Adviser, Enterprise AI Investment and Governance

Judgement before adoption

The adviser will help an enterprise leadership team evaluate proposed uses of artificial intelligence and establish proportionate governance for adoption. The scope is business and technology advice, including use-case assessment, operating controls and investment recommendations. It does not confer authority to deploy systems, approve personal-data processing or determine clinical suitability.

Make the use case earn approval

The work should distinguish useful automation from demonstrations that lack a viable operating owner. Each proposal must identify the decision or task being changed, the users affected, the information required and the consequences of an incorrect output. Potential productivity gains need a credible explanation of how released capacity will benefit the organisation.

Different applications require different decisions

An internal drafting assistant, a service triage tool and a system influencing sensitive operational decisions should not share an undifferentiated approval process. The adviser will recommend assessment routes based on impact, data sensitivity, human oversight and the ability to detect or reverse mistakes. Specialist legal, privacy, security and clinical input must be sought where relevant.

Test the continuing operating burden

The engagement will examine build, buy and extend options, including supplier dependence, integration costs and access to evidence about performance. Recommendations should account for ongoing monitoring, changes in model behaviour and the work needed to maintain reliable human review. A pilot that depends on exceptional manual supervision may not support a scalable business case.

The adviser will design decision papers that make assumptions and unresolved questions clear. Management should be able to approve a bounded experiment, require more evidence or reject a proposal without interpreting technical marketing claims. Procurement and deployment remain with authorised teams.

A portfolio of bounded experiments

The final output will include a prioritised use-case portfolio, proportionate assessment criteria, pilot evaluation plans and recommended ownership. It must distinguish verified benefits from hypotheses and identify the conditions required before wider deployment.

Success means that leadership can select worthwhile opportunities while maintaining accountability for outcomes. The adviser should leave a process that business teams can use without treating every experiment as a major programme or allowing apparently small tools to accumulate consequential unmanaged dependencies.