financial statement audits, improving audit quality , increasing audit productivity, internal control audit work , manual audit procedures, recurring audit deficiencies, relevant audit standards, reliable audit evidence;
• Business : business digitization, business information technology intensity , business model transformation indices, business operations, business processes , business professionals, business rules, general business descriptions, increasing business competition, strategic business partner role;
• Case : accounting information systems case study, compelling use case, in-depth case study, participatory case study, specific case, various use cases;
• Cybersecurity : 52 cybersecurity comment letters, cybersecurity audit effectiveness , cybersecurity breach incidents, cybersecurity incidents, cybersecurity risk disclosure practices , cybersecurity risk disclosure trends , organizational cybersecurity risk exposure, overall cybersecurity risks, proprietary cybersecurity information , regarding cybersecurity;
• Data : accounting data , accounting fraud data mining literature , available data, big data capabilities, big data technologies , climate data, collected data, data analytics, data breach, data processing integrity , data quality research , data standards, data visualization software, financial data, general ledger data, interactive data visualization, interview data, legal-entity data segmentation, novel data analysis technique, novel data mining technique, real-life data, social media data, textual data, unstructured data, using data ;
• Disclosures : corporate disclosures, cryptocurrency disclosures, cybersecurity risk disclosure practices , cybersecurity risk disclosure trends , disclosure location, firm disclosures , remediation disclosures;
• Firms : 4 audit firms , adopting firm, firm disclosures , firm resource, firm samples, firm size, firm tenure, incentivizing client firms, Korean-listed firms;
• Information: accounting information systems, accounting information systems case study, accounting information systems scholars, agricultural information systems , budget information, business information technology intensity , clarifying information, developing accounting information systems , existing information systems, information content, information dissemination, information overload, information processing capabilities, information quality, information systems discipline, information systems theories, information technology experts, integrated information systems, personal information management capabilities , private information, proprietary cybersecurity information , qualitative information, quantitative information, social responsibility information, specific value information, text information;
• Literature : accounting fraud data mining literature , accounting literature , current literature, existing literature, extensive literature review, natural language processing literature , prior literature, research literature, systematic literature review;
• Management: cyber risk management effectiveness, cyber risk management maturity, knowledge management research, management accountants, management accounting, management reporting , personal information management capabilities, supply chain management, top management commitment, top management support, workflow management;
• Model : accounting fraud detection models , business model transformation indices , developed models, digital maturity model, filed model, force field model , model performance, predictive models, proposed model, research model, theoretical model, wave theory life cycle model ;
• Reporting : financial reporting, management reporting , report length, social responsibility reports, unique reporting requirements;
• Research : answering research questions, data quality research , design science research contribution, empirical research, extending research, future research, knowledge management research , prior research, recent research, research initiative, research literature , research model , research studies;
• Risk: cyber risk management effectiveness, cyber risk management maturity, cybersecurity risk disclosure practices, cybersecurity risk disclosure trends, organizational cybersecurity risk exposure, overall cybersecurity risks , regulation risks, risk assessment;
• Service : assurance services, consumer services, payment services, service components, service quality , shared service mode;
• Study: accounting information systems case study , cross-sectional field study, existing studies, in-depth case study , longitudinal study, multi-case study approach, participatory case study, research studies ;
• System: accounting information systems, accounting information systems case study, accounting information systems scholars, agricultural information systems, developing accounting information systems, enterprise resource planning system design agenda, existing information systems, information systems discipline, information systems theories, integrated information systems, intelligent systems, laggard accounting systems, system quality, system usage;
• Technology : above-mentioned technologies, big data technologies, blockchain technology applications, blockchain technology solutions, business information technology intensity , computer technology, emerging technology adoption, information technology experts , learning technologies, ledger technology, past technology experience, technological advancements, technological developments, trending technology;
• Use : compelling use case , cost-effective use , decision-making use, effective use , organizational use, user satisfaction, using data , using DevOps, using propensity score, various use cases .
• A more diversified set of subtopics within the topics found;
• The increasing relevance of matters regarding social responsibility, climate, and budgetary information;
• A more evident link, from the subtopics, identified, between accounting and other social sciences through the consideration or inclusion of a wide-ranging of explanatory factors, such as “individual factors”, “environmental factors”, “organizational complexity factors”, “psychological factors”, and “social-psychological factors”;
• A diverse set of underlying theories and research methods used, particularly those focusing on case and experimental studies, as well as literature reviews (for this reason, “case”, “study”, and “literature” appears as novelties within the most relevant topics, besides those previously found, such as “research” and “model”);
• Besides general references to “emergent technologies” or “trending technologies”, the most significant number of indications on specific uses of those tools as precise topics or subtopics, for instance, “blockchain”, “crypto assets” or “cryptocurrencies”, “intelligent systems”, “cloud-based accounting”, “big data”, “data analytics”, “data mining, “learning technologies”, and “natural language”;
• “Risk”, “cybersecurity” and “tax” are included in the set of main topics, which demonstrates the growing relevance of those topics (the latter as a particular novelty for this period).

3. Discussion

3.1. research limitations, 3.2. future avenues in accounting and information system research, author contributions, data availability statement, conflicts of interest.

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Albuquerque, F.; Dos Santos, P.G. Recent Trends in Accounting and Information System Research: A Literature Review Using Textual Analysis Tools. FinTech 2023 , 2 , 248-274. https://doi.org/10.3390/fintech2020015

Albuquerque F, Dos Santos PG. Recent Trends in Accounting and Information System Research: A Literature Review Using Textual Analysis Tools. FinTech . 2023; 2(2):248-274. https://doi.org/10.3390/fintech2020015

Albuquerque, Fábio, and Paula Gomes Dos Santos. 2023. "Recent Trends in Accounting and Information System Research: A Literature Review Using Textual Analysis Tools" FinTech 2, no. 2: 248-274. https://doi.org/10.3390/fintech2020015

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The Impact of Accounting Information System on the Organizations Financial Performance

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• Thabet Yusuf AlBastaki 11 &
• Allam Hamdan 12  

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In the face of fast technological progress, increasing knowledge, and difficult demands from businesses and customers, an accounting information system is an essential instrument in the hands of managers seeking to sustainable competitive advantage. The impact of accounting information systems on organizations financial performance is investigated in this study. The primary goal of this paper is to review the theoretical and conceptual basis as well as research findings on accounting information systems and company financial performance. According to the findings of the review, previous studies on the impact of accounting information on financial performance focused on the cost implications of accounting information systems as they relate to corporate financial performance. The vast majority of studies used a survey study methodology to investigate this link, and the rest of the researches were conducted in industrialized economies where accounting information systems technologies have been extensively adopted. As a result, this study suggests that further research should done in this area to close this research gap.

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AlBastaki, T.Y., Hamdan, A. (2023). The Impact of Accounting Information System on the Organizations Financial Performance. In: Alareeni, B., Hamdan, A. (eds) Sustainable Finance, Digitalization and the Role of Technology. ICBT 2021. Lecture Notes in Networks and Systems, vol 487. Springer, Cham. https://doi.org/10.1007/978-3-031-08084-5_5

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Accounting Information Systems and Ethics Research: Review, Synthesis, and the Future

We thank Roger Debreceny, Mary Curtis, anonymous reviewers, and participants at the 2015 Midyear Meeting of the Accounting Information Systems Section of the AAA for their helpful suggestions and comments.

Supplemental material can be accessed by clicking the link in Appendix A.

Editor's note: Accepted by Roger S. Debreceny.

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Binod Guragai , Nicholas C. Hunt , Marc P. Neri , Eileen Z. Taylor; Accounting Information Systems and Ethics Research: Review, Synthesis, and the Future. Journal of Information Systems 1 June 2017; 31 (2): 65–81. https://doi.org/10.2308/isys-51265

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The rapid evolution of technology and the increasingly integrated nature of Accounting Information Systems (AIS) in business provide opportunities for those who interact with these systems to act unethically. Accountants, as the managers of accounting information systems and gatekeepers of assets, records, and reporting, have a responsibility to understand and address ethical dilemmas related to these responsibilities in their organizations. A summary of AIS and ethics research calls attention to gaps in the literature and provides directions for future research. The ETHOs framework, which categorizes factors as environmental, technological, human, and organizational, provides a model for researchers to examine ethical issues related to the AIS functions of recordkeeping, reporting, and control.

