Consulting sector faces AI pressure on pricing and client demand

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Consulting faces AI pressure

Highlights

Generative AI is reducing demand and pricing power for premium consulting services by automating basic analysis and presentation tasks previously billed by firms.
Consulting firms such as Accenture, McKinsey, BCG, and Bain are developing automated products and integrating AI into workflows to retain clients seeking lower-cost and higher-efficiency solutions.
Competition is intensifying in advanced consulting as AI labs like Anthropic and OpenAI target high-end implementation work, favoring firms with stronger engineering capabilities.

AI challenges the traditional consulting model

As reported by Financial Times, generative AI is beginning to erode part of the advantage that established consultancies have long held in selling tailored business advice, particularly as automated systems deliver plausible answers quickly and at lower cost.

That does not yet amount to a full replacement threat for human advisers. But it is creating pressure on a business model that has relied heavily on charging premium fees for analysis, presentation work and problem-solving that machines can now perform more easily at the simpler end of the market.

At Accenture's investor day this week, chief executive Julie Sweet argued that large IT-focused consultancies still have the scale and talent needed to help clients pursue their AI goals. Strategy firms including McKinsey, Boston Consulting Group and Bain are also positioning themselves as guides for companies seeking road maps for AI adoption.

Even so, the economics are becoming less comfortable for incumbent firms. Lower-value mandates once supported more difficult assignments, but companies are increasingly bringing basic tasks inside the business and assigning them to AI tools, raising pressure for consultants to justify fees through outcomes rather than hours billed.

Firms adapt as clients seek new value

The sector is already responding by building cheaper automated products that clients can buy off the shelf and by adopting AI more aggressively in its own workflows. Consultancies are also emphasizing the efficiency gains the technology can offer, while trying to preserve their role in more complex deployment and transformation work.

That higher-end segment may become more contested as AI labs and talent-heavy groups such as Anthropic and OpenAI also pursue consulting opportunities around advanced implementation. In that environment, firms with strong engineering capabilities may be better placed to defend market share than those relying mainly on presentation and strategic framing.

Consultancies have historically adapted to major technology shifts, from the internet and digitization to Big Data and cloud computing. The latest transition suggests companies may still pay for advice, reassurance and technical support, but firms now need to prove more clearly which parts of that value must still come from people rather than software.

In our earlier article on how AI is raising the cost of standing still for businesses, we explained that rapid adoption is pushing up competitive standards and making “average” performance less sustainable. We also noted that staying competitive increasingly requires rethinking investment priorities, workforce skills, and decision-making, as companies that use AI for productivity and automation can strengthen their market position while laggards risk irrelevance.

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