Companies have long worried about artificial intelligence exposing sensitive data. Palantir Technologies Inc. (NASDAQ:PLTR) CEO Alex Karp says they’re focused on the wrong threat.
Speaking at the G20 Innovation Ministerial, Karp argued that the real strategic risk isn’t losing data — it’s unintentionally giving away the proprietary knowledge, workflows and decision-making that create a company’s competitive advantage, or what he called its “alpha.”
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The ‘Alpha’ Problem
Karp’s warning wasn’t about cyberattacks or data breaches. Instead, it centered on how enterprises deploy large language models inside their organizations.
“Those companies are exfiltrating — not intentionally — your alpha to the company that provides the model,” Karp said, referring to companies that deploy AI without the right architecture.
He argued that the problem goes beyond privacy or compliance. If businesses feed proprietary processes into generic AI systems, they risk exposing the very know-how that differentiates them from competitors.
“This isn’t sovereignty. This is anti-sovereignty,” Karp added.
To illustrate the point, Karp used the example of a French nuclear reactor manufacturer. The company may want AI to optimize its supply chain, identify alternative suppliers and model disruptions, but not at the cost of revealing decades of manufacturing expertise or operational processes to an external model provider.
Palantir’s Application Layer
Karp framed the issue as a missing layer in today’s AI stack.
After acknowledging NVIDIA Corp (NASDAQ:NVDA) CEO Jensen Huang as “the world’s expert” on compute and describing the role of frontier AI models, Karp argued that models alone are insufficient for enterprise and government use.
“These models without an application layer will give you an answer,” he said, “but that answer… is not 100% accurate.”
More importantly, he argued that organizations need software capable of controlling how proprietary data interacts with AI models, ensuring it can be audited, secured and adapted without exposing sensitive knowledge.
“We are the application layer,” Karp said. “We will put our ontology in the middle and allow you to train these models so that you can control them and there’s no exfiltration.”
While Karp was describing Palantir’s own platform, he made a broader point: “Whether you use our product or not, you will need this to make these things work and make them secure.”
Why It Matters
Karp’s remarks offer one way to think about the evolving AI investment landscape.
Much of the market’s attention has focused on companies building chips and frontier models. Palantir’s thesis is that as AI adoption matures, value could increasingly shift toward the software layer that governs how organizations deploy models, protect proprietary knowledge and integrate AI into real-world operations.
Whether investors agree with that view or not, Karp’s comments highlight a debate that is likely to become more important as enterprises move from experimenting with AI to embedding it into mission-critical workflows.
Photo: PJ McDonnell / Shutterstock
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