Provided by James R. Martin, Ph.D., CMA
Professor Emeritus, University of South Florida
AI and Expert
Systems Main Page | Automation Bibliography
| Data Mining Bibliography
Abernethy, J., F. Candelon, T. Evgeniou, A. Gupta and Y. Lostanlen. 2024. Bring human values to AI. Harvard Business Review (March/April): 60-68.
Ackerman, J. L. 2023. Artificial intelligence may be coming sooner than expected. The CPA Journal (May/June): 72-73.
Adam, A. 1998. Artificial Knowing: Gender and the Thinking Machine. Routledge.
Agrawal, A., J. S. Gans and A. Goldfarb. 2017. What to expect from artificial intelligence. MIT Sloan Management Review (Spring): 23-26.
Agrawal, A., J. Gans and A. Goldfarb. 2018. Prediction Machines: The Simple Economics of Artificial Intelligence. Harvard Business Review Press.
Agrawal, A., J. Gans and A. Goldfarb. 2020. How to win with machine learning. Harvard Business Review (September/October): 126-133. (Artificial intelligence in business, data mining and prediction models).
Agrawal, A., J. Gans and A. Goldfarb. 2022. From prediction to transformation: To realize their potential, AI technologies need new systems that leverage them. Harvard Business Review (November/December): 100-109.
Akerkar, R. and P. Sajja. 2009. Knowledge-Based Systems. Jones & Bartlett Publishers.
Allen, M. K. 1987. The Development of an Artificial Intelligence System for Inventory Management. Council of Logistics Management.
Almufadda, G. and N. A. Almezeini. 2022. Artificial intelligence applications in the auditing profession: A literature review. Journal of Emerging Technologies in Accounting 19(2): 29-42.
Anders, S. B. 2023. ChatGPT resources for CPAs. The CPA Journal (May/June): 76-77.
Babic, B., D. L. Chen, T. Evgeniou and A.Fayard. 2020. A better way to onboard AI: Understand it as a tool to assist rather than replace people. Harvard Business Review (July/August): 56-65.
Babic, B., I. G. Cohen, T. Evgeniou and S. Gerke. 2021. When machine learning goes off the rails: A guide to managing the risks. Harvard Business Review (January/February): 76-84.
Bailey, A. D. Jr., K. Hackenbrack, P. De and J. Dillard. 1987. Artificial intelligence, cognitive science, and computational modeling in auditing research: A research approach. Journal of Information Systems (Spring): 20-40.
Bakarich, K. M. and P. E. O'Brien. 2021. The robots are coming...But aren't here yet: The use of artificial intelligence technologies in the public accounting profession. Journal of Emerging Technologies in Accounting 18(1): 27-43.
Baker, W. M. and P. R. Witmer. 1997. Intelligent agents go to work for management accountants. Management Accounting (April): 32, 34-35.
Bammens, Y. and P. Hunermund. 2023. Using federated machine learning to overcome the AI scale disadvantage. MIT Sloan Management Review (Fall): 54-57. (Federated machine learning allows small-data organizations to train and use sophisticated machine learning models).
Banham, R. 2018. Taking stock of artificial intelligence. Journal of Accountancy (June): 64-66.
Barney, J. B. and M. Reeves. 2024. AI won't give you a new sustainable advantage. Harvard Business Review (September/October): 72-79.
Barro, S. and T. H. Davenport. 2019. People and machines: Partners in innovation. MIT Sloan Management Review (Summer): 22-28.
Baxter, K. and Y. Schlesinger. 2023. Managing the risks of generative AI. Harvard Business Review (Winter Special Issue): 137-139.
Beane, M. 2019. Learning to work with intelligent machines. Harvard Business Review (September/October): 140-148.
Bender, E. A. 1996. Mathematical Methods in Artificial Intelligence (IEEE Computer Society Press). Wiley-IEEE.
Benson, B. and A. Aljabr. 2022. Artificial intelligence and data science: Next wave change. Cost Management (September/October): 18-22.
Bertomeu, J. 2020. Machine learning improves accounting: Discussion, implementation and research opportunities. Review of Accounting Studies 25(3): 1135-1155.
Bertomeu, J., E. Cheynel, E. Floyd and W. Pan. 2021. Using machine learning to detect misstatements. Review of Accounting Studies 26(2): 468-519.
