As companies race to implement artificial intelligence, concerns are growing among business customers. Could the very AI companies that companies rely on end up becoming competitors? The question came to light at Lion Forum, a venture capital conference in Massachusetts, where Anthropic’s head of healthcare, Syed Mohiuddin, was asked a question many executives are increasingly considering.
“Why should we trust you not to steal our business?” wondered the Semaphore news agency, whose correspondents were present at the event. report.
“That’s a fair question,” Mohiuddin replied. “Because we are both a frontier lab that builds models and a product company that delivers applications.”
The exchange reflects growing anxiety about the dual roles played by major AI developers. Companies like Anthropic, OpenAI, and Google DeepMind not only build the underlying AI models used by companies across industries, but they are also increasingly developing software products that can compete with existing enterprise services.
But concerns extend beyond software. Many AI companies have engineers working directly with customers to help them integrate models into business operations. Critics argue that while these teams are intended for technical support, they inevitably gain detailed knowledge of how banks, manufacturers, consulting firms, retailers and other businesses operate.
The issue was also raised by Palantir CEO Alex Karp during the meeting. Recent CNBC interviewsThere, he explained the frustration among business leaders over the direction of the industry.
“These people are furious,” Karp said. “They’re saying, ‘I’m paying for a token that doesn’t create any value, and they’re going to get my IP.'”
Concerns are growing as Frontier AI Labs expands beyond providing basic models to developing specialized applications.
Anthropic has already introduced products aimed at legal and design professionals, markets traditionally served by dedicated software providers. This raises broader questions about what will happen when AI companies eventually move beyond software tools and provide the underlying professional services themselves.
According to Semafor’s analysis, one factor that could limit that expansion is the rapid rise of open source AI models.
Many of these models, including some developed in China and emerging alternatives in the US such as Reflection, are closing the performance gap with proprietary systems while allowing companies to run AI locally without sending sensitive data to external providers.
For companies handling valuable intellectual property, that distinction is becoming increasingly important.
“They have to use AI Labs’ products to stay competitive, but to do that they have to send all their IP. That’s a very unpleasant thing to do to someone who might be trying to replace you,” Wilson, CEO of software testing startup Antithesis, told Semaphore.
Anthropic rejected the idea that its purpose was to replace its technology-based businesses.
“Claude Code didn’t kill Replit and Cursor,” Mohiuddin said last month, referring to Anthropic’s growing AI-assisted coding platform along with its own developer tools.
“We’re not trying to be a kingmaker or a market heir. What we’re trying to do is raise the bar on what’s possible.”
Whether that balance can be maintained remains an open question.
As Semafor pointed out, the central question is not simply whether AI labs have the technical capabilities to compete directly with customers, but whether doing so will ultimately prove more profitable than providing the technology that enables customers to succeed.
The answer could shape the future relationship between AI developers and companies that increasingly rely on their models.
Nazrin Sadigova
