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Early Adoption of Generative AI by Global Business Leaders: Insights from an INSEAD Alumni Survey

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  • Jason P Davis
  • Jian Bai Li
Abstract
How are new technologies like generative AI quickly adopted and used by executive and managerial leaders to create value in organizations? A survey of INSEAD's global alumni base revealed several intriguing insights into perceptions and engagements with generative AI across a broad spectrum of demographics, industries, and geographies. Notably, there's a prevailing optimism about the role of generative AI in enhancing productivity and innovation, as evidenced by the 90% of respondents being excited about its time-saving and efficiency benefits. Analysis revealed different attitudes about adoption and use across demographic variables. Younger respondents are significantly more excited about generative AI and more likely to be using it at work and in personal life than older participants. Those in Europe have a somewhat more distant view of generative AI than those in North America in Asia, in that they see the gains more likely to be captured by organizations than individuals, and are less likely to be using it in professional and personal contexts than those in North America and Asia. This may also be related to the fact that those in Europe are more likely to be working in Financial Services and less likely to be working in Information Technology industries than those in North America and Asia. Despite this, those in Europe are more likely to see AGI happening faster than those in North America, although this may reflect less interaction with generative AI in personal and professional contexts. These findings collectively underscore the complex and multifaceted perceptions of generative AI's role in society, pointing to both its promising potential and the challenges it presents.

Suggested Citation

  • Jason P Davis & Jian Bai Li, 2024. "Early Adoption of Generative AI by Global Business Leaders: Insights from an INSEAD Alumni Survey," Papers 2404.04543, arXiv.org.
  • Handle: RePEc:arx:papers:2404.04543
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