Prominent hedge fund managers Dan Sundheim and Mala Gaonkar are betting big on public companies rather than startups to capitalize on the artificial intelligence revolution, according to insights shared at Tuesday’s Invest for Kids conference in Chicago.
Dan Sundheim, founder of D1 Capital Partners, which manages approximately $26 billion, argued that the optimal way to invest in AI is through publicly-traded corporations rather than seed rounds or private companies. His rationale centers on the unique nature of AI as a transformative technology that will impact all sectors, requiring massive resources and infrastructure that only large public companies can effectively deploy.
Sundheim emphasized that scale trumps nimbleness in the AI field, noting that major corporations are making substantial capital and talent investments in AI projects without expecting short-term returns. These companies are looking at return on investment timelines of a decade rather than a quarter, reflecting the massive infrastructure requirements of AI implementation.
Mala Gaonkar, former Lone Pine executive who launched SurgoCap Partners in 2023, offered a complementary perspective on AI investing strategy. She stressed that AI will impact different industries on varying timelines, making it crucial for investors to identify which sectors will experience immediate benefits versus those requiring longer development periods. Gaonkar specifically highlighted medtech, particularly diagnostic imaging, as an early beneficiary of AI advances.
Both funds have demonstrated exceptional performance in 2024. Gaonkar’s SurgoCap Partners has surged more than 25% this year as assets have grown to over $3 billion. Sundheim’s D1 Capital has posted even stronger returns, with its public book up more than 34%, though its venture investments have declined 2.6% year-to-date.
Both managers are part of Julian Robertson’s Tiger Management network, known as Tiger Cubs, which focuses heavily on growth stocks and technology sector investments. Sundheim, who served as CIO at Viking Global before founding D1 in 2018, made 228 private company investments over the past six years, joining the aggressive private funding wave of 2020-2021.
Interestingly, Sundheim also identified Elon Musk’s SpaceX as the world’s most exciting private company, with D1 holding a stake worth approximately $2.5 billion. Sundheim also noted that AI infrastructure needs will create investment opportunities in companies supplying electrical grid upgrade equipment, highlighting the broader ecosystem opportunities surrounding AI development.
Key Quotes
AI, unlike other big technological advances, will be felt across sectors so all companies have an interest in putting money toward it.
Dan Sundheim explained why he believes public companies offer superior AI investment opportunities. This statement highlights AI’s unique cross-sector applicability, distinguishing it from previous technological revolutions that were more narrowly focused.
Companies putting capital and talent behind AI projects are doing so without expecting a short-term return on their investment… companies are looking at the ROI a decade from now, not a quarter.
Sundheim emphasized the long-term nature of AI investments, explaining why large public corporations with patient capital are better positioned than startups seeking quick returns. This reflects the massive infrastructure requirements of meaningful AI implementation.
Over the next three to five years, it’s crucial to know which areas will feel immediate benefits and which sectors will take time.
Mala Gaonkar stressed the importance of understanding AI’s differential impact across industries. Her focus on sector-specific timelines provides a strategic framework for investors seeking to optimize their AI exposure.
Our Take
The convergence of opinion between Sundheim and Gaonkar represents a maturation of AI investment thinking among elite hedge fund managers. Their pivot toward public companies reflects hard-won lessons from the 2020-2021 private funding frenzy, where many venture bets have underperformed. The emphasis on infrastructure and decade-long timelines suggests we’re moving beyond AI hype into a phase requiring serious capital deployment and operational execution—areas where established corporations excel. Notably, their exceptional 2024 returns (25-34%) validate this public-market approach, potentially triggering a broader reallocation of institutional capital away from AI startups. The identification of electrical grid suppliers as AI beneficiaries is particularly astute, recognizing that AI’s energy demands create lucrative secondary opportunities. This sophisticated, infrastructure-focused investment thesis may define the next phase of AI market evolution.
Why This Matters
This perspective from two prominent Tiger Cub fund managers signals a significant shift in AI investment strategy among sophisticated institutional investors. Their preference for public companies over startups challenges the prevailing narrative that early-stage AI ventures offer the best returns, suggesting that the capital-intensive nature of AI development favors established corporations with deep resources.
The emphasis on decade-long ROI timelines reflects AI’s fundamental difference from previous tech trends, requiring patient capital and massive infrastructure investments that only large-scale operations can sustain. This has important implications for both retail and institutional investors seeking AI exposure, suggesting that blue-chip tech stocks may offer more reliable returns than speculative startup investments.
Gaonkar’s sector-specific timeline analysis provides crucial guidance for portfolio allocation, indicating that investors must carefully evaluate which industries will benefit from AI in the near term versus long term. The identification of medtech as an early winner offers actionable intelligence for sector rotation strategies. Their combined $29 billion in assets under management and exceptional 2024 performance lends significant credibility to these investment theses, potentially influencing broader market capital flows toward public AI plays.
Recommended Reading
For those interested in learning more about artificial intelligence, machine learning, and effective AI communication, here are some excellent resources: