Why Howard Marks Prefers Tech Giants Over AI Startups
Investors pouring millions into speculative AI startups face odds similar to lottery tickets, warns Howard Marks of Oaktree Capital. On the "We Study Billionaires" podcast, Marks outlined the stark contrast between risky AI "moonshot" bets and mature tech titans already generating profits. This is more than cautious investing—it's a recognition of how technological leverage compounds differently depending on system scale.
Marks highlights a critical distinction: established tech giants integrate AI incrementally, harnessing existing infrastructure and revenue streams to absorb shocks. In contrast, most AI startups face a binary survival game with no guarantee of profits. This dynamic shapes where leverage—and therefore durable advantage—truly lies.
Understanding this constraint reshapes how operators approach AI investing and system design. "Change the world and investors making money are not the same thing," Marks notes, pointing to a repeated bubble pattern seen from the dot-com boom to subprime crises.
Rational investments build on platforms, not hype. That’s leverage.
Why Rallying Behind AI Startups Is a High-Risk Lottery
The dominant narrative glorifies AI startups as potential disruptors poised to leapfrog incumbents. This "moonshot mentality" ignores the harsh survival dynamics straining early-stage tech ventures. Unlike giants able to absorb failures with diverse revenue, startups face a single bet—sink or swim.
This binary outcome framework forces speculative behavior, pushing valuations detached from profit potential. Investors chasing lottery-like jackpots overlook the system leverage that tech titans possess through scale and established profit engines. Wall Street’s tech selloff in 2025 exposed this profit lock-in constraint clearly.
In contrast, mature players have diversified AI applications that deliver modular gains rather than bet-the-company gambles. Their systems compound innovation incrementally, making returns more predictable and less binary.
How Big Tech’s Structural Advantages Absorb AI Shocks
Microsoft, Google, and Meta exemplify players layering AI onto vast existing platforms. The cost to implement AI is spread across billions of users, internal data, and cloud infrastructure, dropping incremental expenses towards zero. This creates compounding leverage that pure-play startups cannot replicate without massive funding and years of scaling.
This systemic leverage resembles the trend OpenAI harnessed in scaling ChatGPT to 1 billion users. Startups lack similar built-in audiences or enterprise integrations, forcing them into volatile binary gambles.
Differently from early internet plays in 2000, today’s giants have safeguarded profit streams, cushioning AI transitions. This ownership of existing revenue engines shifts the fundamental constraint from hype to execution and integration.
Why Leverage Experts Must Rethink AI Investment Paths
Shifting from startup chase to platform ownership shifts the intellectual leverage: it forces investors and operators to identify where system-level advantages compound over time without continuous intervention. Leveraging existing profit engines to fund AI adoption reduces risk and creates sustainable advantage.
This contrasts sharply with the popular startup fixation, offering a more repeatable, scalable framework for long-term gains. The constraint shifts from “finding the next big bet” to “optimizing AI integration in established systems.”
Operators mastering this shift can unlock important strategic moves otherwise obscured by hype. For example, companies failing to recognize this risk suffer expensive layoffs and strategic retrenchments, as explored in Why 2024 tech layoffs reveal structural leverage failures.
Ultimately, placing bets on existing tech giants is a lever that turns risk into incremental, compounding advantage—buying stability amid AI’s uncertainty.
Related Tools & Resources
For businesses exploring AI integration while mitigating risk, leveraging tools like Blackbox AI can streamline coding and development processes. This aligns perfectly with Howard Marks' insights on focusing on established platforms capable of absorbing shocks and ensuring sustainable growth. Learn more about Blackbox AI →
Full Transparency: Some links in this article are affiliate partnerships. If you find value in the tools we recommend and decide to try them, we may earn a commission at no extra cost to you. We only recommend tools that align with the strategic thinking we share here. Think of it as supporting independent business analysis while discovering leverage in your own operations.
Frequently Asked Questions
Why does Howard Marks prefer investing in tech giants over AI startups?
Howard Marks prefers tech giants because they integrate AI incrementally on established platforms, spreading costs and risks, unlike AI startups which face high binary survival risks with no guaranteed profits.
What are the risks of investing in AI startups according to Howard Marks?
AI startups pose high risks as they face a binary survival game—sink or swim—with speculative valuations detached from profit potential, making investments similar to lottery tickets.
How do tech giants absorb AI-related risks better than startups?
Tech giants like Microsoft, Google, and Meta spread AI implementation costs across billions of users and diverse revenue streams, reducing incremental expenses and making returns more predictable and less risky.
What examples illustrate the scale advantage of tech giants in AI?
OpenAI scaling ChatGPT to 1 billion users exemplifies systemic leverage; unlike startups, giants have built-in audiences and enterprise integration that reduce volatility in AI investments.
How has Wall Street's tech selloff in 2025 highlighted profit lock-in constraints?
The 2025 tech selloff exposed how market valuations reflect the advantage tech giants have with diversified, profit-generating AI applications versus speculative startup bets vulnerable to hype.
What strategic shifts should investors consider for AI investments?
Investors should shift focus from chasing high-risk AI startups to investing in established platforms where AI adoption compounds existing profit engines, creating sustainable long-term advantages.
How do 2024 tech layoffs reveal structural leverage failures?
Massive layoffs in 2024 highlight failures to recognize structural leverage, where companies over-invested in hype-driven AI startups without stable profit bases, leading to costly retrenchments.
What tools can businesses use to integrate AI while mitigating risk?
Tools like Blackbox AI help businesses streamline AI coding and development, aligning with Howard Marks' strategy of leveraging established platforms to absorb AI integration shocks.