Taking engagements · Q3 2026
jeromebasdevant.com
Based in Spain · FR · EN · ES
AI Leadership Advisory · Jérôme Basdevant

AI is already inside your company. The question is who's leading it.

I help leadership teams figure out what AI actually changes about their business and then make the shift real.

25 years building, scaling, and reinventing technology products across four countries.

Tenure
25 YRS
Building products & teams
SaaS built
02
Platforms from scratch
Team scaled
0 → 50
Product & engineers
Rounds raised
A · B · C
Series, all three
Why Now

The tools are here. The leadership isn't.

Your team is already using AI. Engineers prompt models. Someone built a prototype over a weekend. There's a pilot somewhere. Maybe more.

But nobody's answered the harder questions. Which processes should you automate and which should you rethink entirely? Where does AI create genuine competitive advantage? Where is it just faster busywork? What should you stop investing in? And who in your organization actually owns this?

"Who in your organization would know if the AI output was wrong?"

If nobody can answer that clearly, you don't have an AI strategy. You have a collection of experiments.

This is happening everywhere, not just in the software.

Go-to-market

AI is eating search, automating sales end to end, and collapsing finance workflows into agents. Danfoss automated the majority of its transaction decisions using agentic AI, cutting customer response time from 42 hours to near-instant.

Product

Agents and LLMs are collapsing SaaS tool stacks. Your users won't click through five screens when an agent handles it in a sentence. The question becomes how much of it still needs to exist.

Operations

AI is replacing the manual inspector, the human scheduler, the break-fix maintenance team. All of that in production, across industrials and manufacturing, at scale. The question is how far up the decision chain it goes next.

These questions don't live in engineering. They live in leadership. And most leadership teams don't have anyone who can hold the technology, the strategy, and the organisational change in one conversation.

What Changes When I Show Up

Your roadmap gets honest.

Every roadmap has the wrong things on it. A meaningful share of what's in progress is either the wrong bet or the right bet at the wrong time. The work is finding which is which and building the discipline to cut, not just re-prioritise.

Experiments move faster than planning cycles.

When AI handles the scaffolding, your team focuses on the hard problems. The cycle from "what if" to "here's the data" gets short enough that bad ideas die before they become expensive commitments.

The gap between product and engineering closes.

The friction usually is no longer the technology but the distance between the people deciding what to build and the people building it. I close that gap by making sure the people building understand why. Everything downstream improves.

Your leaders level up.

The CTO stops firefighting. The founder steps out of the weeds. Key people grow into roles that didn't exist six months ago. I build capability that stays after I leave.

AI gets governed, not just deployed.

Clear rules on what AI touches, what it doesn't, and who's accountable when the output is wrong. Including where you stand under the EU AI Act. Your clients and partners are already asking those questions. It's time to take it seriously.

Hard choices get made.

Most AI programs generate a lot of activity, pilots, workshops, strategy decks without generating outcomes. I help you get from conversation to commitment: what to build, what to stop, who owns what. If it doesn't change how your team works, it wasn't strategy.

Engagements

Every engagement builds your internal capability.

Start here · 10 minutes · Free

AI Leadership Snapshot. A 1-page read of where you stand. If we both see something worth digging into, the full AI Readiness Diagnostic goes deeper over 2–4 weeks.

Take the Snapshot
I.

Where do we actually stand?

Diagnostic · AI Readiness

Your team has opinions. Your board has questions. Nobody has the same picture.

  • Where AI creates real advantage in your specific business
  • What your team has already tried, what worked, what stalled, and why
  • Whether your organization is actually ready — skills, data, processes, governance
  • Honest assessment of risk: what happens if you do nothing vs. what happens if you move wrong
FormatDiagnostic study
Duration2–4 weeks
OutputShared picture
AudienceLeadership team
II.

What do we actually do?

Strategy & Hard Choices

You know the landscape is shifting. Now you need to decide and bring the team along.

Starts with a facilitated AI Strategy Workshop — a card deck-based session where your leadership team builds a shared vocabulary, maps opportunities to your actual business, and confronts forced choices: build vs. buy, automate vs. augment, invest vs. let go. The workshop surfaces the real disagreements and assumptions that would otherwise stay hidden until they become expensive.

Then we translate those decisions into a prioritized plan: what to build, what to stop, and in what order. Not a 12-month roadmap, those are fiction in the age of GenAI. A 90-day action plan with clear ownership and an operating model to move forward.

FormatWorkshop + plan
Duration2–4 weeks
Output90-day plan
AudienceLeadership team

The AI Strategy Workshop can also run as a standalone engagement, a natural entry point, and a way to see how I work.

III.

Help us actually change.

Fractional Chief AI Officer (CAIO)

You have the strategy. Now the work starts.

  • Embedded with the team 1–3 days/week
  • Coaching product and engineering leads through new ways of building
  • Redesigning workflows, roles, and decision rights around AI
  • Regular checkpoints with leadership, course-correcting, not just reporting
FormatEmbedded role
Duration3–6 months
Cadence1–3 days/week
AudienceCEO, CTO, product
About

Based in Spain, working across Europe in French, English, and Spanish.

I work across technology, product, and organisational change. Years as CTO inside companies navigating platform shifts and eventually a full generative AI transition. Building, breaking things, making calls that cost money when they were wrong. Then entering from outside at other companies to diagnose and deliver.

That practitioner background is what lets me hold the technology conversation and the strategy conversation in the same room.

The conversation I come back to most is the "what to stop" conversation. Recommending additions is easy. Knowing what to kill, and making the case for it, is where the real work is.

Twelve years building Datamaran from a founding idea to an AI-native platform serving enterprise clients globally. Co-founder and CTO. Scaled product and engineering from 0 to 50. Raised Series A, B, and C. Patent holder on the core AI extraction engine.

That twelve-year run included navigating a full generative AI transition from inside the company. I ran that process myself: which parts of a decade-old product does a capability shift make obsolete? Which become more valuable? I set the strategy, built the agentic AI pod, and redesigned how the team works.

Before Datamaran, I spent several years at ZS Associates in New York, building a SaaS analytics platform for the life sciences industry as an intrapreneur inside a large firm.

For the past six years, alongside the operational work, I have been mentoring and coaching engineers, product leads, and founders at Audencia, Plato, and All Tech Is Human. Giving back is not something I schedule. It is a consistent practice.

What I believe
  • Trust people with ambitious problems before you have verified they are ready.
  • Outcomes over technical elegance, every time.
  • Build for now. The future will be different from the plan.
  • Lead through synthesis, not authority.

Let's talk.

If AI is already changing how your company works and nobody owns the answer yet, I'd like to hear about it.

Book a call
English · French · Spanish — native fluency in all three Based in Spain · Working across Europe