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INTRODUCTION

Literature review and research questions, research methodology, data analysis and findings, author acknowledgements, appendix a – questionnaire, topics for your undergraduate accounting information systems (ais) course-an exploratory study of information technology (it) skills and firm size.

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Leslie Weisenfeld , Sathasivam Mathiyalakan , George Heilman; Topics for Your Undergraduate Accounting Information Systems (AIS) Course-An Exploratory Study of Information Technology (IT) Skills and Firm Size. AIS Educator Journal 1 January 2020; 15 (1): 58–89. doi: https://doi.org/10.3194/1935-8156-15.1.58

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Given the wide range of technologies that businesses employ, and the rapid changes in technology, it is important to assess periodically the critical IT skills students need to prepare them for the work environment. This study presents results from over 100 practicing accountants regarding the IT skills they feel are most important for an undergraduate AIS course. The top ten IT skills for small firm (SF) respondents, respectively, are: spreadsheets, Microsoft Word, Internet research, Internet, QuickBooks, ensuring privacy, Cloud Computing, preventing and responding to cybercrime, software security, and managing and retaining data. The top ten IT skills for medium-large firm (MLF) respondents, respectively, are: spreadsheets, Internet, Internet research, ensuring privacy, Microsoft Word, preventing and responding to cybercrime, managing and retaining data, file systems, Cloud Computing, and Business Intelligence Tools. While SF respondents perceive QuickBooks and software security are more important, respondents from MLF think file systems and Business Intelligence Tools are more important. When determining AIS course content it is important to include the most relevant IT skills, based on what practice thinks students need, and this study indicates firm size is a factor for some IT skills. Designers of undergraduate AIS courses, therefore, need to consider the importance of the IT skills in conjunction with the size of the firms that will employ their students when selecting topics for inclusion.

Since the mid-1980s, there has been growing interest regarding the most important topics to include in an undergraduate AIS course. Researchers such as Theuri and Gunn (1998) , Badua, Sharifi, and Watkins (2011) , Dillon and Kruck (2008) , and Apostolou, Dorminey, Hassell, and Rebele (2014) explore topics on AIS course and textbook content and articles in accounting education and information systems journals (employers' needs, academic versus practitioners' views, and accounting students' perceptions). Rebele and St. Pierre (2015) note, however, that the body of literature is relatively small. Franklin's (2017) review of articles in the 2015 issues of five leading accounting education journals ( Issues in Accounting Education, Journal of Accounting Education, Accounting Education: An International Journal, Advances in Accounting Education, and The Accounting Educators' Journal ) also supports this view since only five percent of the articles relate to technology. Rebele and St. Pierre (2015) further point out that there is little agreement about the most important topics to cover, partly due to the rapid changes in technology. As a result, they maintain that researchers can make an important contribution by focusing on topics to cover and integration of them into the accounting curriculum. Furthermore, since technological innovations are rapid and ever occurring it is important, periodically, to assess what accounting practitioners think are the most important IT skills for an undergraduate AIS course.

In response to the Pathways Commission on Accounting Higher Education Report ( AAA, 2012 ), researchers ( Behn et al. 2012 ; Bloom, 2013 ) continue to call for more academic/practitioner collaboration to ensure accounting education and research keeps pace with practice. Harper and Dunn (2018) further encourage accounting educators to expose students to current and emerging technologies they will need in the work environment. As Drew (2012) notes, the future for accountants may be 100 percent virtual, that is, no offices, employees will work remotely, clients will be digital (no paper anymore), and technology will facilitate all of this.

Qian, Ward, and Blaskovich (2012) maintain IT has revolutionized business and created new expectations for the accounting profession since the need for technology-based knowledge and skills is ever increasing. Similarly, Bradbard, Alvis, and Morris (2014) suggest, “IT in general and spreadsheets in particular have a significant impact on changing the accountant's role in business organizations. Specifically, accounting practitioners are expected to play a much larger role in institution-wide problem solving and managerial decision making” (p. 25). Coyne, Coyne, and Walker (2016) also conclude there is a need to integrate IT within and across organizations, and information security and data integrity are a prerequisite.

Sledgianowski, Gomaa, and Tan (2017) suggest the increase in AIS emphasis since 2002 is due to Section 404 of the Sarbanes-Oxley Act (SOX) and the work of professional accrediting bodies. They point to the importance of QuickBooks, Quicken, SAP, ERP, XBRL, Generalized Audit Software, Tableau Software (visualization and data analytics), Microsoft Project, Visio, Access, flowcharts, Databases, and Presentation Software (PowerPoint) and provide an extensive discussion on incorporating various software into existing courses.

Technology competencies include the use of software, including proficiency in the development and use of spreadsheet models and the use of technology to enhance communication. Also vital is knowledge of the purpose and design of information systems (IS), system architecture, processing modes, network types, hardware components (including mobile devices), operating and application software (including cloud computing), system security, and IS continuity (p. 301).

Much of the employer needs research relies on surveys of Certified Public Accountants (CPAs) primarily in large public accounting firms. Lee, Kerler, and Ivancevich (2018) indicate their respondents are CPAs in “public accounting since it represents entry-level job placement for many graduates of Accounting Master's programs” (p. 47). The majority of undergraduate accounting students, however, do not go into, or do not stay in, large public accounting firms and addressing their needs is important when identifying topics for an undergraduate AIS course ( Schea, 2008 ; Siegel, Sorensen, Klammer, & Richtermeyer, 2010 ). Also, Gabbin (2019) finds only 43 percent of his school's 2018 undergraduate students are in the seven largest CPA firms while 34 percent and 23 percent, respectively, are with other CPA firms or non-CPA firms. Additionally, Tatikonda (2004) notes that, while the majority of accounting programs focus on curricula issues in relation to the CPA exam “two-thirds of accounting graduates take jobs outside public accounting and have no interest in taking the CPA exam” (p. 63).

Accounting graduates' declining interest in public accounting as a career choice is evident in the year-by-year comparison of new CPA exam candidates. The American Institute of Certified Public Accountants' (AICPA) 2019 Trends Report indicates the number of new CPA candidates in 2018 (36,827) is only slightly higher than the 2006 number (36,078). For the period 2006–2018 the largest number of new CPA candidates is in 2010 (49,597) revealing a 26 percent decline from 2010 to 2018. A similar comparison by the Institute of Management Accountants (IMA) indicates the number of new candidates (49,862) joining the Certified Management Accounting (CMA) program as of June 30, 2019 represents a 26 percent increase over the previous year ( IMA, 2019 ). Analyzing these numbers reveals that new CMA exam candidates in 2018 (39,513) exceeds the number of new CPA exam candidates by 2,686. Since the CPA credential is generally recognized as the “public accounting credential,” while the CMA is not, the increasing number of new CMA exam candidates suggests more accounting graduates are pursuing careers outside of public accounting.

This research takes a deep dive into IT skills by asking accountants to indicate the importance of 62 distinct IT skills used in practice to inform undergraduate AIS course curriculum. This study attempts to overcome previous studies' limitations by surveying practicing accountants who are not working primarily in large public accounting firms and focusing solely on IT skills for an undergraduate AIS course. The respondents' demographics ( Table 1 : Respondent Characteristics) indicate 64 percent (71/111) are in SF. The questionnaire includes IT skills from undergraduate AIS textbooks, as well as journal articles. This research adds to the existing literature since 16 of the 20 Top IT Skills shown in Table 3 (Firm Size and Top 27 IT Skills) are new; previous studies did not rank, most likely due to changes in technology. The 16 new IT skills this study ranks are: Internet, ensuring privacy, preventing and responding to cybercrime, QuickBooks, Cloud Computing, managing and retaining data, software security, file systems, Password Management Tools, preventing and responding to computer fraud, Virtual Office Technology, IT controls, Information Security Technology, data loss prevention, software implementation, and Business Intelligence Tools.

Respondent Characteristics

Due to rapid changes in technology, it is likely that the importance of at least some IT skills for accountants will change over time. Since the purpose of this study is to identify the IT skills accounting practitioners think are currently important for an undergraduate AIS course, the following literature review provides an in-depth review of the various IT skills assessed in previous research (2008–2016). A historical perspective on the distinct IT skills and their rankings is necessary since it provides the basis for particular IT skills inclusion in this study's questionnaire 1 and a comparison of this study's results with previous ranking studies to determine if there are changes in the importance of IT skills over time (  Appendix B —Rankings of IT Skills 2 ). Additionally, this study replicates previous ranking studies, includes analysis of 62 distinct IT skills, 3 and provides an update on the IT skills practicing accountants think are important for an undergraduate AIS course.

