AI adoption: who can question the new allocation of work?

When a team introduces AI, some people take on checking tasks while others can devote more attention to client relationships or design. The managerial question is specific: how should this new allocation be decided without treating the absence of objections as evidence of fairness?

What the literature establishes

Jason Colquitt (2001, Journal of Applied Psychology) provides validation evidence for distinguishing four dimensions of organisational justice: distributive, procedural, interpersonal and informational. The resulting allocation, the decision-making process, the treatment of people and the explanations provided are therefore not a single judgement. Applied to AI, this framework encourages managers to distinguish a task allocation considered acceptable from a genuinely fair procedure.

Having a voice is not making the decision

Robert Folger (1977, Journal of Personality and Social Psychology) experimentally examines how the opportunity to express one's views and changes in an allocation influence experienced inequity. His work shows that responses to an allocation do not depend solely on what each person receives: the opportunity to speak also matters. For managers, this suggests gathering objections to task allocation before making the decision, without confusing consultation with a right of veto.

The hasty conclusion

One might conclude that consultation is enough to make any AI-related reorganisation acceptable. The distinction between procedural and distributive justice rules out this shortcut: being able to speak does not automatically correct a checking burden concentrated on the same people. A credible procedure must leave room to change the decision, not merely improve its presentation. (our executive and employee training programmes)

What these findings cannot promise

Neither article studies generative AI or companies in Ticino. They do not demonstrate that a procedure perceived as fair increases AI use or improves productivity. They offer a framework for examining managerial decisions, not an adoption formula: a satisfaction questionnaire alone cannot establish that tasks have been allocated fairly.

A practical check in Lugano

As part of SHR’s programme “Leading AI adoption in your team”, one exercise is to document every task-redistribution decision for a month: who gains a task, who loses one and who takes responsibility for checking. In Lugano, this register could cover file preparation in a bank, product descriptions in fashion, commercial documentation in trading or customer correspondence in an Italian-speaking family SME, with consultation in Italian where that is the working language. The proposed measure is the proportion of decisions for which affected people could raise an objection before the decision and received a reasoned response, out of all recorded decisions. Checking dates, objections and responses makes the procedure observable; this ratio measures an actual opportunity to participate, not the fairness of the outcome. To go further: explore the Leading AI Adoption in Your Team training in Lugano, or browse our executive and employee training programmes in Switzerland.

In pictures: Leading AI Adoption in Your Team in Lugano

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