Are AI Labs Becoming Consulting Firms?

Strategy consulting firms have historically competed mainly with each other. In 2026 they face three new groups of competitors: the AI labs whose models they resell, the tech scale-ups whose platforms they implement, and AI-native advisory firms built without a pyramid. In several cases, as our 2026 report finds, the incumbents' suppliers and partners are becoming their rivals.

Three new fronts at once

The large firms already earn part of their revenue from AI and have built in-house units for it, including McKinsey's QuantumBlack and BCG X. The new entrants are competing for that revenue. Our report sorts them into three groups: AI research labs launching consulting arms of their own, tech scale-ups that partner with consultancies while competing with them, and AI-native firms built to show that a leaner model works. Each group starts from a different position, and all three are moving towards the incumbents' ground.

The labs: OpenAI, Anthropic and Mistral move into deployment

OpenAI, Anthropic and Mistral now sell clients the same AI capabilities the strategy firms offer. The most visible step came in May 2026, when OpenAI launched the OpenAI Deployment Company, which helps mostly multinational clients deploy AI for operations and places engineers inside their organisations. McKinsey and Bain & Company are among its partners. The launch follows the Frontier Alliances programme that BCG and McKinsey joined to speed up enterprise rollout of agentic AI.^[1] Anthropic has launched a services company to help mid-sized firms deploy Claude.^[2]

“Letting the fox into the hen house.”^[3]

BCG takes a different view. Asked by The Wall Street Journal whether the labs threaten BCG, CEO Christoph Schweizer said demand for AI outstrips the capacity to meet it and described the labs' moves as complementary. In his account, BCG's work is redesigning workflows and reshaping whole companies rather than increasing token consumption.^[4]

Both readings can hold at once. The labs currently need the incumbents' client access and change-management capacity, and the incumbents need the labs' models, so the partnerships make sense for both sides. Each joint deployment also shows the lab what clients pay for and places its engineers in the client's organisation. In our reading, the labs are acquiring the one asset they lacked, client relationships, with the incumbents' help.

Tech scale-ups: Palantir and the forward-deployed engineer

Palantir formed partnerships with strategy firms including Bain in March 2026, a second route into the industry alongside the labs'.^[5] The mechanism is the forward-deployed engineer. Once a Palantir engineer has mapped a client's workflows and data, Palantir holds the relationship and can serve the client without the consultant. The consultant provides the introduction and the platform keeps the account.

AI-native consultancies: the 80/20 model

The third group is the AI-native consultancy. Queen's Tower Advisory runs an 80/20 model in which AI handles most of the analyst work, so the firm grows by adding agent capacity rather than headcount. Xavier AI builds AI consultants outright.^[6] Neither firm is large. Their significance is as evidence that a client deliverable can be produced without the junior base the incumbents were built on, a point developed in how AI is reshaping the consulting pyramid.

How the incumbents are responding

The established firms have built delivery units (BCG X has more than 3,000 employees and QuantumBlack more than 1,700), moved a large share of revenue into AI and technology work, and joined the labs' alliances rather than compete with them. The strain shows at the edges of the industry.

Accenture's share price fell a record 20% on 18 June 2026 after the company cut its full-year revenue growth guidance. Management attributed the cut to client pauses linked to geopolitical turbulence and said AI would not damage the business. IT budgets are being redirected towards acquisitions in new growth areas.^[7]

Supplier, partner, competitor: all of it on one chart

Our report places the players on two axes: depth of client relationship and ownership of the AI capability. The top-right quadrant, where a firm owns both, is the ground every group is moving towards.

What this means for established firms

The asset that is hardest to buy

A lab can hire engineers and fund a deployment company, and a scale-up can place engineers inside a client. Neither can quickly acquire what the incumbents have: trust, access, and the ability to make an organisation change how it works. Schweizer's argument about redesigning workflows is a sound defence if it holds in practice. An incumbent whose consultants cannot themselves use AI with judgment is reselling the lab's capability at a markup, and markups are competed away.

The chart suggests the response: move right faster than the labs move up. That means owning enough of the AI capability, in tools and above all in people, for the client relationship to rest on something the supplier cannot copy. It is a capability question before it is a partnership question, which is why AI fluency has become a commercial matter for consulting firms as well as an HR one.

This article expands chapter 1^[8] of The State of AI in Consulting 2026. The revenue these groups are competing for is covered in how AI is changing consulting business models and pricing.