Blackman, R. 2022. Why you need an AI ethics committee: Expert oversight will help you safeguard your data and your brand. Harvard Business Review (July/August): 118-125.
Blyakhman, A. 2021. Technology workbook: The new era of Automl. Strategic Finance (February): 60-61. (Machine learning).
Bojinov, I. 2023. Keep your AI projects on track: Most go off course. To make sure yours succeed, consider these five steps. Harvard Business Review (November/December): 53-59.
Bonson, E., D. Lavorato, R. Lamboglia and D. Mancini. 2021. Artificial intelligence activities and ethical approaches in leading listed companies in the European Union. International Journal of Accounting Information Systems (43): 100535.
Boritz, J. E. and T. C. Stratopoulos. 2023. AI and the accounting profession: Views from industry and academia. Journal of Information Systems (Fall): 1-9.
Bowling, S. and C. Meyer. 2019. How we successfully implemented AI in audit. Journal of Accountancy (June): 26-28.
Brodeur, G. L., G. Hall and E. Tynch. 2023. ChatGPT for legal and tax professionals. The CPA Journal (July/August): 68-71.
Brown, C., E. J. Coakley and M. E. Phillips. 1995. Neural networks enter the world of management accounting. Management Accounting (May): 51-57. (Related to artificial intelligence).
Bughin, J. 2018. Wait-and-see could be a costly AI strategy. MIT Sloan Management Review (Summer): 1-4.
Bughin, J. 2018. Why AI isn't the death of jobs. MIT Sloan Management Review (Summer): 42-46.
Burden, D. J. H. 2009. Deploying embodied AI into virtual worlds. Knowledge-Based Systems (October): 540-544.
Burney, L., K. Church, M. Akpan and S. Dell. 2023. ChatGPT and AI in accounting education and research. Strategic Finance (August): 61-68.
Candelon, F., R. C. di Carlo and S. D. Mills. 2021. AI-at-scale hinges on gaining a 'social license'. MIT Sloan Management Review (Fall): 1-4.
Candelon, F., R. C. di Carlo, M. De Bondt and T. Evgeniou. 2021. AI regulation is coming. Harvard Business Review (September/October): 102-111.
Carmon, Z., R. Schrift, K. Wetenbrock and H. Yang. 2020. Designing AI systems that customers won't hate. MIT Sloan Management Review (Winter): 1-6.
Castelluccio, M. 2017. Technology workbook: AI rising. Strategic Finance (March): 63-65.
Castelluccio, M. 2017. Technology workbook: Artificial intelligence in business. Strategic Finance (April): 55-57.
Castelluccio, M. 2018. Technology workbook: The far limits of AI - Part II. Strategic Finance (January): 55-56.
Castelluccio, M. 2018. Technology workbook: The malicious use of AI. Strategic Finance (April): 55-56. ("The rise of AI could be the worst or the best thing that has happened for humanity." Stephen Hawking).
Castelluccio, M. 2018. Technology workbook: The Malicious use of AI: Part II. Strategic Finance (May): 55-56.
Castelluccio, M. 2020. Technology workbook: A written test for artificial general intelligence. Strategic Finance (November): 53-54.
Causey, A. 1998. The Essence of Artificial Intelligence. Prentice-Hall PTR.
Chabris, C. E. 1987. Artificial Intelligence and Turbo Pascal/Book and Disk. Irwin Professional Publication.
Chamorro-Premuzic, T. 2020. Can surveillance AI make the workplace safe? MIT Sloan Management Review (Fall): 13-15.
Cho, S., M. A. Vasarhelyi, T. Sun and C. Zhang. 2020. Learning from machine learning in accounting and assurance. Journal of Emerging Technologies in Accounting 17(1): 1-10.
Coleman, B., K. Merkley and J. Pacelli. 2022. Human versus machine: A comparison of robo-analyst and traditional research analyst investment recommendations. The Accounting Review (September): 221-244.
Colvin, G. 2015. Humans Are Underrated: What High Achievers Know that Brilliant Machines Never Will. Portfolio/Penguin. (Contents and Summary).
Commerford, B. P., S. A. Dennis, J. R. Joe and J. W. Ulla. 2022. Man versus machine: Complex estimates and auditor reliance on artificial intelligence. Journal of Accounting Research (March): 171-201.
Cook, S., A. Hagiu and J. Wright. 2024. Turn generative AI from an existential threat into a competitive advantage. Harvard Business Review (January/February): 118-125.
