Enterprise transformation experience applied to AI adoption.
My background spans more than 30 years in project management and more than 15 years as a senior Agile coach. I have worked in complex enterprise environments where change succeeds only when strategy, delivery, governance and people line up in the work itself.
Today that experience is focused on enterprise AI adoption and transformation: connecting AI strategy with workflow redesign, decision rights, governance, leadership and the feedback loops required to make adoption visible and improvable.
Point of view
The most useful question is rarely “Which AI tool should we use?” It is “What needs to change in the way this work is performed, governed and led if AI is going to matter?” That shifts the conversation from experimentation alone to operating capability.
How I work
I start with the operating reality. Where do handoffs stall? Where is rework accumulating? Where are people already creating their own AI workarounds? Which decisions are unclear? What must remain under accountable human judgment? The gap between the documented process and the real process is usually where adoption becomes visible.
From there, findings are translated into priorities, workflow changes, governance controls, ownership and measures that leaders can act on.
Working languages and delivery
Engagements are delivered virtually. English is the initial international website language; German and Arabic are also supported working languages.