What does an AI consultant do?

What is an AI consultant?

An AI consultant advises organisations on the choices around artificial intelligence: which problems AI solves and which it doesn't, what it costs, which risks are involved, and who's responsible for what. The core tasks are setting strategy, selecting use cases, guiding implementation and setting up governance. Writing code and training models usually isn't part of the role: that's the work of an AI developer.

An AI consultant is an adviser who helps organisations put artificial intelligence to meaningful use. So what does an AI consultant actually do? They translate what AI can do into choices for your organisation: which problems you solve with it, which you don’t, what it costs, which risks come with it, and who’s responsible for what.

The work sits mainly on the decision side. An AI consultant usually doesn’t write code or train models themselves. The value lies in overview, experience with similar questions, and the freedom to say what’s hard to say internally.

There are broadly two kinds of AI consultants: independent advisers, who only earn from advice, and consultants who are also an implementation partner or reseller for certain platforms. Both can do good work, but the difference determines how free the advice really is. I’m an independent AI consultant myself, and I don’t build or sell software. More on my background is on the about page.

Is every AI consultant independent of vendors?

That varies by AI consultant: there are broadly two kinds, namely independent advisers who only earn from advice, and consultants who are also an implementation partner or reseller for certain platforms. Both kinds can do good work, but the difference determines how free an AI consultant's advice really is.

What's the risk if one party is both the AI consultant and the AI developer?

It gets risky when one party plays both the AI consultant and the AI developer role and earns from the build. The advice then has an interest in a bigger scope.

When does an AI consultant pay off?

In short, an AI consultant pays off for decisions that are expensive or hard to reverse, in the case of an internal stalemate, when an investment needs to be justified, or when something happens for the first time under time pressure. There are also cases where an organisation is better off doing it themselves.

Source: article by Dave Willemstein. Updated: October 2026.

Tasks of an AI consultant

The tasks of an AI consultant broadly follow the lifecycle of an AI decision: from setting direction to making sure it actually works.

1. StrategyDecide what AI should contribute to the organisation's goals.
2. Selecting use casesNarrow a long list of ideas down to a short list with owners.
3. Guiding implementationChoose between building, buying or a partner, and oversee delivery.
4. GovernanceRules, roles and control, so AI stays safe and manageable.

Strategy

An AI consultant helps leadership decide what AI should deliver and where the limits are. That doesn’t start with technology, but with the organisation’s goals: where are the bottlenecks, what’s the ambition, and what’s realistic given the current data and people? The result is an AI strategy with explicit choices, including what you deliberately don’t do. Those choices are then translated into an AI roadmap with sequencing, planning and budget.

Selecting use cases

In many organisations there are more AI ideas than capacity. An AI consultant assesses them the same way each time: how much value does it deliver, is it feasible, is the data ready for it, how much change does it require, and is there someone in the business who wants to own it? The list gets shorter this way, not longer. Which types of use cases typically deliver results is a topic covered separately on this site.

Guiding implementation

After the choice comes delivery, and that’s where many initiatives stall. An AI consultant helps decide whether you build it yourself, buy it, or work with a partner. The consultant then guides delivery: selecting vendors, checking the business case against what’s actually being realised, and making sure management, ownership and adoption aren’t forgotten.

An important distinction: guiding isn’t the same as building. I guide implementations from the client’s side, while the building itself is done by the client’s own team or by a party the client contracts directly.

Governance

AI needs agreements: who’s allowed to use which tools, with which data, who reviews new applications, and who’s allowed to stop them? An AI consultant helps set up that governance, so risk stays manageable without every initiative getting stuck in procedure. That also includes translating regulation, such as the AI Act and data protection law, into concrete rules for your organisation. Keeping that light rather than heavy is a topic covered separately on this site.

What skills does a good AI consultant need?

Technical knowledge is a requirement, but rarely the deciding factor. The skills that matter in practice:

• Translating. Turning technical possibilities into consequences for cost, risk and working processes, in language leadership understands.
• Prioritising. Being willing to say which ideas don’t make the cut, and why.
• Critical review. Being able to see through a demo or vendor proposal: what’s demonstrably working, and what’s marketing?
• Knowledge of data and architecture. Enough to see whether an idea will stall on data quality or existing systems.
• Knowledge of regulation. Knowing what the AI Act and data protection law ask for, and when a lawyer is needed.
• Change management. Understanding that AI only delivers value once people actually work differently.
• Independence. Having no stake in a specific vendor or in a bigger scope.

AI consultant versus AI developer

The two roles are often confused, but they complement each other. An AI consultant decides what should happen and why. An AI developer builds it: models, integrations, connections to existing systems and the software around them, including testing and maintenance.

	AI consultant	AI developer
Core question	What do we do, why, and with whom?	How do we build it, and how do we make sure it works?
Output	Strategy, priorities, choices, governance	Working software, models and integrations
Works mainly with	Leadership, the business, IT, procurement, risk	Engineers, data, existing systems
Timing	Before and during delivery	During build and maintenance

A good project needs both. The consultant makes sure the developer is working on the right problem, with clear requirements and an owner in the organisation. The developer makes sure it actually works. It gets risky when one party plays both roles and earns from the build: then the advice has an interest in a bigger scope.

When should you bring in an AI consultant?

This article covers what an AI consultant does. The question of when you need one is a separate one. In short, it pays off for decisions that are expensive or hard to reverse, in the case of an internal stalemate, when you need to justify an investment, or when you’re doing something for the first time under time pressure. Those situations, and the cases where you’re better off doing it yourself, are covered in more detail on this site’s insights section.

Actively considering hiring someone? The AI consulting page covers the full range of guidance, from advice to ongoing direction, and what it costs. And if you’d like to talk through your own situation, book a thirty-minute call.