DELIVERY MODELS · EXPERT ARTICLE
AI Officer as a service: when it pays off
The role is mandatory, the full-time position is not. A sober look at tasks, workload and the question of when a provided function is the better decision.
Edith Hillebrand-Edwards·5-minute read
The AI Officer is not a showcase role. The AI Officer is responsible for inventory, classification, approvals and evidence — and needs a mandate, methodology and regulatory depth to do so. It is precisely this combination that is scarce on the market.
What the role actually has to deliver
Four blocks of tasks determine the effort: inventory management and classification, approval of new use cases, evidence management vis-à-vis auditors, and competence building in the business units. Only the second block scales with the pace of innovation — the others can be planned.
The workload question
In organisations with a manageable number of productive AI use cases, a full-time workload rarely arises — but there is a continuous need for decision-making capability. This is exactly where a provided model fits: reliable presence at fixed intervals, scaling during project peaks.
‘The obligation is not the position, but the effectiveness of the function.’
When to staff internally — when to use a provided function
High case numbers, deep product integration and an existing second line of defence speak in favour of internal staffing. Build-up phases, several regulatory projects running in parallel and the wish to buy in methodology rather than develop it speak in favour of a service model. The combination is often right: a provided function for the build-up, internal takeover after twelve to eighteen months.
STAFF INTERNALLY IF
- many productive AI systems in the core business
- an established second line of defence is in place
- in-house AI development with a high rate of change
USE A PROVIDED FUNCTION IF
- build-up phase without an existing methodology
- several regulations in parallel (AI Act, DORA, CSRD)
- demand fluctuates strongly with project peaks
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