Leading AI Adoption in Your Team training in Sion · canton of ValaisWhy a team adopts — or ignores — a new AI tool

Making an AI tool available guarantees neither its use nor the value created. Technology acceptance research offers a solid framework for understanding what makes the difference.

The founding model

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

The broader confirmation

Viswanath Venkatesh and colleagues (2003, MIS Quarterly) merged 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 implies for AI

These models were validated on various technologies, not specifically generative AI. But they explain why a tool imposed without a concrete use case goes unused: usefulness is not perceived if it is not tied to the team's real tasks. (our executive and employee training programmes)

The limit of top-down launches

Announcing a tool at executive level and then counting logins says nothing about real adoption. Use constrained to satisfy an indicator is not an anchored practice.

A practical check in {CITY}

In a team entre énergie hydraulique, santé, viticulture et tourisme alpin, start with a short interview with each member about the task they would gladly hand to an assistant, then build a four-week pilot on that task. The spontaneous usage rate at the end of the pilot is a more honest indicator than activated licences. A AI training in Sion can frame this adoption process. To go further: explore the Leading AI Adoption in Your Team training in Sion in the canton of Valais, or browse our executive and employee training programmes in Switzerland. AI training in the canton of Valais.

In pictures: Leading AI Adoption in Your Team in Sion

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