- IBM’s “Watson for Oncology” – a cognitive computing system that was to eradicate cancer?
- Amazon’s A.I. enabled HR software – a software that was to support recruitment by vetting curriculums and making recommendations?
- Facebook’s “Bob” and “Alice” – chatbots that were to learn how to negotiate?
Do you know what these three projects have in common? They are three examples of Artificial Intelligence projects that failed.
Research in this hot topic uncovers several reasons why A.I. initiatives fail. Work in this domain is risky and one can wonder if it is worth it.
Let us dig a bit deeper into this.
Investigation demonstrates that it is hard to get financial return from A.I. – 40% of companies that are making significant investments do not report business gains – according to a 2019 global executive study with 97 countries, 29 different industries and over 2500 respondents conducted by MIT Sloan Management Review and Boston Consulting Group1.
Nevertheless, the same report states that 90% of the inquired agree that A.I. represents a business opportunity for their company1.
It is clear there is a lot of work ahead to guarantee companies can be successful securing their return on investment.
Why is A.I. still today an untapped opportunity, risky and difficult?
Organizational leaders will find reasons connected to technology, data strategy, infrastructures and tools, as well as, pressure from competitors, unrealistic expectations, insufficient knowledge and understanding of A.I. and its applications, business processes such as recruitment and training, the competency gap, replacement threat, security threat, ethical concerns like privacy, short-term versus long-term business focus, to mention a few.1,2,4,5
Nevertheless, one key reason A.I. initiatives fail is because the cultural impact of introducing A.I. is forgotten or underestimated6. To drive the progress in Artificial Intelligence it takes a cultural shift which needs to be successfully driven by the Top Management.1,2,6,7
To find out more about how your Top Executives are instrumental to A.I. and Data success in your company, contact us.
References:
- S. Ransbotham, S. Khodabandeh, R. Fehling, B. LaFountain, D. Kiron, “Winning With AI,” MIT Sloan Management Review and Boston Consulting Group, October 2019.
- D. Kiron, “What Managers Need To Know About Artificial Intelligence,” MIT Sloan Management Review and Boston Consulting Group, January 2017.
- M. K. Lee, “Machine Learning and Your Business: The Journey From Concept to Reality,” MIT Sloan Management Review, August 2020.
- S. Overby, “8 reasons AI projects fail,” The Enterprises Project, March 2020.
- N. Blier, “Stories of AI Failure and How to Avoid Similar AI Fails,” Lexalytics, January 2020.
- V. Baker, M. Revang, S. Sicular, S. Alaybeyi, A. Chandrasekaran, A. Linden, & A. Mullen, “Predicts 2020: Artificial Intelligence – the Road to Production,” Gartner Information Technology Research, December 2019.
- G. Kane, “Is the Right Group Leading Your Digital Initiatives?,” MIT Sloan Management Review, August 2018.