Costello, A. M., A. K. Down and M. N. Mehta. 2020. Machine + man: A field experiment on the role of discretion in augmenting AI-based lending models. Journal of Accounting and Economics (November-December): 101360.
Cui, G., M. L. Wong and H. Lui. 2006. Machine learning for direct marketing response models: Bayesian networks with evolutionary programming. Management Science (April): 597-612.
Daugherty, P. R., H. J. Wilson and P. Michelman. 2019. Revising the jobs artificial intelligence will create. MIT Sloan Management Review (Summer): 1-8.
Daugherty, P. R., H. J. Wilson and R. Chowdhury. 2019. Using artificial intelligence to promote diversity. MIT Sloan Management Review (Winter): 1-6.
Davenport, T. H. 2016. Rise of the strategy machines. MIT Sloan Management Review (Fall): 13-16.
Davenport, T. H. 2019. Can we solve AI's 'trust problem'? MIT Sloan Management Review (Winter): 1-5.
Davenport, T. H. and J. Kirby. 2016. Just how smart are smart machines? MIT Sloan Management Review (Spring): 21-25.
Davenport, T. H. and N. Mittal. 2023. Stop tinkering with AI. Harvard Business Review (January/February): 116-127.
Davenport, T. H. and R. Ronanki. 2018. Artificial intelligence for the real world. Harvard Business Review (January/February): 108-116.
Davenport, T. H. and S. M. Miller. 2022. What machines can't do (yet) in real work settings. MIT Sloan Management Review (Fall): 1-5.
Davenport, T. H. and T. C. Redman. 2023. How AI is improving data management. MIT Sloan Management Review (Winter): 2-6.
Davenport, T. H., G. Guha and D. Grewal. 2021. How to design an AI marketing strategy: What the technology can do today - and what's next. Harvard Business Review (July/August): 42-47.
Davenport, T. H., I. Barkin and K. Tomak. 2023. We're all programmers now: With generative AI, anyone can code. Here's how to help your enterprise embrace this change. Harvard Business Review (September/October): 98-107.
De Cremer, D. 2024. For success with AI, bring everyone on board. Harvard Business Review (May/June): 124-131.
De Freitas, J. and E. Ofek. 2024. How AI can power brand management. Harvard Business Review (September/October): 108-114.
Dickey, G., S. Blanke and L. Seaton. 2019. Machine learning in auditing: Current and future applications. The CPA Journal (June): 16-21.
Dickie, J., B. Groysberg, B. P. Shapiro, and B. Trailer. 2022. Can AI really help you sell? It can, depending on when and how you implement it. Harvard Business Review (November/December): 120-129.
Ding, K., B. Lev, X. Peng, T. Sun and M. A. Vasarhelyi. 2020. Machine learning improves accounting estimates: Evidence from insurance payments. Review of Accounting Studies 25(3): 1098-1134.
Ding, K., X. Peng and Y. Wang. 2019. A machine learning-based peer selection method with financial ratios. Accounting Horizons (September): 75-87.
Drew, J. 2017. Real talk about artificial intelligence and blockchain. Journal of Accountancy (July): 22-26, 28.
Drew, J. 2019. What's 'critical' for CPAs to learn in an AI-powered world. Journal of Accountancy (June): 20-24. (Panel).
Drew, J. 2019. Why patience is important with AI. Journal of Accountancy (July): 38-42.
Drew, J. and K. Tysiac. 2019. What to expect in 2020. Journal of Accountancy (December): 22-27.
Eapen, T. T., D. J. Finkenstadt, J. Folk and L. Venkataswamy. 2023. How generative AI can augment human creativity: Use it to promote divergent thinking. Harvard Business Review (July/August): 56-64. (Cover story).
Edelman, D. C. and M. Abraham. 2022. Customer experience in the age of AI. Harvard Business Review (March/April): 116-125.
El-Wakeel, F. and M. Nandy. 2023. AI from cradle to SDG achievement. Strategic Finance (May): 62-63.
Elliot, V. H., M. Paananen and M. Staron. 2020. Artificial intelligence for decision-makers. Journal of Emerging Technologies in Accounting 17(1): 51-55.
Fedyk, A., J. Hodson, N. Khimich and T. Fedyk. 2022. Is artificial intelligence improving the audit process? Review of Accounting Studies 27(3): 938-985.
