The recent DeepSeek selloff has disrupted the AI investment landscape, sparking concerns among investors and industry leaders alike. While some view it as a sign of instability, early-stage startups could see this moment as an opportunity. DeepSeek’s emergence as a fast follower in AI demonstrates how quickly barriers to entry in the industry are shrinking, making room for new players to innovate without the massive capital expenditures once thought to be necessary.
Erin Martell, venture director at TechNexus, sees this shift as a pivotal moment for startups. “DeepSeek is demonstrating the ability to be a fast follower in the market,” she said. “They've been able to capitalize on existing infrastructure, and now we just have to make sure market timing doesn’t overly favor DeepSeek versus OpenAI, which obviously has better brand recognition. But fundamentally, this is a move toward commoditization.”
This commoditization—where once-exclusive AI capabilities become cheaper and more widely available—creates an atmosphere where startups can compete without the deep pockets of major tech giants.
“Previously, these AI models were so capital-intensive, but now they can be developed at a much lower cost,” Martell (pictured) notes. “The barrier to entry is simply lower.” This means startups can now bring innovative AI solutions to market faster and more affordable than ever before.
An Opportunity for Investors and Founders
For investors, the DeepSeek selloff is a lesson in the evolving nature of competitive moats. The assumption that OpenAI’s advantage was locked in by the high costs of model training—fueled by Nvidia’s specialized chips—was challenged by DeepSeek’s ability to replicate high-performance AI without those resources.
“Investors underestimated how, as the technology evolved, the upfront cost of training a model would decrease significantly,” Martell said. “This was an inevitability with a first-to-market technology.”
As AI becomes more accessible, demand for related industries—including energy, AI safety and regulatory compliance—will only grow. “This shift in costs will create increased consumer demand,” Martell said. The lower the cost of AI, the more industries will adopt and integrate it, creating new opportunities for startups that focus on infrastructure, security and real-world applications of AI models.
How Established Companies Should Respond
For later-stage AI companies that have raised billions, DeepSeek’s breakthrough raises a critical question: What happens when proof emerges that massive capital investments aren’t necessary for competitive AI development? Martell suggests these firms must double down on their brand, channel partnerships and infrastructure investments.
“They still have brand recognition and partnerships in place,” she said. “If training costs come down, great—now how do they mature into more integrated companies?”
One solution Martell pointed to is horizontal integration—expanding ownership across the AI ecosystem. This includes data centers, server efficiency and reasoning infrastructure.
“If DeepSeek is showing that you can train on less sophisticated chips, that’s a benefit to the U.S.-based AI companies, too,” she said. “They’ll learn from it and gain cost efficiencies.”
A Strategic Shift in the AI Race
Martell also raises the possibility that DeepSeek’s cost-cutting claims may be exaggerated. “I think China is exaggerating how cost-efficient they are,” she said. “They’re leveraging existing Western infrastructure, as any fast follower would, but the reality is that it still costs a lot to train these models.” Regardless, the lesson remains the same: AI development is no longer reserved for companies with billion-dollar war chests.
For early-stage startups, the DeepSeek selloff should not be a deterrent—it should be a call to action. With lower barriers to entry and a rapidly expanding AI market, now is the time to innovate. Entrepreneurs who recognize this moment as an opportunity, rather than a setback, will be best positioned to build the next wave of AI-driven solutions.