Capacity is a leadership choice

Time saved becomes value only when someone decides what it is for.

A briefing takes less time to draft. The team can now investigate a difficult question, speak to a less-engaged member, improve accessibility or learn a new skill. It can also be asked to produce more briefings.

Neither outcome is built into the technology. Treat the allocation of capacity as part of the investment decision, not a conversation to have after the pilot.

Measure the whole job

Research gives good reasons to test AI, but not to promise a ready-made return. Noy and Zhang found shorter completion times and higher assessed quality in an experiment on professional writing. Brynjolfsson, Li and Raymond found an average productivity improvement of around 15% among customer-support agents at one company, with substantial differences between workers. Those settings are not a forecast for your policy paper or crisis response. [11, 12]

Count preparation, generation, verification, correction, approval and maintenance. Add licences, training, security support and expert attention. A striking first draft can still be expensive if one specialist spends the afternoon identifying subtle errors.

Measure the route to an approved, usable result, not the route to generated text. Agree in advance what would justify continuing, narrowing or stopping the use.

Your existing strengths and weaknesses matter. Specialist knowledge, trusted relationships and an approved archive can support useful assistance. Outdated documents, weak language coverage or dependence on one reviewer can undermine it. Better retrieval is not a cure for poor source management.

Keep the conditions for expertise

Junior colleagues learn by researching, constructing arguments and receiving feedback. Preserve opportunities to work from original sources and explain why a plausible answer is inadequate. Asking people to review material competently while removing the work through which competence develops is a poor long-term bargain.

Lee and colleagues found relationships between confidence in AI and self-reported critical-thinking effort. The study does not establish inevitable cognitive decline; it reinforces the case for deliberate work design. The ILO likewise distinguishes task exposure from the disappearance of whole jobs. [14, 15]

Involve staff in deciding which tasks to change. Reviewers need knowledge, time and permission to reject an output. People should be able to report an unsuitable use without being blamed for finding it.

Decide who benefits

Acemoglu and Johnson's work challenges the assumption that technological progress automatically distributes its benefits widely. Applied here, the management question is whether efficiency improves service and working conditions or simply intensifies production. [13]

There are material costs beyond the team. Kate Crawford places AI within wider systems of labour, infrastructure and resources. Proportionate use starts with choosing worthwhile tasks and asking meaningful supplier questions, rather than treating endless generation as a goal. [16]

Put the destination of any released capacity in the work plan. Otherwise, the next deadline is likely to decide for you.