From our community: What will clients pay management consultants for in the age of AI?

As AI makes analysis and routine work less expensive, clients expect to pay less for those tasks. At the same time, they will want more from the advice they pay for: clearer priorities, better decisions, and changes that deliver faster results.

This type of advice is difficult to create. In the consulting cases I design to train AI, two types of complexity come together:

• One is related to people, like company politics, conflicting goals and resistance to change.

• The other is data-related. This includes large amounts of (incomplete) data, complex spreadsheets, and vague statements that can be interpreted one way or another.

A strategy consultant’s recommendation needs to make sense of both people- and data-related information. For example, marketing might want more leads, sales wants higher-quality leads, and finance wants lower acquisition costs. Before suggesting more spending or a new tool, someone needs to get all teams to agree on what success means. Then, the real challenge is finding the limits that no one has mentioned, like a promise made to the board or what leaders are truly willing to change. AI can create an analysis quickly, but real answers come from conversations.

This challenge also appears when companies bring AI into their own operations. The technology is often easier to set up than making the organizational changes needed to derive real value from it.

Among my clients, AI adoption varies widely. Some teams generate campaign content; others use agents to draft business plans and investor pitches. In many organizations, employees are experimenting long before leadership has agreed how AI should be used.

I usually start off by mapping four perspectives: official use, unofficial use, leadership’s goals, and opportunities the business has not yet explored. Those gaps shape an action plan, whether the goal is to introduce a new target operating model or simply reduce costs. In my client work, AI has helped reallocate several million euros in marketing spend. In one medium-sized company, it also helped save tens of thousands of euros in a single month.

Turning time saved into financial value requires further decisions: what spending can be removed, where capacity should be redeployed, and which growth opportunities deserve investment.

Helping leadership make those choices — and following through — is increasingly where consultants earn their fee. As AI tools become more widely available, I expect clients to pay for three services in particular:

As AI produces more analysis, clients will expect even more from their advisors. Some consulting projects may become smaller or move in-house. Consultants will need to show how their work improves decisions or helps to take action.

Consulting leaders need to help develop the next generation of consultants. As AI takes over more research and first drafts, junior team members need real chances to build the judgment that clients will expect. This includes tracing claims to their sources, defending recommendations, and joining tough client conversations. They should also see what happens after decisions are made and new processes are implemented. Curiosity and practice matter, but experienced leaders must make time to coach juniors.

Building consulting cases to train AI has reinforced what I see with clients: a strategy, a recommendation or a target operating model has to work not only on paper, but also within the minds and hearts of the people who have to act on it.

Executives considering hiring management consultants should ask themselves: Which decision will this consulting project help us make? What will change in how we work? And how will we know if it made a difference?