- Former OpenAI Head of Go-To-Market Zack Kass said artificial intelligence will produce many winners across industries, not just a handful of dominant tech companies.
- Kass described the current moment as still “early days” for AI investment and urged businesses to adopt AI strategically rather than wait for certainty.
- He argued that cultural and ethical resistance — not technical limitations — will determine how fast AI transforms industries and who benefits most.
What Happened
Zack Kass, the former Head of Go-To-Market at OpenAI, told Bloomberg Television that artificial intelligence “is going to make a lot of winners.” Speaking with anchor Haslinda Amin from the sidelines of the Citi Macro Conference in Hong Kong on March 30, 2026, Kass pushed back against the widespread narrative that AI’s economic benefits will consolidate among a small number of tech giants.
Kass, who spent years leading sales, partnerships, and customer success teams at OpenAI before departing, has become one of the most prominent voices advising Fortune 1,000 companies on AI integration. His advisory client list includes Coca-Cola, Morgan Stanley, and Amgen, spanning consumer goods, financial services, and pharmaceuticals.
The Bloomberg interview took place amid growing investor anxiety about whether AI spending is producing adequate returns. Kass argued that the pessimism is premature and that the technology is still in its earliest phase of commercial deployment.
Why It Matters
The AI investment landscape has attracted significant skepticism over the past year. Many analysts have drawn direct parallels to the dot-com bubble, suggesting that a small group of companies will capture most of the value while others lose their bets. Global AI capital expenditures plus venture capital investments have already exceeded $600 billion, amplifying concerns about overinvestment.
Kass’s argument runs counter to that narrative. His position carries weight because he helped build OpenAI’s commercial strategy during the company’s rapid rise from research lab to the fastest-growing consumer application in history. He has direct experience watching how businesses of various sizes respond to AI tools across different sectors.
“I left OpenAI to support the AI revolution,” Kass has stated in previous interviews. He now operates as an independent advisor and keynote speaker based in Santa Barbara, California, framing AI as an opportunity for broad economic participation rather than a winner-take-all competition.
Technical Details
Kass’s thesis centers on a framework he calls “The Next Renaissance,” which treats AI not as a job-replacement technology but as a productivity layer that enables smaller organizations to compete with larger ones. The argument rests on a specific observation: as AI tools become cheaper and more accessible, the advantages that large companies hold through scale diminish. A ten-person marketing agency using AI-generated content can now produce output that previously required a fifty-person team.
In his advisory work with enterprise clients, Kass emphasizes that the biggest barrier to AI adoption is not computational power or model quality. Instead, he identifies cultural resistance within organizations and unresolved ethical questions as the primary obstacles slowing progress.
Kass holds a BA from UC Berkeley and has spent more than 15 years working in artificial intelligence. At OpenAI, he was responsible for bringing the company’s products to market during the critical period when ChatGPT went from research project to mainstream tool, reaching 100 million monthly users within two months of launch.
He has also highlighted the importance of soft skills in the AI era. In his conference appearances, Kass consistently argues that continuous learning, adaptability, and the ability to work alongside AI systems will separate organizations that benefit from the technology from those that fall behind.
Who’s Affected
Kass’s remarks are directed at enterprise leaders and institutional investors who are still evaluating whether AI investments will deliver meaningful returns. His argument suggests that mid-market companies and startups — not just Big Tech — can capture significant value from strategic AI adoption.
The message is also relevant to policymakers weighing AI regulation. If AI’s economic benefits distribute broadly across industries and company sizes, the case for heavy-handed regulation weakens. If benefits concentrate among a few dominant players, the case for intervention strengthens. Kass’s position supports the former scenario.
Workers across sectors are also affected. If Kass is correct that AI creates many winners, the technology may reshape job functions without eliminating positions at the scale that some labor economists have projected.
What’s Next
Kass continues his advisory and speaking engagements through 2026, with keynotes scheduled at multiple industry conferences worldwide. The central test of his thesis will come over the next 12 to 18 months as enterprise AI deployments mature and produce measurable return-on-investment data. The main limitation of his optimistic outlook is that it depends on AI tools remaining affordable and accessible — an assumption that could be challenged if compute costs rise or if leading AI companies restrict access to their most capable models.
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