Textbooks and Syllabi

Badua et al. (2011) maintain textbooks may be a major factor in AIS courses' topical coverage. Their review of four textbooks (2010–2012) reveals 15 broad areas ranging from AIS and Accountants to Electronic Commerce and the Internet, and 119 specific topic areas. Additionally, their surveys of AIS faculty indicate 90 percent use a textbook, 30 percent have an AIS concentration at their school, 34 percent prefer one AIS course, and 58 percent prefer two AIS courses. Given the large number of diverse topics in AIS textbooks and the expanding role of IT and IT topics, Badua et al. (2011) conclude it may be impossible to agree on AIS topics for a single course and a second course may be necessary. Many accounting programs, however, may not have the ability to offer two AIS courses, so the question of what topics to cover remains important.

Coyne et al.'s (2016) analysis of 19 Current and Proposed IT topics reveals “current AIS curricula teach few technologies” (p. 165) and future AIS curricula need to focus more on practical tools and software since the separation between IT functions and accounting is rapidly disappearing. Traditional Management Information Systems (MIS) courses do address these more technical IT functions so some accounting programs may be able to take advantage of MIS courses if their school has them. Murthy and Ragland's (2009) comparison of topics in AIS and MIS classes reveals similar coverage for Database/Data Management Systems, Systems Analysis and Design/Development, DBMS/Access Projects, and E-Business, while the more technical IT topics (security, hardware and software, networking, and outsourcing) are not generally covered in AIS courses. Other studies also look at topics in AIS journals. For instance, Apostolou et al.'s (2014) review of AIS articles identifies six general areas (software implementation, software security, system controls, system design, transaction processes and controls, and XBRL), that indicates some increasing interest in more technical IT topics with the passage of time.

Student Perceptions

AIS course research also analyzes accounting students' perceptions. For example, Harrast, Strong, and Bromley's (2010) study indicates students desire more integration of technology in their curriculum and prefer to have more hands-on practice. Kearns' (2010) survey of accounting majors reveals students believe IT knowledge and skills are important and will help them perform better during their career. The validity of this perception receives support from Cory and Huttenhoff's (2011) analysis suggesting information systems skills are very important for undergraduate accounting majors since Information Systems ranks fifth, ahead of Auditing, Strategy, Cost/Managerial Accounting, Business Law, and Financial Accounting Research.

Unfortunately, student perceptions of their IT abilities may not match that of their employers. Yu, Churyk, and Chang's (2013) results reveal accounting student interns rate their IT capabilities higher than their employers do. Strong and Portz's (2015) analysis of student perceptions finds significant differences across three universities for 36 technologies, leading them to conclude the finding is likely due to the lack of a set curriculum for AIS courses and future research should help determine what IT skills undergraduate accounting majors need upon entering the profession.

Employers, Academics, and Practitioners

Dillon and Kruck's (2008) employer survey of 56 core content areas includes both IT and non-IT items. Excluding the non-IT items provides rankings for 25 IT Skills (  Appendix B — Rankings of IT Skills). The top 15 IT areas, respectively, are: spreadsheets, AIS Auditing/Generalized Audit Software, operating systems, network security, Project Management, ERP, Databases, input/output devices, Electronic Commerce, IT gathering techniques, disaster recovery and contingency planning, Data Modeling, Local Area Networks, systems implementation and testing, and system maintenance. Chen et al.'s (2009) analysis of 29 IT competencies, using employer recruiters, reveals the top 15 IT skills are, respectively: spreadsheets, Business Graphics Software, Word Processing Software, Presentation Software, Audit Software, Tax Preparation Software, Small Business Systems, Databases, Computerized Accounting Packages, IT assurance, Communication Software, operating/managing own system, network security, operating systems, and Decision Support Software.

Welch, Madison, and Welch's (2010) survey of accountants in CPA firms and Industry/Government (IG) provides rankings for 24 IT skills. Their results indicate both groups agree on the top three skills (spreadsheets, Word Processing Software, and Windows Software). While the CPA group's fourth, fifth, and sixth rankings, respectively, are Internet research, Presentation Software, and AIS Auditing/Generalized Audit Software, the IG group's rankings are Databases and Presentation Software, Internet research, and technology terminology. For rankings seven to 15 both groups rank network security, Computer Hardware, Intranet, Project Management, system evaluation, IT operations, data analysis, Telecommunication Software, technology management, and Collaboration Software in this range, although where they rank them varies. While the CPA group ranks technology terminology (7), Databases (8), and Business Graphics Software and client/server management (15), the IG group ranks AIS Auditing/Generalized Audit Software (11) and does not rank Business Graphics Software and client/server management in the seven to 15 range.

Cory and Pruske's (2012) survey utilizing public and non-public accountants identifies six IT skills both groups think are important; Excel, Word, Windows, Internet research, Presentation Software, and Database Software. A later study ( Kearns, 2014 ), surveying CPAs reveals the following ranking of eight IT skills: Spreadsheet Tools, Governance/Internal Controls, Database Tools, fraud detection and prevention, Computer Networks, IT Security, XBRL, and Audit Software Tools. Winstead and Wenger's (2015) survey of academicians and practicing accountants indicates both groups agree on the importance of operating systems, Software Packages, and Report Software, while practitioners feel Business Cycles, Data Sharing, XBRL, Problem Solving Technology, E-Commerce, and safeguarding electronic accounting records are less important. Lee et al.'s (2018) survey of graduates from a Masters of Accountancy program regarding the importance of Software Tools for new hires reveals Excel is the most important tool, followed by Adobe Acrobat, FASB Codification, and PowerPoint.

IT and Firm Size

Research investigating firm size and use of IT is somewhat limited. Kagan, Lau, and Nusgart (1990) report large firms use more sophisticated information systems than smaller ones. Burke's (2005) exploration of firm size, use of the Internet, websites, e-mail, online research, and non-Internet-based computer systems reveals small businesses are less likely to use the Internet, websites, and non-Internet-based computer systems than large businesses, and significant differences exist in relation to firm size for all variables except e-mail. Additionally, Thong (1999) finds firm size relates to both the likelihood of and extent of information systems adoption. Fordham and Hamilton's study (2019) also reveals the majority of small businesses rely on manual rather than computer-based systems.

Cloud Computing makes possible three types of services, Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS), and Infrastructure-as-a-Service (IaaS). Gupta, Seetharaman, and Raj (2013) suggest small businesses adopt Cloud Computing because it provides cost savings, is easy to use, convenient for work outside the office, reliable, improves the ability for sharing and collaboration, and provides better security and privacy. Low and Chen (2011) and Oliveria, Thomas, and Espadanal (2014) , however, note firm size has a positive effect on the decision to adopt Cloud Computing and large firms have an advantage over small firms. On the other hand, Gupta et al. (2013) suggest size may not be an important factor since the decision to adopt Cloud Computing relates positively to perceptions of cost savings, ease of use, security and privacy, and negatively to issues surrounding reliability, sharing, and collaboration.

Similarly, Seethamraju (2015) maintains SaaS makes it cost effective for small and medium size enterprises to use SaaS Enterprise Resource Planning so firm size should not be a consideration. The key factors in the adoption decision are reputation of the vendor, willingness of the vendor to work with the customer from beginning to end, ability to shift capital expenditures to operating expenses, functionality of the software, and ease of use ( Seethamraju, 2015 ). Likewise, Loukis, Arvanitis, and Kyriakou (2017) indicate firm size has no impact on the decision to use Cloud Computing, and Smith (2016) suggests managed analytics as a service makes Big Data analysis affordable for even smaller companies.

Research Question One (RQ1)

For smaller employers, proficiency in software (QB, tax, excel, etc.) is the most important.

I work for a small, local CPA firm. Our CPAs wear many hats—accounting, tax, financial planning, Excel, QB, Word.

Most small businesses and local CPA firms do not have IT Specialists. Accountants need to know how to trouble shoot problems and talk in plain language about technology issues. When helping my clients with their accounting software adjustments and accounting questions, the answer is sometimes related to the operating system.

