The AI landscape is shifting. At the recent HumanX conference in San Francisco, a gathering of 6,500 executives, founders, and investors focused on artificial intelligence, a clear narrative emerged: OpenAI’s once-unrivaled dominance in the industry is now being challenged, with Anthropic stepping into the spotlight.
Anthropic’s coding agent, Claude Code, was the talk of the town. While many attendees acknowledged the robust offerings from OpenAI, Cursor, and Google, the momentum undeniably favored Anthropic. This surge comes despite a recent public dispute with the Pentagon. Although the Department of Defense initially blacklisted Claude, subsequent court rulings have allowed Anthropic to continue its work with other federal agencies.
Anthropic’s early success in the enterprise sector has uniquely positioned it to capitalize on the burgeoning demand for AI coding agents, tools designed to generate, edit, and review code. While OpenAI pioneered the generative AI revolution with ChatGPT in 2022, Anthropic appears poised to capture significant contracts from major enterprises.
CNBC spoke with 19 executives and investors at HumanX, some of whom requested anonymity to share their candid perspectives. Here are the key takeaways from these discussions:
## Claude: A Growing Devotion
Founded in 2021 by former OpenAI researchers and executives, Anthropic is now valued at an impressive $380 billion, making it one of the world’s most valuable private companies. Since its public launch in May 2025, Claude Code has been a significant revenue driver, generating over $2.5 billion in annualized revenue as of February.
Arvind Jain, CEO of the enterprise AI company Glean, described the phenomenon as “Claude Mania,” creating palpable pressure on business leaders to adopt the technology. “It has become a religion, that’s the level of that mania,” Jain stated in an interview. “Everybody, if you go and ask them today, ‘Hey, if I gave you one AI tool, what tool would you want?’ The answer would be Claude.”
Anthropic further fueled excitement at HumanX with the announcement of Claude Mythos Preview, a new AI model boasting advanced cybersecurity capabilities derived from its strong coding and reasoning prowess. Though its rollout is limited to approximately 50 companies, the model generated considerable buzz.
Victor Riparbelli, CEO of AI video company Synthesia, praised Anthropic’s focused approach to product development, a challenging feat for a rapidly growing startup. “The guys at Anthropic were just like, ‘We’re not going to do anything about video, we’re not going to care about voice models, we’re just going to solve code gen,’ and now we’re here,” Riparbelli explained. He contrasted this with OpenAI, which he believes has been hindered by the need to market multiple products simultaneously, potentially diluting consumer focus.
However, one investor cautioned that while Anthropic has demonstrated consistency and identified a valuable AI use case, the industry remains nascent, and market dynamics can shift rapidly.
## Navigating the AI Transformation: Change Management in the Age of Intelligent Agents
As the tech industry spearheads the integration of AI, companies are simultaneously grappling with its internal deployment and utilization. Even for established Silicon Valley firms, keeping pace with the rapid evolution of AI presents a significant challenge.
Ashwin Sreenivas, president of AI startup Decagon, highlighted how the advent of coding agents has reshaped his company’s operations. Decagon has adapted its interview process to incorporate these tools and now relies on smaller engineering teams. “A project that may have required four or five engineers becomes two engineers because everyone can move a lot faster and go a lot farther,” Sreenivas observed.
For Navrina Singh, CEO of AI governance startup Credo AI, the proliferation of new AI tools evokes both excitement and apprehension. She emphasized the critical importance of enhanced communication, particularly with her clientele. “The things that I could not do last year and I needed to hire 10 people, I can actually build over a weekend and deploy for myself and for the company,” Singh shared. “The anxiety is I can’t control my roadmap, and I can’t control my commitments to the enterprise customers who love more clarity and who like a little bit more stability.”
Incumbent tech giants are facing similar organizational shifts. Jeetu Patel, President of Cisco, revealed that approximately 85% of his company’s engineering workforce, around 18,000 employees, are actively utilizing AI. He noted that the path to widespread adoption was unexpected, with Cisco initially prioritizing adoption over immediate outcomes, trusting in the continuous improvement of AI model capabilities.
“You can’t think of these as tools, you have to think of these as digital coworkers that are joining your team, because your composition of your scrum team changes,” Patel stated at the conference. “You might not have a scrum team of eight people. You might have a scrum team of two people and six agents, or two people and infinite agents.”
## The Geopolitical AI Race: Closing the Gap with China
While recent geopolitical tensions in the Middle East have not yet directly impacted most businesses according to executives and investors at HumanX, a more significant concern looms: China’s advancements in open-weight AI models.
In the AI domain, open-weight models are those where the parameters, crucial for enhancing output and predictions during training, are publicly accessible. As of April, Chinese open-weight models, including GLM-5.1, Kimi 2.5, and Qwen3.5, have demonstrated superior performance across industry benchmarks.
American companies are increasingly adopting these Chinese models. Cursor, for instance, built its Composer 2 model leveraging Kimi 2.5. Earlier, Airbnb’s CEO Brian Chesky disclosed that his company’s chatbot was largely powered by Alibaba’s Qwen model.
Given the U.S. AI industry’s strategic imperative to lead in innovation, there’s a significant domestic focus on closing the gap in open-weight model development. Two investors indicated they are dedicating substantial resources to this effort, with a third identifying it as a critical challenge for the industry.
Glean’s Jain stressed the importance of having diverse AI options. “The trend that we see is that enterprises today, they’re very wary of depending on one or two providers for all of their AI,” Jain commented. “They don’t want to work with just one model company, because they know that innovation is happening across many and also in open source. You want to have a choice.”
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