We commit to identify, document and systematically support the reskilling of our domain experts and mitigate the impact on workers affected by automation, enabling Reskilling by Design.
Automating medium or large processes affects many people across an organisation or industry, and general-purpose AI has widened the range of work this applies to. Technologists should look beyond the technology and help relevant stakeholders understand those effects and their impact. As observed with Jevons’ paradox, when a new technology unlocks major automations that reduce the costs of a service, total demand does not decrease; in fact, as the service becomes more accessible, total demand increases. So it is important that the industry as a whole is supported to evolve towards that increased demand.
Even if more junior practitioners do not lead an operational transformation, they should contribute to ensure that appropriate change-management processes are in place, particularly if they are involved in the development of the AI systems involved. Those processes should contribute towards a sustainable industry-wide effort to shift and evolve amid the accelerated transformation that AI systems are imposing in society and the workforce.
01 — WHERE IT FAILS
Where it fails
Displacement is rarely a single event; it accumulates while attention stays on the technology.
- No systematic plan for supporting the workforce whose work is changing.
- No retraining or reskilling paths for the roles being automated.
- Process changes that go undocumented until the operational knowledge is gone.
02 — PRACTICAL CONTROLS
Practical controls
Controls should treat workforce impact as part of the delivery, not an afterthought of it.
- Assess workforce impact before automating a process.
- Plan business change alongside technical delivery, with reskilling paths for affected domain experts.
- Document process changes so knowledge survives the transition.