Why Executives Can’t Get Comfortable With AI
AI will require continuous learning: Leaders need to embrace that uncomfortable reality and prioritize developing AI literacy.
Alice Mollon / Ikon Images
Executives need to have an understanding of information technology in order to derive business value from it and to productively interact with IT professionals. Nevertheless, IT experts have long lamented many executives’ limited knowledge of IT’s underlying functionality. In turn, many executives have (often unconsciously) declined to develop such IT literacy, preferring instead to focus their time and attention on domain and business matters.
However, recent evidence indicates that organizations that successfully unlock the strategic potential of artificial intelligence have executives and leaders who embody the opposite instinct: These leaders do have deeper knowledge of AI’s functionality.
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Based on several recent and ongoing AI literacy studies, including analyses of 6,986 executives’ AI skills, 645 companies’ board structures, and experimental studies on human-AI collaboration, we suggest a new guiding theme for executives’ AI literacy: Make technology-related discomfort a habit.1 Here are three ways to develop and practice the habit of maintaining AI literacy.
1. Seek the Discomfort of Continual Learning About AI
In order to navigate the business and technological implications of AI, executives must accept the discomfort of always being on the cutting edge with their own understanding of AI. There are two reasons for this. One, AI is an elusive (and now overused) label that encompasses technology tools with very different kinds of properties. Organizational functions need different AI applications heavily tailored to their own data and workflows. For example, while AI chatbot applications based on large language models can make customer service agents more productive for sales and service support functions, decision tree algorithms enable apps that simplify predictive maintenance work for service operations.2 Knowing what distinguishes these different AI technologies will be crucial for business leaders who own and continually refine processes.
Two, AI applications are changing at a furious rate, and the C-suite expects business leaders to keep up with the related transformation opportunities that open up. For example, less than half a year after the popularization of OpenAI’s ChatGPT, French communications company Bouygues Telecom deployed generative AI tools in its customer service process, challenging company executives to rapidly understand the technology and how it differed from earlier AI.3 To meet expectations, executives don’t need to develop deep coding skills, but they do need a sound understanding of foundational AI principles.
References
1. Our extended analysis was based on two of our studies: M. Pinski, T. Hofmann, and A. Benlian, “AI Literacy for the Top Management: An Upper Echelons Perspective on Corporate AI Orientation and Implementation Ability,” Electronic Markets 34, no. 1 (2024): 1-23; and M. Pinski, T. Hofmann, and A. Benlian, “Executive AI Literacy: A Text-Mining Approach to Understand Existing and Demanded AI Skills of Leaders in Unicorn Firms,” in “Wirtschaftsinformatik 2023 Proceedings” (Paderborn, Germany: International Conference on Wirtschaftsinformatik, September 2023).
2. E. Brynjolfsson, D. Li, and L.R. Raymond, “Generative AI at Work,” working paper 31161, National Bureau of Economic Research, Cambridge, Massachusetts, November 2023; and S. Kaparthi and D. Bumblauskas, “Designing Predictive Maintenance Systems Using Decision Tree-Based Machine Learning Techniques,” International Journal of Quality & Reliability Management 37, no. 4 (2020): 659-686.
3. “AI for Everyone: Bouygues Telecom Achieves Rapid Innovation by Scaling AI on AWS IBM,” IBM, accessed April 2, 2024, www.ibm.com.
4. Pinski, Hofmann, and Benlian, “AI Literacy for the Top Management”; and Pinski, Hofmann, and Benlian, “Executive AI Literacy.”
5. Findings are valid for both established companies (S&P 500) as well as startups (unicorns).
6. M. Weber, M. Engert, N. Schaffer, et al., “Organizational Capabilities for AI Implementation — Coping With Inscrutability and Data Dependency in AI,” Information Systems Frontiers 25, no. 4 (August 2023): 1549-1569.
7. M. Pinski, M. Adam, and A. Benlian, “AI Knowledge: Improving AI Delegation Through Human Enablement,” in “CHI ’23: Proceedings of the CHI Conference on Human Factors in Computing Systems” (Hamburg, Germany: ACM Special Interest Group on Computer-Human Interaction, April 2023).
8. Pinski, Hofmann, and Benlian, “AI Literacy for the Top Management”; and Pinski, Hofmann, and Benlian, “Executive AI Literacy.”