Palo Alto CEO Says AI Isn't Delivering Business Value Yet, But Security Vendors Are Racing to Prepare

Palo Alto Networks CEO Nikesh Arora has delivered a sobering assessment of enterprise AI adoption, suggesting that businesses are far behind consumers in implementing artificial intelligence technologies, with coding assistants being the notable exception.

During the company's Q2 earnings call, Arora painted a picture of limited enterprise AI deployment that contrasts sharply with the consumer enthusiasm for AI tools. "Consumers are far outstripping enterprise for the moment, but we expect enterprise will surely and slowly get on that bandwagon," he said, drawing parallels to the cloud computing transition that took two to three years before enterprises began migrating applications.

The CEO's assessment is particularly noteworthy because it comes from one of the world's largest cybersecurity vendors, giving him a unique vantage point on how organizations are actually using AI technologies. When asked about enterprise AI applications driving significant throughput, Arora was blunt: "I can't think of anything but coding apps."

This limited adoption poses an interesting challenge for Palo Alto Networks. While the company is positioning itself as a leader in AI security, the current lack of enterprise AI traffic means there's less demand for the security solutions they're developing. "Coding apps aren't great for Palo Alto's business because they don't generate a lot of network traffic to which it can apply its security smarts," Arora explained.

However, the CEO sees this as a temporary situation and believes his security vendor peers understand the landscape. "We're all laying the groundwork right now. It is sort of an arms race to try and see who can get the AI security sort of platform up and running as quickly as we can."

Despite the limited current adoption, Arora has observed some early signs of enterprise AI usage. "There is now enterprise adoption that we're beginning to see where customers are running perhaps millions of tokens in one or two particular applications they're working with some of the LLM providers on, and that's where we see the traffic," he noted. This traffic is primarily on local area networks, and Arora doesn't believe existing networks struggle to handle it.

The real challenge, according to the CEO, is consolidating AI traffic. "How do you get all the AI traffic to be in one place? So you can understand it, provide visibility, look at the ability to control it and be able to act on it."

As AI-related traffic grows, Arora predicts it will require "a different set of controls and tools." Palo Alto is already positioning itself to meet this future demand. The company recently acquired agentic AI endpoint security startup Koi, putting to bed rumors about the deal by announcing it's complete. Arora also pointed to recent acquisitions of Chronosphere and CyberArk as evidence of Palo Alto's strategy to build a comprehensive portfolio of products to secure the AI applications enterprises will eventually implement.

The CEO expressed confidence that Palo Alto has the products needed today, noting that customers understand they can't prepare for AI if they're running a tangle of security tools. This understanding is driving consolidation to the kind of integrated platforms Palo Alto offers.

Despite the cautious outlook on AI adoption, Palo Alto's business remains strong. The company reported $2.6 billion in Q2 revenue, representing 15 percent year-over-year growth. Subscription offerings continue to perform well, with 23 percent growth in remaining performance obligations, which now stand at $16 billion. The company predicts Q3 revenue will grow at least 28 percent to land between $2.941 billion and $2.945 billion.

However, investors appeared unimpressed by these strong numbers, knocking six percent off the company's share price. This reaction may reflect concerns about Arora's predictions that profits will ease, or perhaps skepticism about the timeline for meaningful enterprise AI adoption.

Arora's assessment provides a valuable reality check in an industry often characterized by AI hype. While many vendors are rushing to market AI-powered solutions, the actual enterprise adoption appears to be in its very early stages. This gap between vendor offerings and customer demand creates both challenges and opportunities for cybersecurity companies like Palo Alto Networks.

The CEO's comments also highlight an important distinction in the AI landscape: consumer AI tools like ChatGPT have achieved massive adoption, but enterprise implementations remain limited. This pattern mirrors earlier technology transitions, suggesting that while AI will eventually transform business operations, the process may take longer than some predictions suggest.

For security vendors, this creates a complex situation. They need to invest heavily in AI security capabilities to be ready when enterprise adoption accelerates, but they must also manage expectations and resources in a market where current demand for these solutions remains limited. Palo Alto's strategy of acquiring complementary technologies and building integrated platforms appears designed to position the company for this eventual shift while maintaining strong performance in its core security business.

As Arora noted, the current period represents an "arms race" among security vendors to establish AI security platforms. The company that can best anticipate and address the unique security challenges of enterprise AI deployment may gain a significant competitive advantage when adoption finally accelerates. Until then, vendors like Palo Alto Networks must balance preparation for the AI future with serving the immediate needs of customers who are still primarily focused on traditional security challenges.