Summary: Consulting is being forced to move beyond advice into execution, with firms like BCG stepping directly into operational roles. This shift is redefining value, compressing traditional models, and exposing which firms can truly deliver outcomes at scale.
BCG’s move into interim management is not a product extension. It is a structural signal about where the industry is heading.
For decades, consulting operated on a clear division of labour. Firms were responsible for defining the strategy, structuring the problem, and presenting a path forward. Clients, in turn, carried the burden of execution, absorbing the risk that came with turning recommendations into results. That model held because execution was difficult to observe, slow to measure, and often fragmented across organisations.
That separation is now breaking down under pressure from multiple directions.
AI is accelerating the production of analysis and reducing the cost of generating “consulting-grade” outputs. Clients are more informed, better equipped, and less willing to pay for process-heavy work. At the same time, private equity and corporate leaders are operating under tighter timelines, where value creation is expected in months rather than years. In that environment, advice without accountability is becoming harder to justify.
This is not a decline in demand for consulting. It is a redefinition of what clients are willing to pay for.
Strategy is collapsing into execution
BCG’s move into interim management reflects this shift in a very direct way. The firm is not simply placing executives into client organisations. It is deploying experienced operators alongside teams, supported by AI capability, with a mandate tied explicitly to value delivery and cash impact.
That changes the nature of the engagement.
The firm is no longer influencing decisions from the outside. It is stepping inside the organisation and taking partial control of outcomes. This is particularly relevant in environments where execution risk is the central issue, not strategic clarity.
Across the market, the work that is growing tends to share similar characteristics. It is less about defining direction and more about ensuring delivery. Transformations are judged on whether they land, cost programmes on whether they show up in EBITDA, and AI initiatives on whether they are embedded into real workflows rather than presented in conceptual roadmaps.
In that context, the client question has shifted. It is no longer simply “what should we do?” but increasingly “who is going to make this happen, and how quickly can it be done?”
Consulting firms are starting to position themselves as the answer to that second question, but doing so requires a different level of credibility.
The competition set is being rewritten
As consulting firms move closer to execution, their competitive landscape changes.
BCG’s move places it in direct competition with interim management providers, restructuring firms, and turnaround specialists. These are organisations that have built their reputations not on the quality of their thinking, but on their ability to deliver outcomes under pressure. Firms such as Alvarez & Marsal, AlixPartners, and FTI have long operated in this space, often stepping into leadership roles within client organisations during periods of stress or transition.
Historically, consulting firms operated alongside these players, often defining the strategy while others executed it. That distinction is becoming less clear.
Clients, particularly in private equity environments, are less interested in dividing responsibility across multiple providers. They are looking for fewer partners with clearer accountability. This creates a more direct comparison between firms, not just in terms of intellectual capability, but in terms of operational credibility.
It also reinforces a broader point about where value sits.
AI can replicate elements of consulting output, from analysis to presentation. What it cannot replicate is the ability to make decisions in uncertain environments, align stakeholders with competing interests, and take responsibility for the consequences of those decisions. That combination of judgment, trust, and experience is becoming more visible as the core product.
AI is accelerating the shift
The role of AI in this shift is often misunderstood.
AI is not removing the need for consulting. It is changing the nature of the work and the distribution of value within it. Tasks that once required significant time and team capacity, such as data analysis, benchmarking, and deck production, are being automated or heavily augmented. As a result, the barrier to producing structured, “consulting-style” outputs has dropped significantly.
When production becomes easier, its value declines.
This pattern has played out across multiple industries. As manufacturing became more efficient, value moved to design and distribution. As information became more accessible, value shifted to interpretation and decision-making. Consulting is now experiencing a similar transition.
The implication is not a simple reduction in headcount, but a reshaping of team structures. The traditional pyramid, built on layers of junior consultants supporting a smaller group of senior leaders, is under pressure. In its place, a model of smaller, more experienced teams is emerging, supported by AI rather than large numbers of analysts.
This reinforces the move toward execution. If fewer people are involved, and those people are more senior, the expectation naturally shifts toward ownership of outcomes rather than contribution to outputs.
The operating model tension
Despite the logic of this shift, it introduces significant tension into the consulting model.
Interim management is not just another service line that can be added without consequence. It operates with different economic assumptions, relies on a different talent base, and carries a different level of risk. Revenue is often more directly linked to outcomes, variability is higher, and delivery risk sits closer to the firm itself rather than being transferred to the client.
This challenges the traditional consulting model, which has been built around scalability, repeatability, and relatively controlled delivery environments.
There is also a cultural dimension to consider.
Advisors are trained to analyse, structure, and recommend. Operators are required to make decisions, often with incomplete information, and accept responsibility for the results. Integrating these two mindsets within a single organisation is not straightforward. It requires changes not only in capability, but in how success and risk are defined internally.
The question is not whether consulting firms can move into this space. It is whether they can do so at scale without fundamentally reshaping how they operate.
Talent becomes the constraint
One of the clearest implications of this shift is in talent.
The market is increasingly rewarding individuals who can operate across both strategy and execution. This includes the ability to frame complex problems, but also the experience to deliver in real operating environments. These profiles are relatively scarce and do not align neatly with the traditional consulting career path.
At the same time, the role of junior talent is evolving.
If AI reduces the need for large teams to perform analytical tasks, the traditional apprenticeship model is compressed. Fewer people are exposed to the early stages of problem solving, and fewer opportunities exist to develop judgment through repetition. This creates a longer-term challenge for firms in building the next generation of senior leaders.
In this sense, AI is not just changing delivery. It is reshaping how capability is developed over time.
Clients are changing how they buy
Client expectations are evolving in parallel.
Particularly in private equity and high-pressure transformation environments, the emphasis is shifting toward speed, clarity, and accountability. Clients are looking for partners who can move quickly, take ownership, and demonstrate tangible impact within defined timeframes.
This reduces tolerance for large, multi-layered teams and extended project cycles.
Instead, there is a preference for smaller, more senior teams that can engage directly with decision-makers and drive execution. AI supports this model by reducing the need for manual production work, allowing experienced individuals to operate more efficiently.
However, this also raises expectations.
If a firm positions itself as owning the outcome, it must be prepared to deliver under scrutiny. The margin for error becomes smaller, and the consequences of failure more visible.
The deeper shift
At its core, this shift is not about interim management.
It is about the erosion of a long-standing assumption within consulting: that defining the answer is sufficient.
That assumption is no longer holding.
AI might change the game, but it does not replace the core of consulting. It exposes it. The real value has always been in judgment, trust, problem framing, and the ability to guide organisations through complex decisions. What is changing is where that value is applied.
It is moving closer to execution, closer to risk, and closer to measurable outcomes.
This raises a more fundamental question for the industry.
If consulting firms are expected to design strategy, execute it, and be accountable for results, then the distinction between advisor and operator becomes increasingly blurred.
The direction is clear.
What remains uncertain is how many firms are structurally prepared to operate in this new model, and how many are signalling the shift without fully committing to the implications.
Ben Appleton is the founder of Strat-Bridge, a specialist executive search partner to the strategy 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.
