Chamath Palihapitiya says consulting giants are helping OpenAI and Anthropic build the firms that may replace them.
Billionaire venture capitalist Chamath Palihapitiya issued a stark warning to the consulting industry on May 17, calling out PwC and Accenture by name for what he describes as a self-defeating AI strategy — one that he says hands OpenAI and Anthropic the keys to their own replacement.
If you are running a consulting business and you are deploying Anthropic or OpenAI directly into your organization (I’m looking at you PwC and Accenture) you are letting the fox into the hen house.
OpenAI and Anthropic are openly funding and starting competitors to you while… https://t.co/MYWEeSjnVD
— Chamath Palihapitiya (@chamath) May 17, 2026
“If you are running a consulting business and you are deploying Anthropic or OpenAI directly into your organization (I’m looking at you PwC and Accenture) you are letting the fox into the hen house,” Palihapitiya wrote on X. “OpenAI and Anthropic are openly funding and starting competitors to you while also using your usage to drive more success for them.”
The post came days after OpenAI officially launched the OpenAI Deployment Company, a subsidiary backed by over $4 billion from 19 institutional investors — including Goldman Sachs, TPG, Brookfield, Bain Capital, McKinsey & Company, SoftBank, and Capgemini — at a $10 billion pre-money valuation. Simultaneously, as crypto.news reported, Anthropic launched a competing enterprise services firm backed by $1.5 billion from Blackstone, Hellman & Friedman, and Goldman Sachs. Together, the two labs committed $5.5 billion to build out consulting and implementation capabilities that place them in direct competition with the firms currently deploying their models.
Token control via OpenAI and Anthropic as the new digital moats
Palihapitiya’s argument centers on what he frames as a structural vulnerability: consulting businesses that pipe client workflows directly through OpenAI or Anthropic models are allowing those same labs to learn from usage patterns, build out competing service arms, and ultimately displace the firms acting as middlemen. “This is not a failure on their part but a failure on your part,” he wrote.
His proposed alternative is a “control plane” that lets consulting firms arbitrate which tokens go where and which model provider generates them. “Controlling the tokens is controlling the spice,” Palihapitiya wrote, borrowing a reference from Dune. He cited his own software venture, 8090, as an example of this approach in practice, pointing to the company’s global partnership with EY, announced in March 2026. Under that deal, EY adopted 8090’s Software Factory platform to power EY.ai PDLC, an AI-native product development lifecycle tool projected to increase software development productivity by 70% and accelerate delivery by 80x, according to EY’s own figures. The platform is being rolled out to tens of thousands of EY US consultants. “We control token generation and can direct them to any model provider,” Palihapitiya wrote, adding that 8090 is “close to another global partnership” to be announced soon.
The stakes for legacy consulting
The competitive threat Palihapitiya describes is already materializing in revenue data. As crypto.news reported, Anthropic’s run-rate revenue hit $30 billion in early April 2026, tripling from $9 billion at year-end 2025, with over 1,000 enterprise customers each spending more than $1 million annually. OpenAI, meanwhile, crossed $25 billion in annualized revenue as of February 2026, as crypto.news covered, with enterprise revenue already accounting for over 40% of total income. Both labs are now acquiring engineering talent and building forward-deployed engineer teams modeled on Palantir’s playbook — embedding specialists directly inside client organizations, the very role that firms like Accenture and PwC have historically owned.
Palihapitiya closed with a pointed characterization of firms slow to adapt: “These organizations refuse to accept the disruption standing still or, even worse, by adopting and accelerating the companies who want to disrupt them.” For traditional consultancies navigating a rapidly shifting enterprise AI landscape, the warning signals that the window to build model-agnostic infrastructure — rather than simply reselling AI access — may be closing faster than many had anticipated.
