01
Business first, then the model
Every engagement starts with the P&L and the processes, not the technology. The question is never “where can we use AI?” — it is “which number are we trying to move, and is AI the cheapest way to move it?”
Based inTallinn, Estonia
WorkingAcross Europe · remote-first
CompanyArvanu · Healthview AI OÜ
About
The seat between the business and the technology.
I’m Michael Kilty. I work as a Head of AI — the executive who sits between the business and the technology and is accountable for AI actually paying off.
Right now I hold that title at a compounding pharmacy in Athens, where I took a regulated, paper-and-phone operation to a live AI-enabled platform in 87 days — patients, clinicians, pharmacists, payments, and treatment-recommendation AI, all under GDPR and pharmacy regulation.
Before that I spent years building AI systems hands-on through Arvanu, my consulting practice under Healthview AI OÜ. That history matters: I make build-vs-buy calls, review architecture, and challenge vendor claims from experience, not from a briefing document.
The role I do best is the one most companies are missing: IBM found 76% of organisations now have a Chief AI Officer, because someone has to own the gap between AI spend and AI results. That gap is my job.
How I operate
Four rules the work runs on.
02
Both rooms, same person
The value of this role is refusing to pick a side. I can hold the board conversation about risk appetite and the engineering conversation about architecture — and make sure they stop contradicting each other.
03
Governance built into delivery
The work is not done when the model responds. It is done when the workflow, approvals, monitoring, and ownership model hold up under audit and under pressure.
04
Leave the team stronger
A good engagement reduces dependency over time. The goal is internal capability — a team that runs AI well because of how the operating model was built, not because I am still in the building.
Where I’m most useful
Where mistakes cost real money.
In serious businesses, the hard part of AI is rarely access to tools. It is deciding what should be automated, who owns the risk, what still needs human review, and whether the system survives real operational use — and an audit.
My background is in exactly those environments: healthcare and pharmacy operations under GDPR and sector regulation. If your business is one where trust and traceability are non-negotiable, that experience transfers directly.
Direct contact
You don’t need a pitch deck to start a conversation.
A stalled AI initiative, a board asking questions you can’t yet answer, or a sense that the tools you’re paying for aren’t earning their keep. Any of that is enough.