Great that you ask all these questions about tech and emerging tech. In reality most firms I know contract out IT services and would never have a new hire handling these issues. Also, while some large firms may need many of these remote areas for a few big clients, most small businesses are not willing to pay a CPA firm to do data mining etc. Clients want us to perform using the core programs they use (MS products, QBooks, etc.) so we can get the work they need out quickly and cost effectively.

From the tone of your questions, you seemed to be interested only in large firms. Smaller firms will have varying degrees of importance related to your questions. I have a small firm and while all of these questions were relevant to large firms, a lot of them were not so relevant to small firms. But being able to adapt to any IT is a plus for any future accountant.

We are a small office with myself as CFO with 1 full time and 1part time assistant. Our IT department takes care of security and software issues, including upgrading our software, and the majority of electronic commerce issues. I look at new technology for assisting with accounting and work with our IT for feasibility and implementation. There is a lot of “”stuff”” out there that either does not or cannot work, or is not needed within the realm of our government entity.

Responses are from an owner of a single person CPA firm that only uses help on an as needed basis. Any staffing needed would be done through a part time staffing agency. However, responses were made on the basis of qualities and attributes desired IF permanent staffing was being considered.

I own and run a small CPA office with 2 individuals plus myself. We primarily do payroll, bookkeeping and tax returns.

Understanding how databases work has been one of the most important things I learned in college. I am an average small business accountant and it has been invaluable knowledge.

I honestly didn't know what many of these terms are referring to. So I checked not important on most of them. Survey didn't seem applicable to a small CPA firm. Maybe I should have checked “”regional CPA firm”” instead of “”other”” as my organization type?

Since 40 percent (10/25) of the respondents that provided written comments indicate size may be a factor in the importance of an IT skill for accountants, RQ1 is: Does the size of the respondent's firm impact the perception of an IT skill's importance?

Research Question Two (RQ2)

There is one point of commonality in the preceding accounting IT research; all the studies identify spreadsheets as the most important IT skill. The ranking of other IT skills varies by study. For instance, hardware, Project Management, Databases, ERP, system design and maintenance, Programming Languages, and system implementation and testing rankings change over time (  Appendix B —Rankings of IT Skills). The change in IT skills' importance over time is not surprising given the rapid changes in technology. As a result, it is important to take the pulse of practice periodically and identify IT skills undergraduate accounting majors need. Since most accounting programs offer at least one undergraduate AIS course to expose their students to necessary IT skills the purpose of this research is to assess what practicing accountants think are the most important IT skills, currently, for an undergraduate AIS course, RQ2 is: What are the important IT skills for an undergraduate AIS course?

Questionnaire Design

The questionnaire's sections include basic demographic information, organizational and employment characteristics, and 62 IT skills representing six categories employing a typical MIS classification scheme (data acquisition, retention and use, infrastructure, system development and/or acquisition, tools, Internet, and governance). The questionnaire utilizes a traditional five-point Likert Scale ranging from Not Important (1) to Very Important (5) for all questions except those in the demographic and organizational and employment characteristics sections. Two questions regarding the importance of IT/accountant cooperation and COBIT are beyond the scope of this paper and are in the questionnaire to gather initial information for future research. The last item asks respondents to share any additional information they feel is important (  Appendix A — Questionnaire).

The questionnaire's IT skills are primarily from previous AIS survey research ranking IT skills ( Dillon & Kruck, 2008 ; Chen et al., 2009 ; Welch et al., 2010 ), textbook topics ( Badua et al., 2011 ), and current and proposed AIS course topics ( Coyne et al., 2016 ). Additionally, 11 IT skills (managing and retaining data, software security, Password Management Tools, data loss prevention, Social Media, HTML, managing vendors and service providers, Block Chain Accounting, Value Added Networks, governing/managing IT investment/spending, and Open Source Software) the authors think might be important to provide an up-to-date ranking of IT skills (  Appendix B —Rankings of IT Skills) were added.

Questionnaire Administration

The questionnaire using Survey Monkey was available on the North Carolina Association of Certified Public Accountants' (NCACPA) Open Forum. The NCACPA's Open Forum requires members have a user name and password and is available through the Connect function on their website. The Open Forum 4 is essentially a place where NCACPA members can go to pose questions they need help with and other members can respond if they have something to say; during the period the questionnaire was available the NCACPA estimates they had 1131 users on the Open Forum (NCACPA staff member in charge of the Open Forum, personal communication, January 29, 2018). The solicitation of NCACPA members' participation used the following two messages in the Open Forum:

The initial posting (October 26, 2017)

I teach accounting courses and recently had an Accounting Information Systems (AIS) course added to my load. I think it is important to make sure students are adequately prepared for the work environment they will be entering. The AIS needs survey (contained in link below) asks questions related to information technology skills you think accounting graduates need and will take about 10 minutes. Your input is very important in helping me design an AIS course that meets the needs of the current accounting environment. Thank-you for your help. Link was here

The reminder posting (January 11, 2018)

YOUR INPUT IS NEEDED- PLEASE Complete this Accounting Information Needs Survey (if you have not done so already). I teach accounting courses and recently had an Accounting Information Systems (AIS) course added to my load. I think it is important to make sure students are adequately prepared for the work environment they will be entering. The AIS needs survey (contained in link below) asks questions related to information technology skills you think accounting graduates need and will take about 10 minutes. Your input is very important in helping me design an AIS course that meets the needs of the current accounting environment. [Link was here] Thank-you for your help and please complete the entire survey (for the Information Technology skills questions the response I don't know has been provided so that you can complete all items).

Of the 154 survey submittals, 111 are usable, 5 and the effective response rate 6 ranges from 6.2 percent (70/1131) to 9.8 percent (111/1131) due to item nonresponses on the 62 IT skills. The basis of testing for response bias is to divide the 111 surveys into two distinct groups (early and late responders). The first group consists of respondents from October 26, 2017, to December 11, 2017 (early responders), and the second group is from January 11, 2018, to January 16, 2018 (late responders). There are no responders after January 16, 2018. A possible reason for the gap (December 12–January 10) between the two groups may be due to the Christmas/New Year's holidays falling during this period. A Chi Square Column Proportions Test using the 63 early responders and 48 late responders for each of the variables indicates no significant differences; thus, the following analysis uses the combined data.

Although a Don't Know response is a valid response, Don't Know responses are not included because only the Likert Scale responses are usable for the statistical analysis. Therefore, the number shown for each IT skill is the number of respondents who answered the IT skill question using the Likert Scale. Any difference between 111 and the number shown in the tables that follow is due to nonresponses and Don't Know responses. Although some researchers impute values for nonresponses, imputing is not viable if nonresponses exceed ten percent ( Lodder, 2013 ); there is no imputation in this study. Nonresponses and Don't know responses are the highest amongst the Data Acquisition, Retention, and Use IT skills 7 (22–37%), with the exception of managing and retaining data (17%), followed by System Development and/or Acquisition (13–18%), Internet (13–16%), Governance (16%), System Development and/or Use (12%), Tools (12%), and Infrastructure (1–11%).

Furthermore, it does not appear that significantly fewer respondents answered questions near the end of the questionnaire. For example, 92 answered question 16 (managing and retaining data—1 st set of questions related to IT skills), 98 answered question 19 (spreadsheets—4th set of questions related to IT skills), and 94 answered question 21 (preventing and responding to computer fraud—last set of questions related to IT skills). Thus, it seems reasonable to suggest respondents simply went through the questionnaire and answered those IT skills they had knowledge of.

Data Acquisition, Retention, and Use is the first set of IT questions and the number of responses for these specific IT skills are: Data Mining (87), Data Warehouses (75), Database Management Systems (85), managing and retaining data (92), Relational Databases (75), Business Intelligence Tools (70), data loss prevention (75), and file systems (76). Based on the number of responses to these IT skills, it seems reasonable to suggest individuals answered only those IT skills questions that were familiar to them. Many of the IT skills in the Data Acquisition, Retention, and Use section relate to complex IT skills that are more likely to be familiar to MLF respondents. However, the sample includes only 40 MLF respondents, so some of the SF respondents also answered these IT skills questions. Because the purpose of this study is to identify topics for an undergraduate AIS course, it is important to use only those responses indicating the practitioner had an opinion on, or knowledge of, the IT skill. Therefore, the 111 respondents include individuals who did not answer all of the 62 IT skills questions, since disregarding responses that did not answer all the IT skill questions 8 is throwing away data that is useful for the analysis.