Fisher, M., S. Gallino and J. Li. 2023. A step-by-step guide to real-time pricing: An advanced AI model considers much more than what competitors are charging. Harvard Business Review (November/December): 92-101.
Fountaine, T., B. McCarthy and T. Saleh. 2019. Building the AI-powered organization. Harvard Business Review (July/August): 62-73.
Fountaine, T., B. McCarthy and T. Saleh. 2021. Getting AI to scale: Don't try to change everything at once, but do begin with something important. Harvard Business Review (May/June): 116-123.
Friedland, J. 2019. AI can help us live more deliberately. MIT Sloan Management Review (Summer): 45-51.
Gal, G. and P. Steinbart. 1987. Artificial intelligence and research in accounting information systems: Opportunities and issues. Journal of Information Systems (Fall): 54-62.
Gandhi, S. and E. Gervet. 2016. Now that your products can talk, what will they tell you? MIT Sloan Management Review (Spring): 49-50.
Gerbert, P. and M. Spira. 2019. Learning to love the AI bubble. MIT Sloan Management Review (Summer): 1-3.
Govindarajan, V. and V. Venkatraman. 2024. Heavy machinery meets AI. Harvard Business Review (March/April): 98-107.
Grenfell, N. 2021. Artificial intelligence and cost and profitability management. Cost Management (November/December): 43-48.
Grobart, J. 2020. Preparing for whistleblower complaints. AI and analytics can be useful tools when investigating whistleblower claims and rooting out fraud and other illegal behaviors. Strategic Finance (September): 34-39.
Haq, I., M. Abatemarco and J. Hoops. 2020. The development of machine learning and its implications for public accounting. The CPA Journal (June): 6-9.
Harrell, E. 2024. The promise and peril of AI at work. Harvard Business Review (July/August): 158-159.
Harvard Business Review. 2017. AI's early conquests. Harvard Business Review (July/August): 30.
Harvard Business Review. 2017. Augmented reality in the real world. Harvard Business Review (November/December): 59.
Harvard Business Review. 2017. How does augmented reality work? Harvard Business Review (November/December): 58.
Harvard Business Review. 2019. A new leader in AI research? Harvard Business Review (July/August): 27.
Harvard Business Review. 2019. The industries in which artificial intelligence start-ups are being funded. Harvard Business Review (May/June): 30.
Harvard Business Review. 2024. Don't let Gen AI limit your team's creativity. Harvard Business Review (March/April): 17-21.
Häubl, G. and K. B. Murray. 2006. Double agents. MIT Sloan Management Review (Spring): 8-12.
Heimans, J. and H. Timms. 2024. Leading in a world where AI wields power of its own. Harvard Business Review (January/February): 70-79.
Hisey, L. 2020. Leveraging lean six sigma with artificial intelligence. Cost Management (July/August): 20-23.
Hodge, F. D., K. I. Mendoza and R. K. Sinha. 2021. The effect of humanizing robo-advisors on investor judgments. Contemporary Accounting Research 38(1): 770-792.
Hoffman, R. 2016. Using artificial intelligence to set information free. MIT Sloan Management Review (Fall): 1-15.
Hogarth, R. M. and E. Soyer. 2015. Using simulated experience to make sense of big data. MIT Sloan Management Review (Winter): 49-54.
Homes, A. F. and A. Douglass. 2022. Artificial intelligence: Reshaping the accounting profession and the disruption to accounting education. Journal of Emerging Technologies in Accounting 19(1): 53-68.
Hopper, G. 2021. Deep Finance: Corporate Finance in the Information Age. Leaders Press.
Howard, A. 2019. The regulation of AI - Should organizations be worried? MIT Sloan Management Review (Summer): 1-3.
Hurson, J. 2018. Creating a brighter future with artificial intelligence. Strategic Finance (April): 12-13.
Issa, H., T. Sun and M. A. Vasarhelyi. 2016. Research ideas for artificial intelligence in auditing: The formalization of audit an workforce supplementation. Journal of Emerging Technologies in Accounting 13(2): 1-20.
Johnson, B. G., F. Phillips and L. G. Chase. 2009. An intelligent tutoring system for the accounting cycle: Enhancing textbook homework with artificial intelligence. Journal of Accounting Education 27(1): 30-39.
Jones, D. R., D. Brown and P. Wheeler. 2001. The effect of justification type on agreement with a decision aid and judgment performance. Advances in Accounting Behavioral Research (4): 187-206.
