Does deploying the same AI harmonise working practices?
Management can give every team the same AI assistant without obtaining comparable working practices. The managerial question is specific: what needs to be harmonised so that AI use does not depend solely on each department’s habits?
What the literature establishes
Wanda J. Orlikowski (1992, Organization Science) proposes a theoretical framework, illustrated by a field study, in which technology is both a product of human action and a medium that structures that action. Its organisational effects therefore cannot be inferred from its features alone: they also depend on the conditions and patterns of use. Applied to AI, this perspective encourages managers to observe practices rather than regard software installation as an accomplished change.
The mechanism: teams appropriate the rules
Gerardine DeSanctis and Marshall Scott Poole (1994, Organization Science) distinguish the structures offered by a technology from the ways groups appropriate them. A procedure built into a tool may be followed, reinterpreted or bypassed in collective work. For a manager, this means examining not just the use of the assistant, but also who intervenes, at what point and under which rules.
The premature conclusion
One might conclude that every department should be required to use the tool identically. Yet these studies do not establish the superiority of complete uniformity: local adaptation is not necessarily a failure. The challenge is to distinguish variations justified by the work from deviations that make responsibilities or handovers ambiguous. (our executive and employee training programmes)
What these studies cannot establish
These articles predate generative AI and primarily offer analytical frameworks, not a measurement of the effectiveness of today’s assistants. They neither quantify the benefits of harmonisation nor identify the optimal degree of standardisation. A shared policy or completed training therefore cannot establish that practices have changed: that change must be observed in the work itself.
A practical check in Lugano
Within SHR — Swiss Human Resources’ programme « Manager à l'ère de l'intelligence artificielle », a proposed exercise in Lugano examines the same operation, such as preparing a customer response, in teams working in banking, fashion, trading or Italian-speaking family SMEs. Over two weeks, record for each eligible case, without copying confidential information, the prescribed rule and the observed practice concerning permitted data, approval and handover to the next colleague. Then calculate the proportion of cases in which a deviation from the protocol has no documented justification, reporting the total number of cases reviewed. Discussing the results in Italian with the teams helps determine whether the rule needs clarification or the local adaptation should be recognised; this rate measures a deviation in practice, not overall work quality. To go further: explore the Managing in the Age of Artificial Intelligence training in Lugano, or browse our executive and employee training programmes in Switzerland.
In pictures: Managing in the Age of Artificial Intelligence in Lugano
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