A recent article in the September–October 2026 issue of Harvard Business Review stopped me in my tracks. Felipe Csaszar’s argues that AI is loosening the cognitive limits that have always shaped strategy: we weigh only a handful of options, lean on static frameworks, and decide in rooms skewed by hierarchy and groupthink.
His examples focus on markets and competitors. But after nearly 20 years helping Fortune 500 clients through workforce transformations, I’ve seen those same limits play out in people decisions again and again. Change doesn’t fail at the plan. It fails at the impacts.
Bringing the three shifts to workforce strategy
That’s why we built Kario AI(TM), The Change Shop’s workforce intelligence platform. Here’s how it brings Csaszar’s ideas to workforce strategy.
Widen the options before you commit. Csaszar urges leaders to explore a long list before debating a short one. With Kario’s what-if scenario planning, you can test several restructuring, rollout, or reskilling paths against simulated employee reactions before choosing one that will be the best fit for your organization and change type.
Trade snapshots for a living model. I’ve long seen the annual engagement survey as the workforce version of a static 2×2. Kario builds a digital twin of your workforce that projects how perceptions will shift across five stages of change and flags talent risks early.
Stress-test without the politics. Csaszar recommends synthetic stakeholder panels to see how a decision will land. Kario’s Smart Scenario and Smart Panel modules to do exactly that, surfacing reactions across four profiles (Analysts, Anchors, Drifters, and Stormfronts) without the filtering–something I’ve watched happen in live focus groups.
The edge is in the data, and the call is still yours
When everyone can use the same AI models, advantage comes from what you build on top of them. I fully agree. Kario AI(TM) is grounded in more than a decade of research into 10,000+ workers’ experiences of change and our 2IsC Model of Impact, Influence, and Consistency.
AI output still needs human judgment, a principle that is built into how we work with clients from day one. It gives leaders sharper signals but the final call is still yours.
