When AI Disruption Never Ends
Rory McDonald and Will Drover argue AI has produced perpetual rather than episodic disruption, which breaks conventional change management built on the assumption that transitions eventually conclude. They set out three “steady-state disruption” practices: permanent AI infrastructure instead of rolling pilots, split cadences for initiatives moving at different speeds, and embedded learning held as standing capacity. Their core claim is that optimising for speed alone produces organisational fatigue and loses to organisations built for endurance.
If you have been waiting for tooling to stabilise before investing in depth, stop — there is no settling point to wait for, so build learning into your weekly cadence rather than treating it as a project with an end date. Notice too whether your organisation runs everything at one urgent tempo; that is the pattern the authors identify as the fatigue driver, and it is worth naming when you scope your own work.
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