Palo Alto Networks CEO Nikesh Arora has pushed back against calls for the artificial intelligence industry to slow the development of increasingly capable models, arguing that efforts to collectively pace AI progress are unlikely to work when companies have different incentives and approaches to safety.
“I think not everybody is going to pace themselves,” Arora told CNBC’s “The Tech Download” podcast, recorded Tuesday.
His comments add another prominent technology executive to an increasingly divided debate over whether the rapid development of frontier AI systems should be deliberately slowed to address potential safety risks.
The debate intensified after an Anthropic researcher estimated that there was a 10% chance AI could “kill all humans.” Another researcher subsequently left the company, warning that Anthropic and OpenAI were not acting responsibly enough in the race to develop increasingly powerful systems.
Anthropic CEO Dario Amodei later called for the industry to “slow the pace at which we improve the capabilities of AI models.” OpenAI CEO Sam Altman, SpaceX CEO Elon Musk and Google DeepMind Chair Demis Hassabis have expressed support for the broader idea of pacing AI development.
Arora initially took a more skeptical view of the proposal. He posted on X that the call for a slowdown looked like a “NINJA MOVE,” suggesting that companies supporting the idea could gain a less visible competitive advantage.
He told CNBC that his initial reaction was driven by the possibility that leading AI companies were attempting to win greater sympathy from regulators and lawmakers.
“I thought they were trying to get the sympathy of the regulators and lawmakers and get a free pass on liability,” Arora said.
But his position has since shifted. Arora now argues that attempting to establish a coordinated pace for AI development is impractical because companies will inevitably move at different speeds.
“I think more than likely that some people will jump the gun, and you’ll have still people developing at the frontier, which means we shouldn’t try and stop the frontiers because they’re the most responsible people,” he said.
That view has created a distinction in the safety debate. Rather than arguing that AI development should proceed without constraints, Arora said companies should determine whether their products are safe enough to release and should hold back systems that are not ready.
“So, from that perspective, the idea is don’t release your product if you don’t believe it’s going to be safe, or you’re comfortable putting it out there,” he said.
He also questioned how the industry could practically establish a mechanism for measuring or enforcing the pace at which AI capabilities should advance.
The disagreement comes at a time when AI companies are debating whether safety should be governed primarily through voluntary safeguards, independent testing, or government regulation.
AI Extinction Risk Remains Contested
Arora also rejected the suggestion that AI has a 10% probability of wiping out humanity, although he acknowledged that the risk should not be dismissed.
“I think it is a small probability, which is extremely small, and it’s our job to make sure we build in the guardrails, the safety and security required, so these models are used for the right thing,” he said.
His position broadly aligns with Nvidia CEO Jensen Huang, who has noted that developers themselves should bear responsibility for determining whether AI systems are safe enough to release rather than relying primarily on new government safety regulations.
“We should create products and properly test them. And if they’re not ready to be released, just hold on to it and keep testing it and keep engineering until it’s ready,” Huang told CNBC’s Jim Cramer last week.
U.S. Treasury Secretary Scott Bessent has similarly noted that AI developers should take responsibility for their systems rather than expecting the federal government to provide a “liability shield.”
The emerging divide is therefore not simply between supporters and opponents of AI safety. Much of the disagreement centers on how safety should be achieved and who should determine when a model is sufficiently safe to deploy.
Amodei’s proposal focuses in part on coordinating the pace of frontier development, while Arora and Huang favor greater responsibility by individual developers and continued testing before release.
The contrast is growing and could become relevant as AI companies deploy models with greater autonomy and access to external tools. A voluntary approach places greater responsibility on companies to identify risks before products reach users, while a coordinated approach attempts to prevent competitive pressure from encouraging companies to move faster than their peers.
The difficulty with the latter approach, Arora argues, is enforcement.
U.S.-China Cooperation Adds Another Layer
The debate becomes even more complicated when it extends beyond individual companies and into international competition.
Amodei has proposed some degree of global coordination around AI development and pacing, including cooperation with China. The proposal comes as Washington and Beijing remain locked in competition over advanced AI, semiconductors, and computing infrastructure.
Bessent said Sunday that the United States and China had discussed establishing a “U.S.-China AI Dialogue.” According to Bessent, Washington proposed a notification mechanism for national-security incidents involving AI.
Such a mechanism could provide a channel for governments to communicate about serious AI-related incidents even while the two countries continue competing over technology.
But establishing meaningful cooperation could prove difficult. The United States has sought to restrict China’s access to advanced semiconductor technology that can be used for AI development, while Chinese companies are simultaneously expanding their own AI models and computing capabilities.
The geopolitical competition creates a fundamental tension for any attempt at coordinated AI safety. Governments may want to cooperate on risks that could cross national borders, while simultaneously trying to ensure their own companies remain technologically competitive.
Arora said the United States would first need greater agreement internally about what it wants from AI before attempting to coordinate its approach with another country.
“I think the first step is for us to get some semblance around what do we actually want before we start talking about let’s coordinate that with somebody else,” he said.
Arora’s stance underpins the central problem facing the emerging AI safety debate: the technology is developing globally, but there is no single authority capable of determining how quickly it should advance.
According to him, the practical alternative is not to attempt to halt frontier development but to place responsibility on developers to test their systems, build safeguards, and decide whether a product is ready for release. The competing view is that voluntary restraint may be difficult to sustain when companies are competing for technological leadership and commercial advantage.
