Capacity & Change Fatigue
We plan change in a sensible order and protect people's time and energy. We manage tiredness from change as a risk to delivery.
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AI can raise enjoyment and stress at the same time
Among regular AI users, 67% enjoy work more since adopting AI and 41% report increased mental strain (BCG, AI at Work, 2026; 11,749 respondents in 14 markets). 79% of employees have low trust in organisational change (Gartner, 2025; survey of more than 2,850 employees). Deloitte finds that organisations that cultivate what it calls "changefulness" are 2.4 times more likely to report better financial results and to provide more meaningful work (Deloitte, Global Human Capital Trends, 2026).
Change fatigue (tiredness from too much change) matters in every AI programme. It is a risk to delivery. We manage it like one.
Systematic Burnout Prevention in the AI Era
A three-day executive programme for business executives and HR leaders. It is built on InnovaStrata's WISH™ framework. Participants learn how AI can make work more intense. They link people's stress to business results. They learn the four pillars of WISH™. They place their organisation on a four-stage maturity model: Unregulated, Structured, Paced, Symbiotic. They leave with an Action Planning Guidelines Booklet. It has a section for each pillar, filled in on Days 2 and 3. Participants then combine it into one first plan for their team. They test the plan with a peer.
The maturity exercise shows where participants think their organisation is. For a measured picture, use the Human Layer Diagnostic. It also measures capacity: weekly tiredness, amount of change, trust in change, AI workload. Each is measured separately.
How it runs
Day 1 | Day 2 | Day 3 | |
|---|---|---|---|
Theme | The case and the diagnosis | WISH™, part one | WISH™, part two, and the way forward |
Content | Modules 1-3: the adoption crisis, the global picture, diagnosing the impact | W: Workload pacing; I: Intentional reskilling | S: Psychological safety; H: Institutional headship; maturity model; action planning |
Applied work | Rose, Thorn & Bud challenge; simulation round 1 (diagnose) | A practice lab and preliminary plan for each pillar | A practice lab for each pillar; simulation round 2 (redesign); maturity self-assessment; Guidelines Booklet |
Participants leave with | A shared language for AI-driven strain | Preliminary plans for W and I | Plans for all four pillars and a self-assessed maturity level |