Table 1 provides basic demographic, organizational, and employment characteristics. In terms of firm size, 64 percent (71/111) of the respondents are in SF. The Organization for Economic Cooperation and Development's ( OECD, 2019 ) classification is the basis for firm size (SF ≤ 50 employees and MLF > 50 employees). As Table 1 indicates, the respondents are fairly evenly split between female (SF 52.1%, MLF 47.5%) and male (SF 47.9%, MLF 52.5%), and the majority are White/Caucasian (SF 93%, MLF 90%). More than half are 45–64 years old 9 (SF 32.4% + 29.6%, MLF 25% + 50%), most are CPAs (SF 93%, MLF 92.5%) and have a bachelor's (SF 60.6%, MLF 52.5%) or master's (SF 38%, MLF 47.5%) degree in accounting (SF 77.5%, MLF 72.5%).

With respect to their current position (length in firm), the highest percentage have been with their firm ten years or less (SF 23.9% + 23.9%, MLF 30% + 22.5%), in their current position (length in position) ten years or less (SF 26.8% + 21.1%, MLF 45% + 20%), and are in top management (SF 67.6%, MLF 60%). Regarding type of firm, the majority of SF respondents are in Regional CPA firms (40.8%) or other (43.7%), and MLF respondents are in private industry (47.5%) or other (35%). Of the SF respondents indicating other, 80.6 percent (25/31) are in local CPA firms ( Table 1 notes provide more details on the private industry and other categories and are the result of how respondents classified themselves in their answers to   Appendix A —questionnaire items 7 and 8).

RQ1: Does the size of the respondent's firm impact the perception of an IT skill's importance?

A five-point Likert Scale Not Important (1) to Very Important (5) determines the 62 IT skills' importance in the questionnaire. Table 2 , however, focuses on the number of SF and MLF respondents, so the coding is 1 Not Important (1 or 2 in the original scale reflecting Not Important) and 2 Important (3, 4, 5 in the original scale reflecting Important). A column proportion Chi Square Test assesses the association between firm size (SF vs MLF) and the importance (1-Not Important vs. 2- Important) of an IT skill.

14 IT Skills with Significant Differences by Firm Size

Firm Size and Top 27 IT Skills

(Mean ≥ 3 for SF, or MLF, or Both)

Of the 62 IT skills, 14 have significant differences for firm size, and seven (Data Mining, managing and retaining data, Business Intelligence Tools, Data Flow Diagrams, Document Flowcharts, System Flowcharts, and QuickBooks) are new IT skills (not ranked in previous studies). QuickBooks (Panel D—question 19 in the questionnaire) and the Database Management Systems (Panel A—question 16 in the questionnaire) are the most significant of the 14 IT skills. QuickBooks is significantly more important to SF respondents, and the Database Management Systems is significantly more important to MLF respondents. While none of the SF respondents indicate QuickBooks is not important, 23.1% of MLF respondents think it is not important. For the Database Management System, the highest percentage of SF respondents think it is not important, while the opposite is true for MLF respondents. There is also a significant association between firm size and Data Mining, Data Warehouses, Relational Databases, and Business Intelligence Tools. That is, a greater proportion of MLF respondents view Data Mining, Data Warehouses, Relational Databases, and Business Intelligence Tools to be more important than do SF respondents.

In fact, the largest percent of SF respondents think Data Mining and Relational Databases are not important, while the opposite is true for MLF respondents. For Data Warehouses a higher percentage of SF respondents think it is not important than MLF respondents and for Business Intelligence Tools a higher percentage of MLF respondents think it is important compared to SF respondents. Additionally, there is a marginally significant association between firm size and managing and retaining data. Both groups think managing and retaining data is important, with only a slightly larger percentage of MLF respondents viewing it as more important than do SF respondents.

Table 2 Panel B provides results for Infrastructure (Question 17 in the questionnaire). There is a significant association between firm size and the importance of the Intranet and Extranet. These results indicate that a greater proportion of MLF respondents views the Intranet and Extranet as more important than do SF respondents. There is a marginal significance for hardware, with a higher percentage of SF respondents indicating Important than MLF respondents.

Table 2 Panel C presents results for System Development and/or Acquisition (Question 18 in the questionnaire). A significant association exists between firm size and Document Flowcharts, software purchase decisions, and System Flowcharts. That is, a greater proportion of MLF respondents perceive Document Flowcharts and System Flowcharts to be more important than do SF respondents. Conversely, a higher percentage of SF respondents, in comparison to MLF respondents, think the software purchase decision is important. Data Flow Diagrams are marginally significant with a larger percentage of MLF respondents indicating Important as compared to SF respondents. There is no association for firm size and the IT skills in the Internet (Question 20) and Governance (Question 21) sections of the questionnaire.

In summary, SF respondents perceive QuickBooks and software purchase decisions as more important, while MLF respondents think Data Mining, Database Management Systems, Relational Databases, Business Intelligence Tools, Intranet, Extranet, and Document and System Flowcharts are more important. Additionally, the highest percentage of MLF respondents think that Data Mining, Database Management Systems, and Relational Databases are important, while the highest percentage of SF respondents indicate Not Important. These findings tend to support previous research suggesting large firms use more sophisticated information systems than small firms ( Kagan et al., 1990 ; Burke, 2005 ; Thong, 1999 ).

The results in Table 2 suggest it is important for undergraduate AIS course designers to consider where their students' employment opportunities are. If the answer is SF, then spending time on Data Acquisition, Retention, and Use skills (Panel A), other than managing and retaining data, would not seem prudent given undergraduate AIS course constraints. Similarly, the Infrastructure skills (Panel B) Intranet and Extranet, and System Development and/or Acquisition skills (Panel C) involving Data Flow Diagrams, Document Flowcharts, and System Flowcharts are probably less important for students employed in SF. If students are likely to be in MLF, then course coverage recommendations would be the opposite of that for SF employment.

Of the 14 IT skills with significant differences by firm size, five of them (managing and retaining data, Business Intelligence Tools, Intranet, Extranet, and QuickBooks) are in Table 3 . Since firm size affects the importance of some IT skills, Table 3 presents the 27 of the 62 IT skills that have means greater than or equal to three for SF, or MLF, or both. Sixteen of the 27 IT skills are new and not ranked in previous studies, likely due to changes in technology and/or changes in the technology's importance to accountants.

RQ2: What are the important IT skills for an undergraduate AIS course?

The top 15 IT skills ( Table 4 ) for SF respondents indicates three are from the Tools category, five from Internet, four from Infrastructure, two from Data Acquisition, Retention and Use, and one from Governance. The ranking from one to 15, respectively, is: spreadsheets, Microsoft Word, Internet research, Internet, QuickBooks, ensuring privacy, Cloud Computing, preventing and responding to cybercrime, software security, managing and retaining data, network security, preventing and responding to computer fraud, file systems, Password Management Tools, and Virtual Office Technology. Of the top 15 IT skills 11 are new skills (Internet, ensuring privacy, preventing and responding to cybercrime, QuickBooks, Cloud Computing, managing and retaining data, software security, file systems, Password Management Tools, preventing and responding to computer fraud, and Virtual Office Technology), which are not in previous ranking studies, likely due to changes in technology and/or changes in the importance of the technology for accountants.

Firm Size and Top 15 IT Skills

The top 15 IT skills for MLF respondents indicates two are from Tools category, five are from Internet, three are from Infrastructure, four are from Data Acquisition, Retention, and Use, and one from Governance. The ranking from one to 15, respectively, is: spreadsheets, Internet, Internet research, ensuring privacy, Microsoft Word, preventing and responding to cybercrime, managing and retaining data, file systems, Cloud Computing, Business Intelligence Tools, IT controls, data loss prevention, Password Management Tools, software security, and preventing and responding to computer fraud. Of the top 15 IT skills, 12 are new skills and the differences from SF respondents are MLF respondents include IT controls, Business Intelligence Tools, and data loss prevention and do not include QuickBooks and Virtual Office Technology.

Comparing the top 15 IT skills for SF and MLF reveals three differences for each. SF respondents think QuickBooks, network security, and Virtual Office Technology are more important and MLF respondents perceive Business Intelligence Tools, data loss prevention, and IT controls are more important. The rankings for 16 and above ( Table 3 ) also reveal three differences for each group. While SF respondents indicate input devices, output devices, and software implementation are more important, MLF respondents think enabling decision support analysis, Intranet, and Extranet are more important.

