IA on the job: asking the machine to avoid asking for advice?
Asking for advice within a team also involves the impression people believe they convey of their competence. The management question is specific: how can AI serve as a first point of contact without reinforcing the avoidance of useful requests for advice?
What the literature establishes
Alison Wood Brooks, Francesca Gino and Maurice E. Schweitzer (2015, Management Science) show in their experiments that seeking advice can increase, rather than diminish, the advice seeker's perceived competence. This effect depends notably on task difficulty and the expertise of the person approached. The fear of appearing incompetent therefore does not necessarily reflect how the recipient interprets the request.
An often underestimated willingness to help
Francis J. Flynn and Vanessa K. Bohns (2008, Journal of Personality and Social Psychology) show that people underestimate the likelihood that others will agree to a direct request for help. The mechanism examined involves, in particular, insufficient recognition of the social cost of refusing for the person approached. Agreement should therefore not be mistaken for unconstrained availability.
The premature conclusion
One might conclude that people should always ask a colleague rather than AI; these studies do not support that prescription. An assistant can help clarify a question before it is asked, without replacing the advice itself. The useful distinction is between preparation that facilitates an exchange and use that primarily enables its avoidance. (our executive and employee training programmes)
What these findings do not demonstrate
These studies concern neither generative AI nor teams in Basel, and they do not demonstrate that consulting an assistant reduces human interaction. Nor do they establish that every request for advice improves a decision or is welcomed in every hierarchical relationship. Managers therefore need to observe, rather than assume, why people refrain from asking.
A practical check in Bâle
As part of SHR's “IA on the job” programme, a Basel team in pharmaceuticals, life sciences, Rhine logistics or international R&D could test a rule for two weeks: use the assistant to formulate a question, then approach a colleague whenever the answer depends on a local commitment or a trade-off between functions. For non-sensitive situations and using an authorised tool, a minimal log records the identified need for advice, whether a colleague was actually approached and whether the planned next step changed. The ratio of requests made to needs identified makes compliance with the rule verifiable; observed changes indicate what the exchange contributed. Anonymous feedback on requests not made can then distinguish a question that became unnecessary from one abandoned for fear of imposing or appearing incompetent. To go further: explore the AI on the Job training in Basel in the canton of Basel-Stadt, or browse our executive and employee training programmes in Switzerland.
In pictures: AI on the Job in Basel
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