AI adoption: does the recipient of the work remain visible?
In SHR — Swiss Human Resources’ programme “Leading AI adoption in your team”, adoption is usefully examined as a transformation of work, not simply a change of tools. This raises a precise managerial question: how can employees retain an understanding of the value their work provides to its recipient when AI takes over some of its stages?
What the literature establishes
John Richard Hackman and Greg Oldham (1976, Organizational Behavior and Human Performance) studied a model linking job characteristics to psychological and motivational outcomes. Task significance — its impact on other people’s lives or work — contributes to experienced meaningfulness, alongside skill variety and task identity. This framework therefore distinguishes efficient execution from the experience of doing work that matters.
The mechanism: seeing whom the work benefits
Adam Grant (2008, Journal of Applied Psychology) experimentally examined the effects of task significance on performance. His findings highlight, among other things, the role of perceived social impact and the feeling that others value one’s work, as well as conditions that moderate the observed effects. For a manager, this suggests examining the feedback that makes an employee’s contribution visible, rather than assuming that higher output alone provides motivation.
The premature conclusion
One might conclude that delegating some work to AI necessarily makes it less meaningful. These studies do not establish that: automation can also free up time to understand a request or support a client. What matters is less the amount of work automated than how much the new organisation of work reveals about its consequences for others. (our executive and employee training programmes)
What these data cannot establish
These articles address neither generative AI nor businesses in Lugano; they cannot predict a local effect on adoption. The first tests a model of job design, while the experiments in the second concern particular occupational settings. An increase in document production or a general satisfaction survey would therefore be insufficient to verify that the connection with the recipient has been preserved.
A practical check in Lugano
In a bank, fashion business, trading company or Italian-speaking family SME in Lugano, select a single AI-assisted workflow and propose a two-week log, without moving confidential data outside authorised systems. For each deliverable, record in Italian its recipient, the intended benefit and whether feedback from that recipient confirms the benefit. Calculate the proportion of deliverables with such feedback, then review cases without feedback with the team: this rate measures the visibility of value, not value itself, and gives SHR’s programme a concrete starting point for adjusting feedback loops. To go further: explore the Leading AI Adoption in Your Team training in Lugano in the canton of Ticino, or browse our executive and employee training programmes in Switzerland.
In pictures: Leading AI Adoption in Your Team in Lugano
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