Broadcom CEO Hock Tan remains unfazed by concerns regarding a potential slowdown in cutting-edge AI model development, asserting that the company’s long-term revenue projections remain robust. Tan’s confidence comes amid investor jitters sparked by Anthropic CEO Dario Amodei’s recent essay advocating for a more measured pace in AI model advancement. Amodei’s call for moderation, echoed by prominent figures like OpenAI CEO Sam Altman and Elon Musk, led to a reassessment of compute demand expectations among investors in AI infrastructure providers.
This sentiment directly impacted Broadcom’s stock, which saw a 4.8% decline. The broader semiconductor market experienced a significant downturn, with the iShares Semiconductor ETF shedding 5.6%. Companies supplying other data-center components also faced considerable selling pressure.
When questioned on CNBC’s “Mad Money” about whether the AI slowdown debate had influenced his outlook, Tan dismissed the notion. “No, not in the least,” he stated. “We see the demand for compute infrastructure, for AI development or AI frontier models, and inference for the products that they feed to the world, as continuing to be very strong and, I believe, very durable.”
Broadcom’s ambitious growth trajectory for its AI semiconductor business is underpinned by substantial revenue targets. On its fiscal 2026 third-quarter earnings call, Tan projected AI semiconductor revenue to reach $115 billion in fiscal 2027, with an audacious doubling to $230 billion by fiscal 2028. This significantly bolstered 2028 forecast was a key highlight of the earnings report. Broadcom’s AI revenue stream is diversified, encompassing both custom AI accelerators and essential networking chips that power AI systems.
A significant driver of this optimism is Broadcom’s relationship with Anthropic. Tan indicated that Anthropic is on track to become Broadcom’s largest custom chip customer in 2027 and maintain that position through 2028. This customer dynamic underscores why investor sentiment towards Broadcom is particularly sensitive to commentary from Anthropic’s leadership. Historically, Google has been a cornerstone of Broadcom’s custom chip business, collaborating on the design of Google’s Tensor Processing Units.
During his recent CNBC interview, Tan expressed particular optimism regarding the demand for AI inference—the process of utilizing trained AI models for real-world applications. “I don’t know about training, but when you want to productize inference, I see it continuing to be very, very strong,” Tan remarked.
Amodei’s essay reignited a critical debate within the AI community: whether the industry is progressing too rapidly in developing increasingly powerful models. Amodei proposed a structured, three-phase approach to decelerate development without compromising commercial competitiveness or the United States’ leadership in AI.
While Tan acknowledged the necessity of establishing governance and safeguards for AI usage, he conveyed a less alarmist perspective on the technology’s trajectory. “Like any tool, it’s important to put governances, safeguards on how we use the tool,” Tan told Cramer. He further elaborated that AI should not be perceived as an autonomous entity capable of uncontrolled proliferation.
Instead, Tan championed AI’s transformative potential to significantly enhance productivity. “AI, generative AI, the creation of those frontier models … will create huge value,” he stated, drawing parallels to the societal impact of the Industrial Revolution. He concluded by emphasizing AI’s role as a tool that will ultimately elevate the quality of life for humanity.
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