AI Creates Consulting’s Next Reinvention

Summary: AI is generating significant demand for strategy consulting, but it is also compressing the analytical work that supports the traditional consulting pyramid. The coming consulting reinvention will demand smaller expert teams, stronger internal capabilities and senior leaders who can connect technology, commercial priorities and implementation.

AI is creating a consulting boom around the very technology that will eventually force consulting firms to redesign themselves.

That tension is visible in Bain’s German market commentary, where Christina Ellringmann, Managing Partner for Germany and Austria, argues that “a patchwork of AI solutions creates no value.”

Bain research found that 80% of senior executives were dissatisfied with the speed of AI transformation. Only one in five had largely or fully achieved their goals.

Companies are not short of tools or ambition. They are short of the operating model needed to create measurable value. That creates a sizeable opportunity for strategy firms, but also a question: if AI changes how clients operate, why would consulting remain untouched?

The AI boom is funding consulting reinvention, and the firms selling the change will be changed by it first.

The Problem Is Organisational

The first phase of corporate AI adoption was defined by access. Employees received assistants, functions launched pilots and leadership teams asked every unit to identify use cases. The result was activity without equivalent transformation.

The pattern is well documented. McKinsey’s research on agentic AI found that while nearly 80% of companies now use generative AI, more than 80% report no material impact on earnings, and fewer than 10% of use cases ever make it past the pilot stage.

A portfolio of disconnected pilots rarely changes business economics. One team automates documents, another experiments with customer service and a third builds a knowledge tool. Each may demonstrate potential, yet the organisation around them remains unchanged.

Pilots Are Not Transformation

The missing elements are shared infrastructure, clear accountability and a way to scale successful ideas. Companies also need leaders who can decide which workflows to redesign, what should remain human-led and where investment can produce a defensible return.

The cost of skipping those questions is now measurable. Bain’s analysis of AI budgets and returns found that nearly 40% of companies targeting cost reductions of 11 to 20% landed below 10%. Nine in ten still plan to increase AI spending again.

This is not primarily a technology decision. It is a management decision with technology inside it. Treating AI as a collection of tools avoids harder questions about ownership, incentives and organisational change.

Capability Must Return In-House

The capability problem runs deeper. Two decades of outsourcing and offshoring reduced costs and provided specialist resources, but often weakened internal software knowledge. Many organisations also lost the ability to learn through building.

Agentic AI exposes that dependency because it cannot simply be installed like conventional software. Agents interact with data, decisions, controls and other systems, requiring supervision and refinement. The same Bain analysis found that only 7% of companies run fully autonomous agents in production today; supervision is the norm, not the exception.

Organisations must understand how agents work, where they fail and who owns each outcome. External support can accelerate the journey, but cannot replace institutional understanding. Buying more technology cannot compensate indefinitely for capability the business no longer owns.

Consulting Reinvention Meets the Pyramid

This environment is good for consulting demand. Leaders face pressure to act, boards want progress and few teams want to discover that competitors moved faster. Strategy firms can offer prioritisation, perspective and experience from multiple transformations.

Bain’s German-speaking business has reportedly been growing at double-digit rates, at a moment when Germany’s consulting market is rewiring. The firm employs around 1,500 consultants across the region and plans another “significant three-figure” intake of young consultants this year, 25% more than last year. Ellringmann says she still believes in the pyramid model.

That confidence matters because AI challenges the work on which the pyramid depends. Consulting firms have traditionally combined a few senior advisers with larger teams of junior consultants. Those teams conduct analysis, build models and prepare presentations while developing future managers and Partners.

AI does not remove the need for analysis, but it compresses the time and headcount required. Research can be accelerated, first drafts produced instantly and large datasets interrogated with less manual effort. In due diligence, AI can surface patterns and test hypotheses at a speed that once required a sizeable team.

Apprenticeship Must Evolve

The public commitment to the pyramid therefore sits beside a quieter debate. In my conversations with Partners across the strategy consulting market, smaller teams, greater specialist leverage and different development paths for junior consultants are recurring themes.