Jones, M. T. 2008. Artificial Intelligence: A Systems Approach. Jones & Bartlett Publishers.
Joshi, A., I. Buche and M. P. Sadler. 2023. Moving beyond islands of experimentation to AI everywhere. MIT Sloan Management Review (Summer): 74-79.
Juma'h, A. H. and L. Arumugam. 2023. Reaping AI benefits on a budget. Strategic Finance (October): 29-31.
Kapanowski, G. 2023. The rise of AI and ChatGPT is here: Now what? Cost Management (July/August): 43-47.
Kaufmann, M., P. Manolios and J. S. Moore. 2000. Computer-Aided Reasoning: An Approach (Advances in Formal Methods). Kluwer Academic Publishers.
Kellogg, K. C., M. Sendak and S. Balu. 2022. AI on the front lines: AI progress can stall when end users resist adoption. Developers must think beyond a projects business benefits and ensure that end users' workflow concerns are addressed. MIT Sloan Management Review (Summer): 44-50.
Kenney, A. 2023. The promise and peril of ChatGPT. Journal of Accountancy (May): 1-7.
Khalifeh, T. 2023. Accounting in the age of generative AI: Accounting and finance professionals can benefit from ChatGPT, but they must take steps to mitigate risks. Strategic Finance (October): 55-64.
Kiron, D. 2022. AI can change how you measure - and how you manage. MIT Sloan Management Review (Spring): 24-28.
Kiron, D. and G. Unruh. 2019. Even if AI can cure loneliness - Should it? MIT Sloan Management Review (Winter): 1-4.
Kiron, D. and M. Schrage. 2019. Strategy for and with AI. MIT Sloan Management Review (Summer): 30-35.
Klotz, F. 2016. Are you ready for robot colleagues? MIT Sloan Management Review (Fall): 60-65.
Klotz, F. 2018. Building a robotic colleague with personality. MIT Sloan Management Review (Summer): 1-5.
Klotz, F. 2018. How AI can amplify human competencies. MIT Sloan Management Review (Fall): 14-15.
Klotz, F. 2018. The quest to create utterly normal virtual reality experiences. MIT Sloan Management Review (Spring): 1-5.
Klotz, F. 2019. The perils of applying AI prediction to complex decisions. MIT Sloan Management Review (Summer): 1-4.
Koch, R. 2017. Technology workbook: Will artificial intelligence eliminate my job? Strategic Finance (September): 62-63.
Kokina, J. and T. H. Davenport. 2017. The emergence of artificial intelligence: How automation is changing auditing. Journal of Emerging Technologies in Accounting 14(1): 115-122.
Krolak, P. D. 1971. Portfolio evaluation & re-evaluation: An experiment in subjective probability, man-machine learning and decision making. Decision Sciences 2(2): 225-238.
Lanz, J. 2023. Artificial intelligence. The CPA Journal (September/October): 70-72.
Latham, S. and B. Humberd. 2018. Four ways jobs will respond to automation. MIT Sloan Management Review (Fall): 11-14.
Lebovitz, S., H. Lifshitz-Assaf and N. Levina. 2023. The No. 1 question to ask when evaluating AI tools. MIT Sloan Management Review (Spring): 27-30.
Leonardi, P. 2023. Helping employees succeed with generative AI: How to manage performance when new technology brings constant and unpredictable change. Harvard Business Review (November/December): 49-53.
Li, F. 2010. The information content of forward-looking statements in corporate filings - A naive Bayesian machine learning approach. Journal of Accounting Research (December): 1049-1102.
Lin, P. 2018. Adapting to the new business environment: The rise of software robots in the workplace. The CPA Journal (December): 60-63.
Lin, P. and T. Hazelbaker. 2019. Meeting the challenge of artificial intelligence: What CPAs need to know. The CPA Journal (June): 48-52.
Lucini, F. 2021. The real deal about synthetic data: It's often difficult to access the real-world data needed to train AI models or gain insights, but new techniques for generating look-alike data sets can help. MIT Sloan Management Review (Fall): 1-4.
Maguire, K. 2017. Technology: Machine learning, human fraud. Strategic Finance (March): 70-71.
Malone, T. W. 2018. How human-computer 'superminds' are redefining the future of work. MIT Sloan Management Review (Summer): 34-41.
Masuch, M. and P. LaPotin. 1989. Beyond garbage cans: An AI model of organizational choice. Administrative Science Quarterly 34(1): 38-67.
