Leading AI Adoption in Your Team training in FribourgWhy a team adopts—or ignores—a new AI tool

Making an AI tool available does not guarantee its use or the value created. Research on technology acceptance offers a solid framework for understanding what makes the difference.

The foundational model

Fred Davis (1989, MIS Quarterly) established that technology usage depends above all on two perceptions: perceived usefulness and perceived ease of use. This acceptance model remains one of the most cited and replicated in management science. Davis, 1989

The expanded confirmation

Viswanath Venkatesh and colleagues (2003, MIS Quarterly) integrated eight competing models into a unified theory: usage intention depends on performance expectancy, effort expectancy, social influence, and facilitating conditions. Venkatesh et al., 2003

What this means for AI

These models have been validated across various technologies, not specifically on generative AI. But they explain why a tool imposed without concrete use cases remains unused: usefulness is not perceived if it is not linked to the team's actual tasks. (our executive and employee training programmes)

The limitation of top-down rollouts

Announcing a tool in a management committee and then measuring logins tells nothing about actual adoption. Constrained usage to satisfy a metric is not an embedded practice.

A practical implication, verifiable in {CITY}

In a team spanning bilingual SMEs, agrifood and public services, begin with a short interview with each collaborator about the task they would willingly hand over to an assistant, then build a four-week pilot around that task. The rate of spontaneous use at the end of the pilot is a more honest indicator than the number of activated licences. An AI Training in Fribourg can guide this adoption approach. To go further: explore the Leading AI Adoption in Your Team training in Fribourg in the canton of Fribourg, or browse our executive and employee training programmes in Switzerland. AI training in the canton of Fribourg.

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