Google picks licensing over consulting: a new strategy in the fight for the enterprise

Google is writing licensing agreements with private investors, while OpenAI and Anthropic build their own consulting units. The difference in approach may determine who takes the lead in what is arguably the most important new distribution channel for enterprise AI, and the first this significant since the arrival of cloud computing.

Three strategies in the fight for the enterprise

OpenAI and Anthropic are investing in classic consulting. OpenAI has created a multibillion-dollar unit valued at $10 billion. Anthropic is following a similar path with an investment of $1.5 billion. Both companies hire consultants, open offices, and prepare diagnostics and customization for each client.

It is a proven approach: McKinsey, BCG and Deloitte show that consulting works. But it is resource-intensive. Every new client requires people, time and deep knowledge of its business processes.

Google chose something entirely different. Instead of building its own consulting firm, the company signs licensing agreements directly with private investors such as Blackstone and KKR. These funds manage huge portfolios: hundreds of companies of different sizes, industries and geographies. When Google licenses its models to such a fund, it gains access not to a single company but to the entire portfolio at once.

Why licensing scales better

Consulting requires scaling headcount linearly. Every new client task needs an expert who understands both the architecture of Google Gemini and the client's operations. If a consulting firm has to work with a thousand companies, it needs a thousand consultants. Add training, quality control and staff turnover.

Hiring qualified consultants, training them continuously and managing quality all grow nonlinearly in cost. That is why even large consulting firms grow more slowly than SaaS companies. They are limited by the number of talented people on the market and the time it takes to train them.

A license scales very differently. One contract, one integration, and the partner's entire infrastructure gets access to Google's models. There is practically no limit on the number of users. An investor can distribute the license among hundreds or thousands of portfolio companies without further negotiations.

Portfolio companies as a new distribution channel

The main advantage of Google's approach is not the contract value but the breadth of reach and the speed of access. The portfolio companies of private investors are not only Fortune 500 firms, but also:

• Startups in AI, SaaS and fintech
• Manufacturers and logistics firms
• Companies in healthcare and retail
• Energy and infrastructure projects

Each of them needs AI, but does not want to negotiate with Google on its own, sign a separate contract, train specialists and integrate the API. When Blackstone or KKR license Google's models, they become an internal distributor. The fund offers AI to its portfolio companies as a tool for improving operational efficiency. A portfolio company does not pay Google directly: it pays the investor, or receives the tool as part of a support program.

For investors, this adds value to every investment. For Google, it means access to thousands of companies without launching its own consulting arm. In effect, Google is using private capital as its distribution infrastructure.

What this means

Cloud computing went from a technology to a service to a software distribution channel. AI is following a similar route. The difference is that the cloud was distributed through corporate IT departments and consultants, while AI can be distributed through financial partners and portfolios.

The company that first builds strong relationships with the largest investors and secures licensing contracts will gain access to tens of thousands of companies at once. The result: not a consulting firm, but an infrastructure company that manages access to AI through capital.