Nasdaq CEO Adena Friedman on 2026 outlook, impact of AI and IPO pipeline
Speakers
Adena Friedman
— CEO, Nasdaq
Summary
Nasdaq CEO and Chair Adena Friedman joins Squawk Box at Davos to discuss her 2026 outlook, focusing on AI as a transformative supercycle. She argues AI will require massive infrastructure and energy buildout, with public capital markets playing a larger funding role. She also says hyperscalers and AI-leaning semiconductor companies have earned into their multiples, while flagging capital needs for private AI leaders and a positive U.S. economic backdrop.
- Adena Friedman describes AI as a rare transformative supercycle.
- She sees a large AI infrastructure buildout requiring capital and energy infrastructure.
- Public capital markets are expected to play a bigger role in funding AI infrastructure.
- Hyperscalers and AI-focused semiconductor companies have seen multiples compress despite value creation.
- Private AI leaders show rapid revenue growth but face large capital requirements.
- She cites a positive U.S. economic outlook, strong consumer spending, and deregulatory tailwinds.
- Enterprise AI adoption depends on modernization of infrastructure, data, and code bases.
Ideas
AI is transformative supercycle with accelerating adoption.
AI is a transformative, infrequent supercycle that will greatly accelerate adoption, though enterprises still need foundational work on infrastructure, data management, and code bases to adopt at scale; it can also lower barriers for new businesses.
AI infrastructure buildout requires massive capital.
The AI supercycle requires an enormous infrastructure buildout, and the scale of $1.4T in infrastructure commitments means broader public capital markets will play a larger role in funding it.
Hyperscalers and AI semis earn into multiples.
Hyperscalers and AI-leaning semiconductor companies have seen their multiples come down even as their stock prices created enormous value, so they are earning into their valuations and remain fundamentally supported.
AI buildout drives energy infrastructure demand.
AI infrastructure commitments must spread out, requiring broader capital markets and industry experts to build out energy infrastructure and other infrastructure, creating a demand tailwind for energy infrastructure.