McAfee, A., D. Rock and E. Brynjolfsson. 2023. How to capitalize on generative AI: A guide to realizing its benefits while limiting its risks. Harvard Business Review (November/December): 42-48.
McCarthy, W. E. and E. Outslay. 1989. An analysis of the applicability of artificial intelligence techniques to problem-solving in taxation domains. Accounting Horizons (June): 14-27.
Meinhart, W. A. 1966. Artificial intelligence, computer simulation of human cognitive and social processes, and management thought. The Academy of Management Journal 9(4): 294-307.
Meissner, P. and C. Keding. 2021. The human factor in AI-based decision-making. MIT Sloan Management Review (Fall): 1-5.
Mintz, S. M. 2021. Teaching ethics and AI for finance. Strategic Finance (August): 40-45.
MIT Sloan Management Review. 2018. Improving strategic execution with machine learning. MIT Sloan Management Review (Fall): 2-7.
Morse, G. 2020. Harnessing artificial intelligence. Harvard Business Review (May/June): 158-159.
Moser, C., F. D. Hond and D. Lindebaum. 2022. What humans lose when we let AI decide. MIT Sloan Management Review (Spring): 12-14.
Nathan, B. 2021. Technology workbook: AI: A blessing and a curse. Strategic Finance (September): 62-63.
Neeley, T. and P. Leonardi. 2022. Developing a digital mindset: How to lead your organization into the age of data, algorithms, and AI. Harvard Business Review (May/June): 50-55.
Negnevitsky, M. 2001. Artificial Intelligence: A Guide to Intelligent Systems. Addison Wesley.
Oansiti, M. and K. R. Lakhani. 2020. Competing in the age of AI: How machine intelligence changes the rules of business. Harvard Business Review (January/February): 60-67.
Odkhishig, G., A. M. Rose, J. M. Rose and K. Rotaru. 2022. Increasing reliance on financial advice with avatars: The effects of competence and complexity on algorithm aversion. Journal of Information Systems (Spring): 7-17.
Palumbo, S. and D. Edelman. 2023. What smart companies know about integrating AI. Harvard Business Review (July/August): 116-125.
Parks, L. 2021. COSO issues guidance on AI. Strategic Finance (November): 12.
Patelli, L. 2019. AI isn't neutral. Strategic Finance (December): 11-12.
Petkov, R. 2020. Artificial intelligence (AI) and the accounting function - A revisit and a new perspective for developing framework. Journal of Emerging Technologies in Accounting 17(1): 99-105.
Plattfaut, R. and V. Borghoff. 2022. Robotic process automation: A literature-based research agenda. Journal of Information Systems (Summer): 173-191.
Pope, K. R., L. Black and M. Stern. 2023. Generative AI in accounting applications: A live example provides a guide for strategically using ChatGPT to create an aging of accounts receivable report. Strategic Finance (November): 29-36.
Qasim, A. and F. F. Kharbat. 2020. Blockchain technology, business data analytics, and artificial intelligence: Use in the accounting profession and ideas for inclusion into the accounting curriculum. Journal of Emerging Technologies in Accounting 17(1): 107-117.
Qasim, A., G. A. El Refae and S. Eletter. 2022. Embracing emerging technologies and artificial intelligence into the undergraduate accounting curriculum: Reflections from the UAE. Journal of Emerging Technologies in Accounting 19(2): 155-169.
Radigan, J. 2020. How to incorporate AI into your audit. Journal of Accountancy (September): 71, 73, 76-77.
Rahimikia, E., S. Mohammadi, T. Rahmani and M. Ghazanfari. 2017. Detecting corporate tax evasion using a hybrid intelligent system: A case study of Iran. International Journal of Accounting Information Systems (25): 1-17.
Ramakrishnan, R. 2022. How to build good AI solutions when data is scarce. MIT Sloan Management Review (Fall): 1-9.
Ramakrishnan, R. 2023. How to build good AI solutions when data is scarce. MIT Sloan Management Review (Winter): 48-53.
Ransbotham, S., D. Kiron, P. Gerbert and M. Reeves. 2017. Reshaping business with artificial intelligence. MIT Sloan Management Review (Fall): 1-17.
Rechtman, Y. 2023. Can artificial intelligence become an accounting expert? The CPA Journal (July/August): 6-9.
