Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
AI Experiments Need Domain Experts. Here’s How to Support Them. |
| Συγγραφείς: |
Karunakaran, Arvind1,2, Kellogg, Katherine C.3, Wiesenfeld, Batia4,5 |
| Πηγή: |
Harvard Business Review Digital Articles. 8/6/2026, p1-10. 10p. |
| Θεματικοί όροι: |
*Generative artificial intelligence, *Organizational structure, *System integration, *Empirical research, *Employees' workload |
| Περίληψη: |
The article examines the critical role of domain experts in successful generative AI (gen AI) innovation within organizations, based on a two-year study of two U.S.-based companies—NE Health and LegalCo—developing organization-wide gen AI solutions. It finds that sustained engagement of domain experts in collective gen AI experimentation depends on organizational scaffolding that mitigates the hidden workload of trial-and-error, review, alignment, and integration activities. NE Health’s implementation of four types of scaffolding—including ongoing training, shared evaluation rubrics, clear risk assessment frameworks, and formal recognition of AI innovation work—enabled broad expert participation and the development of over 140 gen AI solutions. In contrast, LegalCo’s lack of such scaffolding led to expert disengagement and the failure to scale AI initiatives. The study highlights that the success of gen AI innovation relies less on the technology itself and more on the supportive structures that enable domain experts to collaboratively experiment and integrate AI into workflows. [Extracted from the article] |
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| Βάση Δεδομένων: |
Business Source Index |