For decades, technology consulting relied on a familiar economic model. A small number of senior people framed the problem. Larger teams of analysts, consultants and project managers did the work. The client paid for the combined effort.
AI is challenging that arrangement.
PwC is deploying AI agents across consulting workflows. Capgemini’s leadership has argued that AI will not eliminate consulting, while acknowledging that the way consulting is delivered is changing. Accenture, meanwhile, is reorganising parts of its business around integrated AI, cloud and cybersecurity initiatives.
The direction is clear, even if the eventual employment impact remains uncertain. Work that once required several layers of people can increasingly be completed by smaller teams supported by AI.
For European technology consultancies, however, the pressure comes from two directions.
The analytical pyramid is getting smaller
The traditional consulting pyramid depends on leverage. Senior consultants sell the work; junior consultants produce much of the analysis, documentation, research and project support.
AI changes the economics of that arrangement.
Research, first drafts, document reviews, code analysis and parts of requirements gathering can increasingly be automated or completed with fewer people. This does not mean that every task can be automated reliably, or that every junior role will disappear. It does mean that clients have a stronger reason to question how many people a project needs and what they are actually contributing.
The consequences extend beyond headcount. If a consultancy can deliver the same outcome with a smaller team, its pricing, utilisation targets, career paths and promotion criteria may all need to change.
A firm that continues to sell labour in a market increasingly paying for outcomes will find its economics under pressure.
Europe adds a second layer
European technology consulting has a complication that makes this transition particularly interesting: regulation.
The EU AI Act, DORA and NIS2 create substantial obligations for organisations within their respective scopes. They also increase demand for people who can interpret requirements, assess risks, redesign processes and implement controls.
That work is not automatically safe from automation. AI can assist with documentation, evidence collection, policy mapping and control testing. But accountability, judgement, implementation and the management of difficult trade-offs remain important.
The opportunity is therefore not simply to hire more compliance specialists. It is to find people who can connect regulatory obligations with technology, operating models and business execution.
That combination is harder to build than a team that can produce a convincing report.
Fewer people, different capabilities
The strategic mistake would be to treat this as a straightforward choice between reducing headcount and hiring AI specialists.
The more consequential question is which work still requires human judgement, which work can be automated, and which capabilities become more valuable when the two are combined.
For a consulting firm, that may mean fewer people producing analysis and more people capable of validating it, challenging assumptions, managing risk and turning recommendations into implemented change.
For a client, it means looking beyond the proposed team size. A smaller team may be more effective, but only if it has the experience and authority to make decisions, manage dependencies and deliver the result.
The distinction matters particularly in regulated environments. Generating a policy is one thing. Demonstrating that a control works, that responsibilities are clear and that the organisation can defend its decisions is another.
The talent question comes first
For CEOs, COOs and consulting leaders, the workforce question is no longer simply how many people to hire. It is how to assemble the capabilities required by a different delivery model.
Three questions deserve attention.
Which work should no longer be done manually? Identify the activities where AI can reduce effort without compromising quality, security or accountability.
Where does human judgement remain essential? Focus on people who can assess evidence, navigate ambiguity, make decisions and take responsibility for implementation.
Can the organisation find and develop those people? The required combination of technical understanding, commercial judgement and execution experience may not exist in sufficient numbers within the current team.
The answers have direct implications for recruitment, reskilling, organisation design and leadership succession.
The next consulting advantage
AI will not make technology consulting irrelevant. It will make the distinction between firms that sell effort and firms that deliver outcomes more difficult to ignore.
European regulation adds complexity, but complexity alone is not a competitive advantage. The advantage belongs to organisations that can translate it into sound decisions, effective controls and measurable operational change.
That requires a different balance of people, technology and accountability.
The firms that recognise this early will have a clearer view of the capabilities they need. Those that wait may discover that their traditional delivery model has become too expensive before they have built a credible alternative.
For companies hiring into technology, transformation or AI-related roles, the question is becoming more specific: what must this person make possible that technology alone cannot?
That is a better starting point than writing another job description.