Google Just Spent $750M to Settle the “AI Will Kill Consulting” Debate
For a year, every AI thread has circled the same prediction: agents will hollow out consulting. McKinsey is the next Blockbuster. Pick your metaphor.
Last week, Google ended the argument with a checkbook.
At Cloud Next ‘26, Google announced a $750 million fund to help consulting firms: McKinsey, Accenture, Deloitte, BCG, Bain, PwC, Capgemini, TCS roll out agentic AI to their clients. Largest single partner investment ever from a hyperscaler. And it lands in the middle of a wave:
McKinsey launched a joint working group with Google the same week.
OpenAI formed “Frontier Alliances” with McKinsey, BCG, and Accenture in February and is selling Codex through Accenture, Capgemini, and PwC.
Anthropic put $100M into its Claude Partner Network and another $200M into a PE vehicle to embed Claude in portfolio companies.
Microsoft announced its own partner initiative the day before Google’s.
If AI were killing consulting, none of this would be happening. The labs would go direct. They’re not. They’re paying consultants to be the front door.
AI is not replacing consulting. It’s merging with it.
The raw models coming out of frontier labs are not enterprise-ready. Someone has to connect them to actual data, build the guardrails, design the rollout, fit them into how teams already work.
The model doesn’t know your industry. Doesn’t understand your compliance constraints.
Consultants do. That’s the gap. And the economics show how big it is: for every $1 a customer spends on Google Cloud, partners capture up to $7.05 in services revenue. The cloud is the loss leader. The services around it are the business.
The numbers inside the firms back it up. McKinsey says roughly 40% of its work is now GenAI-related. BCG was at 20% in 2024 and climbing. Deloitte calls its Google commitment its largest AI investment ever - 1,000+ pre-built agents, Gemini rolling out to 100,000 of its own people. Accenture has built 450+ agents on Google Cloud and is a lead partner for Google, OpenAI, and Microsoft simultaneously.
Deal cadence has compressed too. Lab–consultant partnerships used to form when the startup hit ~$10M in revenue, 2-4 years in. Now they’re happening at $2-5M, 12-18 months in. Everyone’s racing to lock in distribution.
The market didn’t die. It compressed and reshaped.
What’s dying vs. what’s growing
Classic consulting work: research, slides, process maps, the 200-page deck nobody reads is exactly what AI is automating. Anyone whose value prop is “I synthesize 40 interviews into a PowerPoint” should be reading the room.
What’s growing is the layer above it: identifying the right business problem, packaging the AI stack into something that works in production, and taking responsibility for the outcome. That last one is the quiet moat. Frontier labs do not want to be on the hook for enterprise outcomes. Consultants have been on the hook for sixty years. It’s literally the business.
This is why McKinsey is hiring engineers, not just MBAs. The skill stack changed. The brand and client access didn’t.
The playbook
If you’re a consultant. Stop bragging about “using AI.” Anyone can use AI. Get fluent in the engineering layer - agents, evals, integrations, monitoring or get out of the delivery seat. Pick one industry vertical and one platform (Gemini, OpenAI, Claude) and go deep enough that you can architect a production system, not just a pilot. Generalists are about to get crushed.
If you’re a founder selling AI to the enterprise. Stop trying to sell directly. Consultants own the relationship, the trust, and the outcome accountability, your fastest path to revenue is being the picks-and-shovels layer under someone else’s services contract. The compressed deal timelines mean there’s a real window open right now. It will close.
If you’re an enterprise buyer. Be skeptical of any partner whose only answer is “we’ll plug in the model.” The model is the easy part. Three questions to ask before you sign: Who owns the production system in year two? Who maintains the eval suite when the model gets updated? Who pays when it breaks? If you can’t get a clear answer to all three, you’re buying a pilot, not a system.
The takeaway
The “AI will kill consulting” narrative was always too clean. What’s actually happening is messier and more interesting: the labs need a distribution layer, the enterprises need an integration layer, and the consultants who have been quietly building both for decades just got handed $750M to accelerate.
The moat is getting deeper.
You just have to know where to look.