I work at the intersection of behavioral science, AI adoption, and human-centered transformation — helping organizations design changes people actually adopt, and sustaining them long after go-live.
Ten years across Accenture and EY designing change programs for large-scale transformations — ERP rollouts, shared service center go-lives, culture shifts, new ways of working. I kept seeing the same gap: programs that checked every adoption box, and six months later, nobody actually working any differently.
Today I take on independent consulting projects focused on HR transformation — new tools, new operating models, new ways of working — where adoption is the real deliverable, not a checkbox.
Most transformation roadmaps stop at the future state. I take it one level deeper — into the specific, observable behaviors that make that future state real, so success can actually be measured.
The strategic vision — the new tool, the new process, the new way of working, as leadership defines it.
The vision broken down into specific, observable actions: what people do differently, in which moment, instead of what.
Because behaviors are observable, they're measurable — turning adoption from a feeling into a number leadership can track.
Implementation isn't adoption.
A rollout can hit every milestone on the plan and still leave people doing things the old way. The behaviors in between are what decide which one happens.
Every format below runs on the same model — the Behavioral Enablement Layer — breaking transformation down into future state, microbehaviors, and measurable outcomes.
A talk for leadership and HR audiences on why transformation programs check every adoption box and still fail — and what it actually takes to make change stick. Tailored to your audience, in person or virtual.
Why AI rollouts fail for the same reason every other transformation does — and how to design the specific behaviors that turn a new tool into something people actually use.
A hands-on session where your team maps its own transformation into future state, microbehaviors, and KPIs — leaving with a working draft, not just a framework.
Redesigning existing training programs so they teach behavior, not just content — so the learning experience makes the new way of working easier to do, not just easier to explain.
Pinpointing exactly where real adoption breaks down: which behaviors need to be installed, which need to be unlearned, and what's quietly reinforcing the old habit.
Traditional change management, made more precise with a behavioral science layer — translating stakeholder strategy and communications into the specific behaviors that define success.
Embedding the same behavioral rigor into AI rollouts as any other transformation: which behaviors change, with which AI tool, and how it gets measured — not just a training deck.
Designing the full adoption architecture of a program — stakeholders, communications, training, and measurement — integrated under one behavioral model instead of run as separate workstreams.
Mapping and supporting sponsors, middle management, and end users so change has real allies at every level — not just formal sign-off.
Not sure which format fits your team?
Get in touchWhy most change programs run on hope instead of precision — and the missing layer between frameworks like ADKAR or Kotter and what actually changes on an ordinary Tuesday.
Blog · free readSpanish edition — why organizations confuse compliance with real transformation, written from inside real projects, not from theory.
Kindle · USD 9.99English edition — why organizations confuse compliance with real transformation, written from inside real projects, not from theory.
Kindle · USD 9.99The same 2-page diagnostic from the book, free in exchange for your email — no purchase needed.
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