Model capability is doubling every 4–5 months. Who needs consulting when a well-engineered prompt and a Socratic dialogue with Claude or GPT gets you a rock solid TAM and a bullet proof implementation plan?
Everyone. Or at least, every leader concerned with what AI can do versus what the enterprise can absorb.
During an interview with Lex Fridman, Jensen Huang discussed the need for the architecture of a company to reflect the environment it exists in. 89% of enterprises still use a corporate structure designed in the industrial age. Most run 12 to 18 month planning cycles. AI model architectures are being invented every six months. That demands a fundamental shift in how enterprises operate if they’re going to survive the AI environment forming around them.
The frontier labs see this as a key friction point in their own growth cycle. OpenAI signed multi-year deals with McKinsey & Company, BCG, Accenture, and Capgemini. Called them “Frontier Alliances.” Anthropic invested $100 million in a consulting partner network and deployed Claude to all 470,000 Deloitte employees. OpenAI’s blog on the announcement: the bottleneck isn’t model intelligence. It’s how agents are built and run inside organizations.
Established leaders in tech have deployed embedded engineering teams directly inside customer accounts. Forward-deployed engineers. These teams accelerate adoption. They solve technical deployment problems on live systems, in real time. Palantir originated the model. Databricks, Anduril Industries, and several other industry leaders adopted variations as a core growth strategy. Now OpenAI, Anthropic, Salesforce, Adobe, and others are deploying their own FDE teams.
FDEs can solve for implementation and the adoption curve, but AI’s real value comes from somewhere else entirely. Role redesign when 40% of a team’s tasks shift to AI overnight. Incentive structures that reward adoption instead of penalizing experimentation. Workforce planning for jobs that didn’t exist six months ago. Cross-functional governance for systems that touch legal, compliance, HR, and operations simultaneously. Organizational rewiring is where the promise of value becomes tangible.
In 1926 James McKinsey wrote, “the theoretical man knows why, the practical man knows how, the man who would lead must know why and how.” Consulting had a monopoly on the theoretical. AI disrupted that. But the practical experience that makes transformation stick still lives in the minds of a limited number of people spread across a handful of organizations.
As the industry shifts from pure advisory to outcomes-based models, what we’re seeing is a return to McKinsey’s original ideal: the theoretical and the practical coming together to guide transformation.