AI on the Job training in NeuchâtelGenerative AI at work: who actually gains in productivity?

Does a generative AI tool rolled out to every desk produce the same effects everywhere? Two field studies give a measured answer, finer than the usual claims.

Gains measured in the field

Erik Brynjolfsson, Danielle Li and Lindsey Raymond (2023, Quarterly Journal of Economics) tracked a generative AI assistant deployed to customer support agents in a large firm. Productivity rose by about 14% on average, with a markedly larger effect for the least experienced workers. Brynjolfsson, Li & Raymond, 2023

The effect on writing tasks

Shakked Noy and Whitney Zhang (2023, Science) measured in a controlled experiment that access to a generative model cuts the time spent on professional writing and improves perceived quality, again mostly for less confident writers. Noy & Zhang, 2023

What these results do not say

Both studies cover specific tasks — customer replies, short writing — not entire jobs. They measure neither long-term quality nor the effect on juniors who lean on the tool early in their learning. (our executive and employee training programmes)

The limit of a uniform rollout

If gains concentrate on certain profiles and tasks, one identical instruction for all wastes potential where it exists and breeds frustration where it does not. Task analysis precedes tool choice, not the reverse.

A practical check in {CITY}

In a team entre microtechnique, horlogerie et laboratoires de recherche appliquée, list repetitive writing-heavy tasks for two weeks, then test the tool on one of them with a human checkpoint. Comparing time spent before and after gives a local measure, without extrapolation. A AI training in Neuchâtel can frame this role-by-role diagnosis. To go further: explore the AI on the Job training in Neuchâtel in the canton of Neuchâtel, or browse our executive and employee training programmes in Switzerland. AI training in the canton of Neuchâtel.

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