In terms of undergraduate AIS course design, Table 4 indicates it is more important for students who are likely to be in SF to have QuickBooks, network security, and Virtual Office Technology skills, and for students going to MLF it is more important to have Business Intelligence Tools, data loss prevention skills, and IT Controls. Furthermore, all students need skills related to spreadsheets, Internet research, Internet, and Microsoft Word based on the rankings in Table 4 . Which of the other skills to include in an undergraduate AIS course will depend on time constraints and where (SF vs. MLF) the majority of the students in the accounting major will be employed. Additional suggestions for undergraduate AIS course design and SF versus MLF considerations are in the following section.

Limited research exists with respect to firm size and the importance of IT skills for accountants. Tables 2 and 3 provide evidence that there is a relationship between firm size and the importance of some IT skills. For example, SF respondents perceive QuickBooks and software purchase decisions to be more important, which seems reasonable given their work environment. SF are more likely to use QuickBooks, and small CPA firms are more likely to have clients who use QuickBooks. The type of software to buy is also an important question for SF, and they may look to their CPA for help because they are not likely to have IT staff.

MLF respondents think enabling decision support and analytics that deal with Big Data (Data Mining, Data Warehouses, Database Management Systems, Relational Databases, and Business Intelligence Tools) and their supporting technologies (Intranet, Extranet, Document Flowcharts, and Systems Flowcharts) are more important. The greater importance attached to the more sophisticated IT tools by MLF respondents seems reasonable because MLF or CPA firms with large clients will have work environments that are more complex and require the maintenance and analysis of significant amounts of data.

spreadsheets ( Dillon & Kruck, 2008 ; Chen et al., 2009 ; Welch et al., 2010 ; Cory & Pruske, 2012 ; Kearns, 2014 ; Lee et al., 2018 )

Word Processing ( Chen et al., 2009 ; Welch et al., 2010 ; Cory & Pruske, 2012 )

Internet research ( Welch et al., 2010 ; Cory & Pruske, 2012 ).

This research's results also support previous findings that firm size is not a factor for Cloud Computing ( Gupta et al., 2013 ; Seethamraju, 2015 ; Loukis et al., 2017 ). Note that Table 2 does not include Cloud Computing, and Cloud Computing ranks seventh and ninth, respectively, for SF and MLF respondents ( Table 4 ).

Additionally, this research adds to the existing literature because 16 of the top 20 IT skills ( Table 3 ) are new (not ranked in previous studies) and 13 made the top 15 IT skills list ( Table 4 ) for SF, or MLF, or both. The 16 new IT skills are: Internet, ensuring privacy, preventing and responding to cybercrime, QuickBooks (SF only), Cloud Computing, managing and retaining data, software security, file systems, Password Management Tools, preventing and responding to computer fraud, Virtual Office Technology, IT Controls, Information Security Technology, data loss prevention, software implementation (SF only), and Business Intelligence Tools (MLF only).

Utilizing Tables 3 and 4 in conjunction with   Appendix B (Rankings of IT Skills) should help AIS faculty decide what to include, what to discard, and what to do outside of an undergraduate AIS course. For example, spreadsheets are the top IT skill time after time, so coverage is essential. In fact, Brown and Pike (2010) indicate, “Excel is the default software for financial analysis and journal entry preparation in the United States and perhaps the world” (p. 26). Schools that lack sufficient AIS faculty might consider utilizing a separate course for spreadsheets taught by MIS faculty, if they have MIS faculty. Some of the 62 IT skills (  Appendix B ) that did not make this study's top IT skills ( Tables 3 and 4 ) may be better in other accounting courses. For example, AIS Auditing/Generalized Audit Software, CASE Tools, and Document and System Flowcharts might be more useful in an undergraduate Auditing course than an AIS course.

Comparing the four studies' rankings (  Appendix B ) reveals that the importance of some IT skills for an undergraduate AIS course may decline over time 10 (for example, input/output devices, Electronic Commerce, hardware, Intranet, Extranet, Project Management, AIS Auditing/Generalized Audit Software, Local Area Network, software purchase decisions, system implementation and testing, system design and maintenance, Database Management Systems, Databases, ERP, Data Warehouses, CASE Tools, Program Design, and Programming Languages). This study's results also support Winstead and Wenger's (2015) findings that the more complex topics, like Electronic Commerce, system implementation and testing, ERP, System Design, XBRL, and Programming Languages are less important to accounting practitioners. Because the majority of these topics are generally found in MIS courses ( Murthy & Ragland, 2009 ), it may be better for undergraduate accounting majors to take MIS courses covering these topics rather than trying to put them in the undergraduate AIS course.

The IT skills shown in Table 3 should be up for consideration when designing an undergraduate AIS course. How many IT skills and which ones to include will depend on whether the accounting program has one or two undergraduate AIS courses. Many schools with only one AIS course should probably focus on the top 10 or 15 IT skills ( Table 4 ) for either SF or MLF, depending on the size of the firms employing their students. Furthermore, 12 of the top 15 IT skills are important, regardless of firm size, and provide a good starting point for schools with only one undergraduate AIS course. The 12 IT skills are: spreadsheets, Internet research, Internet, Microsoft Word, ensuring privacy, preventing and responding to cybercrime, Cloud Computing, managing and retaining data, software security, file systems, Password Management Tools, and preventing and responding to computer fraud. While some might suggest Internet research and Internet are the same, they probably are not. For many the Internet is now “the library.” Generally, one would not consider “using the library” and “library research” to be equivalent skills; the same logic should probably apply to Internet and Internet research.

Schools with two AIS courses might focus on the top 10 or 15 IT skills for SF ( Table 4 ) in the first course and pick up the remaining IT skills for MLF ( Tables 3 and 4 ) in the second course. Regardless of whether the accounting program has one or two AIS courses, the emphasis should be on practical tools and software ( Coyne et al., 2016 ), as the IT skills in Tables 3 and 4 indicate. For example, most AIS textbooks contain chapters on business processes, and using QuickBooks in conjunction with these chapters can provide students with a hands-on experience using a practical tool that SF respondents favor.

Future Implications

The rapid technological innovations make it important for future research to assess emerging IT skills and their impact on the accounting profession. According to Robert Half's 2020 Salary Guide, key IT skills for new accounting hires include cloud-based systems, data analytics and database management, ERP systems, Excel, industry-specific software, and QuickBooks for small and midsize businesses ( Half, 2020 ). This study's questionnaire covers all of Robert Half's key IT skills except for industry-specific software.

While not accounting specific, Some (2019) indicates that the top 2019 technologies are: Artificial Intelligence (AI), Quantum Computing (faster computing), blockchain, Virtual Reality (VR) and Augmented Reality (AR), Intelligent Apps, and Big Data. Additionally, Gartner's 2020 top ten strategic technology categories include hyper-automation (AI and machine learning), multi-experience (AR and VR), democratization (data models), human augmentation (technology enhancing cognitive and physical experiences), transparency and traceability (technology and the trust crisis), empowered edge (Internet of Things), distributed cloud (public cloud services), autonomous things (drones, robots, etc.), practical blockchain, and AI security ( Panetta, 2019 ). This study's questionnaire includes IT skills for only a few of those that Some and Gartner identify: blockchain, Big Data (Business Intelligence Tools and Data Mining), Cloud Computing, and the Internet. New technologies that future research should investigate will depend on how quickly and how much the new technologies impact accounting practice.

Since this study utilizes only two groups (SF vs. MLF), future research might utilize three groups (small, medium, and large) to determine the variation in the importance of IT skills between the three different firm sizes. Additionally, future research can continue to explore the relationship between firm size and the importance that accountants attach to IT skills because limited studies exist, with even fewer investigating a direct correlation to size. While this study collected data on age, it did not collect data on continuing professional education (CPE) or additional technology training. For example, the NCACPA holds two two-day technology conferences every year, so technology CPE is available for CPAs if they choose to do it. Future studies could improve upon this study by collecting data on technology training to determine if age and additional technology training, or the lack there of, have an impact on the importance of IT skills. Another avenue for future research would be to compare the IT skills in Table 3 , especially the 16 new IT skills, to AIS syllabi and textbooks because the studies in this area are dated.

