AI Operations · Role
Head of AI Operations
The Head of AI Operations runs the whole function: strategy, team, governance and budget. They answer for AI's aggregate business impact, not a single project.
What they do
- Set the company's automation strategy and roadmap.
- Build and lead the team (managers, engineers, governance).
- Own aggregate ROI and risk in front of leadership.
Skills it needs
Salary by country and seniority
| Country | Seniority | P25 | Median | P75 | |
|---|---|---|---|---|---|
| Germany | Head / Director | €116,906 | €116,938 | €116,969 | Public-source estimate |
| Spain | Head / Director | €90,008 | €110,005 | €130,003 | Public-source estimate |
| Spain | All | €48,000 | €48,000 | €48,000 | Public-source estimate |
| France | Head / Director | €83,700 | €85,800 | €87,900 | Public-source estimate |
| United Kingdom | Head / Director | €170,510 | €170,510 | €170,510 | Public-source estimate |
| Italy | Lead | €44,939 | €44,939 | €44,939 | Public-source estimate |
| Italy | Head / Director | €90,500 | €90,500 | €90,500 | Public-source estimate |
| United States | Head / Director | €183,823 | €220,686 | €220,686 | Public-source estimate |
Figures in euros, gross annual — each with its source.
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The market uses several titles for the same role:
How it changes by seniority
- At an SMB — The end-to-end operational owner: strategy, execution and governance, often with a small team.
- At a scale-up — Builds the function: hires, defines processes and moves from one-offs to a measured portfolio.
- At an enterprise — Leads several teams and governance at scale; owns ROI and risk in front of leadership.
When to hire
When AI stops being a project and becomes a function with its own team and budget.
When not to
If you're still validating your first use case: this is a scale role, not a starter one.
Interview questions
1. How do you set the annual AI budget and how do you defend it to the leadership committee?
What to look for: Reasons in portfolio terms (what scales, what gets switched off) and business case, not a technical wish list.
2. What team structure do you build to move from a project to a function?
What to look for: Distinguishes profiles (execution, engineering, governance) and knows what to hire first by maturity.
3. A deployment makes a wrong decision that hits a customer. Who is accountable and what do you change?
What to look for: Owns the accountability rather than spreading it; turns the failure into governance, not blame-hunting.
4. How do you know whether the AI Operations function is making or losing money in aggregate?
What to look for: Has a portfolio view with ROI per process and switches off what underperforms.
Scorecard
- Portfolio strategy — Prioritises the set of initiatives by impact and risk; scales or switches off with judgement.
- Team building — Builds and levels up the team; knows the sequence of profiles by maturity.
- Accountability — Owns aggregate impact and risk to leadership, without diluting responsibility.
- Business case — Translates AI into business language: defensible budget, return and risk.
Red flags
- — All vision and no number: can’t say what the function returns.
- — Dodges responsibility when something goes wrong ("it was the model", "it was the team").
- — Wants to hire a large team before validating the first use case.
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