With a vision, companies should invest in AI readiness across their workforce and technical estate. This means ensuring employees at all levels have at least a baseline understanding of AI capabilities and limitations, and technology systems are interoperable and robust. To support success, companies should develop an AI talent pipeline— identify a cadre of specialists(“ AI builders” and“ AI masters”) who can build, implement, and maintain AI tools internally.
In conclusion, designing for an AI future involves a holistic approach: technology and talent. Companies that align these will not only deploy AI faster, they’ ll do so with a workforce that’ s skilled, adaptive, and trusted to keep the human advantage in play.
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References
1. Dwivedi, Y. K. et al.“ So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. Int J Inf Manage 71,( 2023).
2. McKinsey Global Institute.“ Generative AI and the Future of Work in America.”( 2023).
3. WEF. Future of Jobs Report 2025.” World Economic Forum( 2025).
4. Rogers, E. M.“ Diffusion of Innovations.”( The Free Press, New York, 1995).
5. Ryan, R. M. & Deci, E. L.“ Self-determination theory and the facilitation of intrinsic motivation.” American Psychologist 55, 68 – 78( 2000).
6. Bandura, A.“ Social cognitive theory of selfregulation.” Organizational Behavior and Human Decision Processes 50, 248 – 287( 1991).
7. Ajzen, I.“ From intentions to actions: A theory of planned behavior. in Action control: From cognition to behavior”( eds. Kuhl, J. & Beckman, J.) 11 – 39( Springer., Heidelberg, Germany, 1985). doi: 10.1007 / 978-3-642- 69746-3 _ 2.
8. Venkatesh, V., Morris, M. G., Davis, G. B. & Davis, F. D.“ User Acceptance of Information Technology: Towards a Unified View.” MIS Quarterly 27, 425 – 478( 2003).
9. Bhattacherjee, A.“ Understanding Information Systems Continuance: An Expectation-Confirmation Model.” MIS Quarterly 25, 351( 2001).
10. Venkatesh, V., Thong, J. Y. L. & Xu, X.“ Consumer Acceptance and Use of Information technology: Extending the Unified Theory of Acceptance and Use of Technology.” MIS Quarterly 36, 157 – 178( 2012).
11. Dwivedi, Y., Rana, N., Chen, H. & Williams, M. A“ Meta-analysis of the Unified Theory of Acceptance and Use of Technology( UTAUT). in IFIP International Working Conference on Governance and Sustaibability in Information Systems: Managing the Transfer and Diffusion of IT” 155 – 170( Springer Berlin Heidelberg, 2011). doi: 10.1007 / 978-3-642-24148-2 _ 10.
12. Williams, M. D., Rana, N. P. & Dwivedi, Y. K.“ The Unified Theory of Acceptance and Use of Technology( UTAUT): A Literature Review.” Journal of Enterprise Information Management vol. 28( 2015).
13. Swargiary, K.“ The Impact of ChatGPT on Student Learning Outcomes: A Comparative Study of Cognitive Engagement, Procrastination, and Academic Performance.”( 2024) doi: https:// dx. doi. org / 10.2139 / ssrn. 4914743.
14. Sukri, A., Rizka, M. A., Purwanti, E., Ramdiah, S., & Lukitasari, M.“ Students’ Perceptions of ChatGPT in Higher Education: A Study of Academic Enhancement, Procrastination, and Ethical Concerns.” European Journal of Educational Research 11, 859 – 872( 2022).
15. Zhao, H., Ye, L., Guo, M. & Deng, Y.“ Reflection or Dependence: How AI Awareness Affects Employees’ In-Role and Extra-Role Performance?” Behavioral Sciences 15,( 2025).
16. Dergaa, I. et al.“ From tools to threats: a reflection on the impact of artificial-intelligence chatbots on cognitive health.” Front Psychol 15,( 2024).
17. Fuchs, E. & Flügge, G.“ Adult neuroplasticity: More than 40 years of research.” Neural Plast 2014,( 2014).
18. Sadegh-Zadeh, S.-A.“ Neural reshaping: the plasticity of human brain and artificial intelligence in the learning process.” Am J Neurodegener Dis 13, 34 – 48( 2024).
19. Dahmani, L. & Bohbot, V. D.“ Habitual use of GPS negatively impacts spatial memory during self-guided navigation.” Sci Rep 10,( 2020).
20. Moravec, P. L., Dennis, A. R. & Minas, R. K.“ How Asking Users to Rate Stories Affects Belief in Fake News on Social Media.” Information Systems Research 33,( 2022).
21. Hoffman, R. R., Mueller, S. T., Klein, G. & Litman, J.“ Measures for explainable AI: Explanation goodness, user satisfaction, mental models, curiosity, trust, and human-AI performance.” Front Comput Sci( 2023) doi: 10.3389 / fcomp. 2023.1096257.
54 Bold ideas to power progress