Limitations

The respondents in this study are entirely NCACPA members who use the Open Forum. While there is no reason to believe practitioners in North Carolina view IT skills differently than those in other geographic regions, the restriction to members of the NCACPA using the Open Forum is a limitation of this study. Additionally, the questionnaire's length (it includes questions related to demographic information and 62 IT skills) may have discouraged Open Forum users from participating. Because response rates vary for research utilizing surveys or questionnaires, they are always a study limitation. Unfortunately, low response rates for online surveys with professional accountants is likely to continue to be an issue. For example, a recent AICPA Trends Report (2019, p. 38) utilizing online surveys with accountants from universities and colleges and accounting firms indicates response rates, respectively, of 12 and 2.3 percent.

This research attempts to overcome previous studies' limitations by surveying practicing accountants who are not working primarily in large public accounting firms. The results provide the views of over 100 professional accountants: 93 percent are CPAs, 64 percent in SF, and many have been in the profession for a significant period of time (highest percentage are in the age range 45–64). Input from SF practitioners is important because the majority of undergraduate accounting students will not go into, or will not stay in, large public accounting practice; therefore, addressing their needs is important when identifying topics for an undergraduate AIS course ( Schea, 2008 ; Siegel et al., 2010 ). Additionally, this study provides an important update on IT skills, their importance to accountants, and an SF versus MLF comparison.

The top IT skills ( Table 3 ) this research identifies will help accounting educators decide what topics their undergraduate AIS course(s) should include. Of additional significance are the 35 IT skills (can be found in   Appendix B —Rankings of IT Skills) that did not make the top 27 IT skills in Table 3 . This research's ranking of the 62 IT skills allows AIS educators to evaluate the topics they currently cover and what they might want to change, depending on where the majority of their students' employment opportunities are (SF vs. MLF). Furthermore, the top 27 IT skills ( Table 3 ) this study reveals provides an important update because it includes 16 skills that are not in previous ranking studies, due to lack of inclusion and/or changes in technology.

The authors would like to thank the Editor-in-Chief, the associate editor, and three anonymous reviewers whose comments and suggestions greatly improved the quality of our original manuscript.

Editor's Note: This article contains hyperlinks to World Wide Web pages. Readers who have the ability to access the Web directly from their devices and applications may be able to gain direct access to these linked pages. Readers are warned of the following caveats regarding these links.

The links existed as of the date of publication but are not guaranteed to be working thereafter.

The contents of web pages may change over time. Where version information is provided in the AISEJ published article, different versions may not contain the information, or the conclusions referenced.

The author(s) of the web pages, not AIS Educator Journal nor AIS Educator Association , is (are) responsible for the accuracy of their content.

The author(s) of this article, not AIS Educator Journal nor AIS Educator Association , is (are) responsible for the accuracy of the URL and version information.

Section I: Demographic Data

What is your gender?

Female ____

What is your age?

Under 25 _____

25 – 34 _____

35 – 44 _____

45 – 54 _____

55 – 64 _____

65 – 74 _____

Over 75 _____

Other (please specify) _____

No Certification _____

My highest degree completed is a(n):

Associate's _____

Bachelor's _____

Master's _____

Doctoral _____

My highest degree completed was in:

Accounting _____

My ethnic group is:

American Indian or Alaskan Native _____

Asian or Pacific Islander _____

Black or African-American _____

Hispanic or Latino _____

White / Caucasian _____

Prefer not to answer _____

Section II - Employment – Firm / Sector Information

I am currently employed by:

Big-Four Firm _____

Other National CPA Firm _____

Regional CPA Firm _____

Private Industry _____

Other _____

Manufacturing _____

Wholesale _____

Retail _____

Consulting Services _____

Governmental Agency _____

Educational Institution _____

Section III – Length of Employment and Position

Number of employees in my current firm/organization is:

51– 100 _____

101–500 _____

501–1000 _____

1001 – 2000 _____

2001–3000 _____

> 3000 _____

I have been in my current firm/organization for:

< 5 years _____

5 – 10 years _____

11 – 15 years _____

16 – 20 years _____

More than 20 years _____

I have been in my current position for:

My current position is that of a:

Upper-level manager _____

Middle-level manager _____

Lower-level manager _____

Non-manager _____

Section IV – Supervisory Information

Supervision is part of my job:

Section V – Direct Supervision

If you answered “Yes” to Question 13, how many employees do you supervise directly:

< 10 _____

11 – 20 _____

21 – 30 _____

31 – 50 _____

51 – 70 _____

> 70 _____

Section VI – Hiring Input

Section VII – Data Acquisition, Retention, & Use

Please indicate the importance of the following Information Technology (IT) Skills, knowledge, etc. listed below to your organization in terms of hiring a recent accounting graduate.

Section VIII – Infrastructure

Section IX – System Development and/or Acquisition

Section X – Tools

Section XI – Internet

Section XII – Governance

Section XIII – Cooperation between IT Personnel and Accountants

Section XIV – COBIT

Section XV – Anything Else?

Please indicate any additional information that you would like to share:

The studies presented in this literature review are the ones that were available when the IT skills for the questionnaire were determined.

The three ranking studies presented in   Appendix B represent the most current studies that ranked at least 24 distinct IT skills at the time this study's questionnaire was developed.

Skills are from previous ranking studies and textbook topics, and some are new due to changes in technology or not being included in previous ranking studies.

Members have the opportunity to participate voluntarily in posts on the Open Forum.

They provided the most responses to the 62 IT skills questions.

Although the questionnaire included a Don't Know option (a valid response), those responses are not included in the statistical analysis or the effective response rate.

This is likely due to lack of familiarity with these IT skills.

Only 14 of the respondents answered all 62 IT skills questions; nonresponses are likely due to lack of familiarity with the skill.

While some might suggest age is a factor with respect to IT skills, that may not be the case if the individual has kept up with changes in technology through additional training. Since the questionnaire did not collect data regarding additional technology training, this issue cannot be addressed.

Additionally, firm size affects some IT skills' importance, as this study indicates. Since previous studies did not address firm size, the rank order for this study's results in   Appendix B are without division for firm size to provide comparability with the previous studies.

Recipient(s) will receive an email with a link to 'Topics for Your Undergraduate Accounting Information Systems (AIS) Course-An Exploratory Study of Information Technology (IT) Skills and Firm Size' and will not need an account to access the content.

Subject: Topics for Your Undergraduate Accounting Information Systems (AIS) Course-An Exploratory Study of Information Technology (IT) Skills and Firm Size

(Optional message may have a maximum of 1000 characters.)

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11.The Effectiveness of the Accounting Information System

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The state of AI in early 2024: Gen AI adoption spikes and starts to generate value

If 2023 was the year the world discovered generative AI (gen AI) , 2024 is the year organizations truly began using—and deriving business value from—this new technology. In the latest McKinsey Global Survey  on AI, 65 percent of respondents report that their organizations are regularly using gen AI, nearly double the percentage from our previous survey just ten months ago. Respondents’ expectations for gen AI’s impact remain as high as they were last year , with three-quarters predicting that gen AI will lead to significant or disruptive change in their industries in the years ahead.

About the authors

This article is a collaborative effort by Alex Singla , Alexander Sukharevsky , Lareina Yee , and Michael Chui , with Bryce Hall , representing views from QuantumBlack, AI by McKinsey, and McKinsey Digital.

Organizations are already seeing material benefits from gen AI use, reporting both cost decreases and revenue jumps in the business units deploying the technology. The survey also provides insights into the kinds of risks presented by gen AI—most notably, inaccuracy—as well as the emerging practices of top performers to mitigate those challenges and capture value.

AI adoption surges

Interest in generative AI has also brightened the spotlight on a broader set of AI capabilities. For the past six years, AI adoption by respondents’ organizations has hovered at about 50 percent. This year, the survey finds that adoption has jumped to 72 percent (Exhibit 1). And the interest is truly global in scope. Our 2023 survey found that AI adoption did not reach 66 percent in any region; however, this year more than two-thirds of respondents in nearly every region say their organizations are using AI. 1 Organizations based in Central and South America are the exception, with 58 percent of respondents working for organizations based in Central and South America reporting AI adoption. Looking by industry, the biggest increase in adoption can be found in professional services. 2 Includes respondents working for organizations focused on human resources, legal services, management consulting, market research, R&D, tax preparation, and training.

Also, responses suggest that companies are now using AI in more parts of the business. Half of respondents say their organizations have adopted AI in two or more business functions, up from less than a third of respondents in 2023 (Exhibit 2).