Redman, T. C. 2021. What's holding your data program back? To deliver on the promise of data-backed technology, such as AI, companies must address underlying restraining forces. MIT Sloan Management Review (Fall): 1-10.
Robinson, C. C., J. Cherfoli and K. Tysiac. 2019. Data and the deep bleu sea: Georgia Aquarium uses AI and predictive analytics to improve the guest experience. Journal of Accountancy (June): 30-32.
Ross, J. 2018. The fundamental flaw in AI implementation. MIT Sloan Management Review (Winter): 10-11.
Russell, S. and P. Norvig. 2009. Artificial Intelligence: A Modern Approach, 3rd Edition. Prentice Hall.
Saenz, M. J., E. Revilla and C. Simon. 2020. Designing AI systems with human-machine teams. MIT Sloan Management Review (Spring): 1-5.
Schalkoff, R. J. 2009. Intelligent Systems: Principles, Paradigms and Pragmatics. Jones & Bartlett Publishers.
Seymour, M., D. Lovallo, K. Riemer, A. R. Dennis and L. Yuan. 2023. AI with a human face: The case for - and against - digital employees. Harvard Business Review (March/April): 49-54.
Siegel, J. G. and J. K. Shim. 2003. The Artificial Intelligence Handbook: Business Applications. South-Western Educational Publishing.
Silverman, K. 2020. Why your board needs a plan for AI oversight. MIT Sloan Management Review (Fall): 1-6.
Skiena, S. S. 2017. The Data Science Design Manual. Springer. Chapter 1: What is Data Science? Chapter 2: Mathematical Preliminaries. Chapter 3: Data Munging. Chapter 4: Scores and Ranking. Chapter 5: Statistical Analysis. Chapter 6: Visualizing Data. Chapter 7: Mathematical Models. Chapter 8: Linear Algebra. Chapter 9: Linear and Logistic Regression. Chapter 10: Distance and Network Methods. Chapter 11: Machine Learning. Chapter 12: Big Data: Achieving Scale. Chapter 13: Coda.
Smith, D. 2019. Technology workbook: AI in data governance. Strategic Finance (September): 60-61.
Smith, D. and G. Hoggard. 2022. Counting eggs with AI: The Rembrandt egg operation shows how computerized vision and AI adoption can create significant value for any organization. Strategic Finance (February): 26-33.
Stark, D. 2022. Book review essay: Questioning humans versus machines: Artificial intelligence in class conflict. Administrative Science Quarterly 67(3): NP42-NP46. Based on Frank, P. 2020. New Laws of Robotics: Defending Human Expertise in the Age of AI. Harvard University Press.
Stefano, D. 2023. People may be more trusting of AI when they can't see how it works. Harvard Business Review (September/October): 30-31.
Street, D. and J. Wilck. 2023. "Let's have a chat:" Applying ChatGPT and other large language models to the practice of forensic accounting. Journal of Forensic & Investigative Accounting 15(2): 158-191.
Street, D., J. Wilck and Z. Chism. 2023. Six principles for the effective use of artificial intelligence large language models. The CPA Journal (November/December): 50-56.
Sun, T. and M. A. Vasarhelyi. 2017. Deep learning and the future of auditing: How an evolving technology could transform analysis and improve judgment. The CPA Journal (June): 24-29. (Deep learning, a cutting-edge use of artificial intelligence).
Sundarraj, R. P. 2006. Modeling an intelligent authentication system to protect financial information. International Journal of Accounting Information Systems 7(2): 110-112.
Sutton, S. G., M. Holt and V. Arnold. 2016. "The reports of my death are greatly exaggerated" - Artificial intelligence research in accounting. International Journal of Accounting Information Systems (22): 60-73.
Tamayo, J., L. Doumi, K. Sagar and R. Saaun. 2023. Reskilling in the age of AI: Five new paradigms for leaders - and employees. Harvard Business Review (September/October): 56-65. Change management. (Cover story).
Tarafdar, M., C. M. Beath and J. W. Ross. 2019. Using AI to enhance business operations. MIT Sloan Management Review (Summer): 37-44.
Truemper, K. 2004. Design of Logic-based Intelligent Systems. Wiley Interscience.
Turban, E., R. Sharda and D. Delen. 2010. Decision Support and Business Intelligence Systems, 9th Edition. Prentice Hall.
Van Der Merwe, A. and L. R. White. 2021. AI for decision analysis. Strategic Finance (February): 22-29.
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