AI specialist: expertise for strategy and delivery

What does an AI specialist do?

An AI specialist helps an organisation put artificial intelligence to meaningful use. That sounds straightforward, but the title covers very different kinds of work. One AI specialist trains and tests models, another connects a language model to your document system, and a third helps leadership decide which AI investments are worth making and which aren’t.

What they have in common is that they bridge what’s technically possible and what’s genuinely useful for your organisation. A good AI specialist therefore doesn’t start with the technology, but with the question: which problem are we solving, how do we measure whether it worked, and what happens when the system gets it wrong?

Depending on the profile, an AI specialist concretely does one or more of these things:

• assesses use cases for value, feasibility and risk;
• designs, builds, tests or configures AI applications;
• compares and selects vendors and solutions;
• measures and monitors the quality of AI systems;
• sets up governance, including what the AI Act and UK GDPR require;
• guides teams on adoption and day-to-day use.

No single AI specialist is equally strong at all of these. That’s why the first step in looking for AI expertise isn’t a name, but a sharp description of what you actually need.

Kinds of AI specialists

Broadly, there are two families: strategic and technical AI specialists. Each family has its own specialisations within it.

Strategic AI specialists work at the level of decisions. They help determine where AI adds value, which use cases should come first, whether to build, buy or partner, and which risks that carries. Their output is a well-founded choice: a roadmap, a selection recommendation, an assessed business case.

Technical AI specialists work at the level of systems. A machine learning expert trains and evaluates models. An AI developer builds applications around existing models, often a large language model from a vendor. A platform specialist configures one specific environment, such as an AI assistant inside your office software. Their output is working software. What an AI developer’s day-to-day work actually looks like is covered in a separate article on this site.

Both families are needed in a mature AI programme. The risk comes from hiring one when you need the other: a technically strong builder who’s also making the strategic calls, or a strategist from whom you expect a working system.

Which expertise do you need?

Start with the question on the table, not the job title. Four situations that come up often:

• You don’t yet know where AI adds value. Then you need strategic AI expertise: someone who maps opportunities, risks and conditions before any budget is committed.
• You need to choose between vendors or solutions. Also strategic, but with enough technical depth to see through demos and set up a test on your own data. How to weigh standard software against custom development is covered under choosing or building AI software.
• You know what you want and need build capacity. Then you need technical specialists: your own team, a development partner, or freelance developers. Examples of what can be built are on custom AI solutions.
• Initiatives are running with no owner. Then you’re looking for an AI lead to steer and keep oversight, possibly part-time.

If you’re weighing hiring against bringing someone onto permanent staff, the cost comparison matters too, though published salary benchmarks for this role are still thin and vary widely by region and seniority, so I haven’t included a figure here rather than guess at one. Practical criteria for selecting an outside advisor are covered on hiring an AI consultant.

My specialisations

I’m a freelance AI consultant, an AI specialist on the strategic side: an independent AI consultant who works alone. I don’t write code and I don’t sell software or implementations. That’s a deliberate choice: the moment I earn from the build, I have an incentive to grow the scope.

Where I am specialised:

• AI strategy and prioritisation. From scattered ideas to a portfolio with well-founded choices and a roadmap.
• Readiness. An assessment across strategy, data, technology, people and governance. The AI Readiness Assessment costs €7,000 and takes 2-3 weeks.
• Vendor selection. Criteria set upfront, the same scenario tested on your data, and a three-year TCO comparison. One example is the case study on vendor selection in enterprise retail.
• Assessment and due diligence. Assessing business cases and AI propositions for value, risk and feasibility.
• Governance. Roles, decision frameworks and the requirements of the AI Act, made workable.
• Guidance from the client side. As Fractional AI Lead, I help steer delivery by your own team or a development partner.

For the build itself, you work with your own team or with parties you contract directly. Where that helps, I introduce developers I know, with no margin on their rate; how that works is covered under the partner network. An overview of the whole development journey, from specification to upkeep, is on the AI development page.

Want to know which AI expertise your question actually needs? Book a thirty-minute consultation. If the answer is that you need a builder and not an advisor, you’ll hear that too.