Gen AI adoption is most common in the functions where it can create the most value

Most respondents now report that their organizations—and they as individuals—are using gen AI. Sixty-five percent of respondents say their organizations are regularly using gen AI in at least one business function, up from one-third last year. The average organization using gen AI is doing so in two functions, most often in marketing and sales and in product and service development—two functions in which previous research  determined that gen AI adoption could generate the most value 3 “ The economic potential of generative AI: The next productivity frontier ,” McKinsey, June 14, 2023. —as well as in IT (Exhibit 3). The biggest increase from 2023 is found in marketing and sales, where reported adoption has more than doubled. Yet across functions, only two use cases, both within marketing and sales, are reported by 15 percent or more of respondents.

Gen AI also is weaving its way into respondents’ personal lives. Compared with 2023, respondents are much more likely to be using gen AI at work and even more likely to be using gen AI both at work and in their personal lives (Exhibit 4). The survey finds upticks in gen AI use across all regions, with the largest increases in Asia–Pacific and Greater China. Respondents at the highest seniority levels, meanwhile, show larger jumps in the use of gen Al tools for work and outside of work compared with their midlevel-management peers. Looking at specific industries, respondents working in energy and materials and in professional services report the largest increase in gen AI use.

Investments in gen AI and analytical AI are beginning to create value

The latest survey also shows how different industries are budgeting for gen AI. Responses suggest that, in many industries, organizations are about equally as likely to be investing more than 5 percent of their digital budgets in gen AI as they are in nongenerative, analytical-AI solutions (Exhibit 5). Yet in most industries, larger shares of respondents report that their organizations spend more than 20 percent on analytical AI than on gen AI. Looking ahead, most respondents—67 percent—expect their organizations to invest more in AI over the next three years.

Where are those investments paying off? For the first time, our latest survey explored the value created by gen AI use by business function. The function in which the largest share of respondents report seeing cost decreases is human resources. Respondents most commonly report meaningful revenue increases (of more than 5 percent) in supply chain and inventory management (Exhibit 6). For analytical AI, respondents most often report seeing cost benefits in service operations—in line with what we found last year —as well as meaningful revenue increases from AI use in marketing and sales.

Inaccuracy: The most recognized and experienced risk of gen AI use

As businesses begin to see the benefits of gen AI, they’re also recognizing the diverse risks associated with the technology. These can range from data management risks such as data privacy, bias, or intellectual property (IP) infringement to model management risks, which tend to focus on inaccurate output or lack of explainability. A third big risk category is security and incorrect use.

Respondents to the latest survey are more likely than they were last year to say their organizations consider inaccuracy and IP infringement to be relevant to their use of gen AI, and about half continue to view cybersecurity as a risk (Exhibit 7).

Conversely, respondents are less likely than they were last year to say their organizations consider workforce and labor displacement to be relevant risks and are not increasing efforts to mitigate them.

In fact, inaccuracy— which can affect use cases across the gen AI value chain , ranging from customer journeys and summarization to coding and creative content—is the only risk that respondents are significantly more likely than last year to say their organizations are actively working to mitigate.

Some organizations have already experienced negative consequences from the use of gen AI, with 44 percent of respondents saying their organizations have experienced at least one consequence (Exhibit 8). Respondents most often report inaccuracy as a risk that has affected their organizations, followed by cybersecurity and explainability.

Our previous research has found that there are several elements of governance that can help in scaling gen AI use responsibly, yet few respondents report having these risk-related practices in place. 4 “ Implementing generative AI with speed and safety ,” McKinsey Quarterly , March 13, 2024. For example, just 18 percent say their organizations have an enterprise-wide council or board with the authority to make decisions involving responsible AI governance, and only one-third say gen AI risk awareness and risk mitigation controls are required skill sets for technical talent.

Bringing gen AI capabilities to bear

The latest survey also sought to understand how, and how quickly, organizations are deploying these new gen AI tools. We have found three archetypes for implementing gen AI solutions : takers use off-the-shelf, publicly available solutions; shapers customize those tools with proprietary data and systems; and makers develop their own foundation models from scratch. 5 “ Technology’s generational moment with generative AI: A CIO and CTO guide ,” McKinsey, July 11, 2023. Across most industries, the survey results suggest that organizations are finding off-the-shelf offerings applicable to their business needs—though many are pursuing opportunities to customize models or even develop their own (Exhibit 9). About half of reported gen AI uses within respondents’ business functions are utilizing off-the-shelf, publicly available models or tools, with little or no customization. Respondents in energy and materials, technology, and media and telecommunications are more likely to report significant customization or tuning of publicly available models or developing their own proprietary models to address specific business needs.

Respondents most often report that their organizations required one to four months from the start of a project to put gen AI into production, though the time it takes varies by business function (Exhibit 10). It also depends upon the approach for acquiring those capabilities. Not surprisingly, reported uses of highly customized or proprietary models are 1.5 times more likely than off-the-shelf, publicly available models to take five months or more to implement.

Gen AI high performers are excelling despite facing challenges

Gen AI is a new technology, and organizations are still early in the journey of pursuing its opportunities and scaling it across functions. So it’s little surprise that only a small subset of respondents (46 out of 876) report that a meaningful share of their organizations’ EBIT can be attributed to their deployment of gen AI. Still, these gen AI leaders are worth examining closely. These, after all, are the early movers, who already attribute more than 10 percent of their organizations’ EBIT to their use of gen AI. Forty-two percent of these high performers say more than 20 percent of their EBIT is attributable to their use of nongenerative, analytical AI, and they span industries and regions—though most are at organizations with less than $1 billion in annual revenue. The AI-related practices at these organizations can offer guidance to those looking to create value from gen AI adoption at their own organizations.

To start, gen AI high performers are using gen AI in more business functions—an average of three functions, while others average two. They, like other organizations, are most likely to use gen AI in marketing and sales and product or service development, but they’re much more likely than others to use gen AI solutions in risk, legal, and compliance; in strategy and corporate finance; and in supply chain and inventory management. They’re more than three times as likely as others to be using gen AI in activities ranging from processing of accounting documents and risk assessment to R&D testing and pricing and promotions. While, overall, about half of reported gen AI applications within business functions are utilizing publicly available models or tools, gen AI high performers are less likely to use those off-the-shelf options than to either implement significantly customized versions of those tools or to develop their own proprietary foundation models.

What else are these high performers doing differently? For one thing, they are paying more attention to gen-AI-related risks. Perhaps because they are further along on their journeys, they are more likely than others to say their organizations have experienced every negative consequence from gen AI we asked about, from cybersecurity and personal privacy to explainability and IP infringement. Given that, they are more likely than others to report that their organizations consider those risks, as well as regulatory compliance, environmental impacts, and political stability, to be relevant to their gen AI use, and they say they take steps to mitigate more risks than others do.

Gen AI high performers are also much more likely to say their organizations follow a set of risk-related best practices (Exhibit 11). For example, they are nearly twice as likely as others to involve the legal function and embed risk reviews early on in the development of gen AI solutions—that is, to “ shift left .” They’re also much more likely than others to employ a wide range of other best practices, from strategy-related practices to those related to scaling.

In addition to experiencing the risks of gen AI adoption, high performers have encountered other challenges that can serve as warnings to others (Exhibit 12). Seventy percent say they have experienced difficulties with data, including defining processes for data governance, developing the ability to quickly integrate data into AI models, and an insufficient amount of training data, highlighting the essential role that data play in capturing value. High performers are also more likely than others to report experiencing challenges with their operating models, such as implementing agile ways of working and effective sprint performance management.

About the research

The online survey was in the field from February 22 to March 5, 2024, and garnered responses from 1,363 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. Of those respondents, 981 said their organizations had adopted AI in at least one business function, and 878 said their organizations were regularly using gen AI in at least one function. To adjust for differences in response rates, the data are weighted by the contribution of each respondent’s nation to global GDP.

Alex Singla and Alexander Sukharevsky  are global coleaders of QuantumBlack, AI by McKinsey, and senior partners in McKinsey’s Chicago and London offices, respectively; Lareina Yee  is a senior partner in the Bay Area office, where Michael Chui , a McKinsey Global Institute partner, is a partner; and Bryce Hall  is an associate partner in the Washington, DC, office.

They wish to thank Kaitlin Noe, Larry Kanter, Mallika Jhamb, and Shinjini Srivastava for their contributions to this work.

This article was edited by Heather Hanselman, a senior editor in McKinsey’s Atlanta office.

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