Senior AI advisor to European leadership teams. 30 years cross-industry, independent by choice. Pan is my editorial name; PiirZ Digital is my delivery firm.
I started as a technologist and grew up as a consultant. For thirty years I've worked at the points where technology meets decisions — boardrooms, ministries, foundations, C-level offices — and where most innovations are either accepted or ignored.
I started in the '90s, when "technological innovation" meant moving a company from fax to corporate email. I worked on the web before Google existed, on e-commerce before Amazon Italy, on mobile before the first iPhone reached Europe, on AI before it became every board's 2024 theme. Not because I had a nose for the future — but because I learned early that every innovation passes through two phases: first it's rejected as "not mature," then it's absorbed as "obvious." My work has always been in between, where decisions cost.
Today I help European leadership teams — mid-large companies, public institutions, VC funds, scale-up founders — take artificial intelligence from the boardroom to production, in a way that survives a European audit. I have no vendor to push. I sell no licenses. I sign the strategy personally, and my delivery team (PiirZ Digital) ships it.
The numbers I show in the boardroom, before the projects.
When a new client asks "but what have you actually done," I tell these three. They're not the biggest or the most recent — they're the ones that taught me the most.
The challenge wasn't building a better algorithm. It was convincing experienced investigators that a machine learning system could help them see better, not replace them. We worked on false positives — the metric that frustrated them daily — and reduced noise by 40%. Investigation speed rose by 60%. The lesson: AI in regulated environments works when it reduces unnecessary work, not when it promises full automation.
Fourteen million tourists per year generate data everywhere: bookings, airport flows, social sentiment, economic indicators. When you arrive, you find forty different dashboards and nobody who actually reads them all. The project was about cutting: a single dashboard with predictive algorithms on seasonality and sectoral crises. The regional government raised campaign effectiveness by 15% and cut response times by 25%. The lesson: sometimes the value of an AI system is what it cuts, not what it adds.
Adopting AI and blockchain in a public service requires one thing before the technology: a governance framework that balances innovation and citizen rights, and survives the political cycle. That's what we built — and what positioned Monaco as a European reference point for responsible adoption of emerging technologies in public administration. The lesson: in public institutions governance isn't a brake on innovation — it's the condition of its survival.
Three principles that guide everything. Not manifestos — operational rules.
I take no commission from any vendor. When I recommend a supplier, it's because the client needs it — not because someone pays me a referral. To me, a consultant's credibility is the only non-scalable asset, and I'm not willing to spend it.
I work in person. Operational delivery is handled by PiirZ Digital with adequate teams, but the strategic thinking is mine and signs with my name. If you want a big deck with twelve white slides and a partner who shows up at kickoff, I'm not your guy.
I don't write strategies that die in PowerPoint. Every roadmap I deliver is executable from day one, with priorities, owners, timelines, and — above all — a delivery partner ready to start. A strategy that can't be executed isn't a strategy. It's an essay.
Fill in the pre-qualification form (5 questions, two minutes). A thirty-minute discovery call: you tell me where you are and what you need, I tell you how I'd approach your specific problem. No pitch, no commitment.