The question is not whether firms will keep hiring graduates. It is what those graduates will do, how they will learn and how many layers the future model can support. AI is not ending the profession, but it is killing the old hiring model: a career path built around producing analysis becomes harder to defend when machines perform more of that work.

This is not an argument for removing junior consultants. Firms still need to develop judgement, commercial confidence and future client leaders, but apprenticeship must evolve. It cannot depend on years producing work AI can now complete in minutes.

The pyramid may survive as a talent philosophy while changing as an economic model. Firms still need future leaders, but fewer people may be required at each level. Teams around Partners are likely to become smaller, more specialised and more fluid.

Value Moves Upward

As analysis becomes faster and cheaper, value moves towards work that is harder to automate: the shift from leverage to judgement. This includes framing the right problem, deciding under uncertainty, navigating organisational politics and taking responsibility for implementation.

That changes what clients will buy. Faster production will not command the same premium when every credible firm has similar technology. Clients will also question large teams simply because complex work once required them.

The premium will increasingly sit with judgement, orchestration and measurable outcomes. It is why senior consultants become more valuable, not less. Expertise still matters, but how it is applied matters more. Knowing the answer creates limited value if a firm cannot mobilise the client to act.

A New Partner Profile for Consulting Reinvention

Talent strategy must change accordingly. Firms can recruit data scientists, engineers and product designers, but technical specialists alone will not close the gap between experimentation and value. Technology expertise must combine with commercial judgement, sector knowledge and implementation credibility.

The scarcer profile is the senior leader who connects those elements. They can identify where AI changes process economics, assemble technical and industry expertise, challenge executives and make implementation happen. It is the same force reshaping consulting’s partnership model itself.

That requires more than adding an AI specialist to an unchanged Partner team. Firms must reconsider whom they hire, how they promote them and what they reward. Commercial contribution must include capability building and delivered outcomes, not just origination.

The Commercial Model Must Follow

A Partner selling disconnected experiments may generate revenue while reproducing the client’s problem. One who helps the client choose fewer priorities, redesign workflows and build internal capability may create more lasting value. That may require a different shape of engagement.

The commercial model must follow. When AI reduces delivery effort, maintaining traditional fees through leverage becomes harder to defend. To see where firms really stand, watch how firms get paid, not what they say about AI. Pricing will need to move towards outcomes, proprietary insight, implementation risk and senior judgement.

The window for gradual change is closing. Bain’s own outlook for AI in 2026 notes that boards now expect AI investment to show up in bottom-line results, and that roughly two-thirds of the barriers sit in data, process and change management rather than the technology itself.

None of this means AI will end strategy consulting. Large investments, uncertain markets and high-stakes transformations will continue to create demand for trusted advice. A private equity investor making a billion-dollar decision will not delegate judgement to a model because analysis arrives faster.

Trust is not a licence to preserve the existing model. The immediate AI opportunity may let firms postpone difficult choices because demand is growing and new services are selling. Those treating AI as another topic inside the current pyramid will miss the larger shift.

AI transformation will expose whether consulting firms can apply their own advice. They must focus on value, redesign workflows, build the right capabilities and change their operating models.

The winners will not be the firms with the most AI projects. They will be the firms prepared to become different businesses because of them.

The winners will not be the firms with the most AI projects. They will be the firms prepared to become different businesses because of them.Ben Appleton, Strat-Bridge

In Conclusion: The Consulting Reinvention Test

Consulting firms are telling clients that AI requires more than adoption; it requires redesign. The same test now applies to them, and it will decide what was worth keeping once the dust settles.

The winners of consulting reinvention will not be those that sell the most AI work, but those willing to redesign the model that made them successful before the market does it for them.

Ben Appleton

Ben Appleton is the founder of Strat-Bridge, a specialist executive search partner to the management consulting industry. He works with global consulting firms and senior leaders across the UK, Germany, Switzerland, and beyond — helping them build capability at the Partner and Director level.

Connect with Ben on LinkedIn or email ben@strat-bridge.com.