The Evolution of Value Investing: What AI Really Changes and What Remains Untouched

When Guy Spier, the legendary fund manager who leads Aquamarine Fund, declared that “the golden age of value investing is over,” he wasn’t being dramatic. After three decades navigating markets and nearly $500 million in assets under management, Spier’s recent Bloomberg piece sparked urgent conversations: Is active investing—particularly value investing—becoming obsolete?

How Information Technology Dismantled the Competitive Edge

For decades, fund managers built their reputations on one fundamental advantage: they could access and process information faster and more thoroughly than ordinary investors. Spier’s own track record proved it. Since 1997, Aquamarine Fund has delivered annualized returns exceeding 9%, consistently outpacing the S&P 500 while reducing downside risk—a feat few active managers achieve.

That edge came from relentless grassroots work. Spier famously traveled to Berkshire shareholder meetings, took flights to London for conversations with investment pioneers Nick Sleep and Qais Zakaria, and spent weeks piecing together scattered information to form investment theses. In that era, research took days or weeks. Knowledge accumulation was measured in incremental blocks. Obtaining corporate data required hunting through annual reports, making phone calls, and building relationships.

But the world has fundamentally shifted.

Today, anyone with an internet connection accesses research reports, earnings transcripts, and industry analysis instantly. Artificial intelligence processes public information at speeds that make human research timelines irrelevant. Large language models auto-generate research summaries. Data analytics tools democratize insights that once required armies of analysts. The information asymmetry that once separated exceptional fund managers from the crowd has nearly vanished.

The Compression of Returns and Rise of Homogeneous Competition

This shift carries serious consequences for professional investors. When analytical frameworks converge—when everyone uses similar AI tools and data sources—several dynamics emerge:

Asset allocation becomes increasingly crowded. Multiple managers identify the same opportunities simultaneously, driving rapid price adjustments and amplifying volatility.

Market inefficiencies compress. The subtle tells hidden in balance sheets and management commentary that skilled investors once exploited become visible to algorithms almost instantly.

Alpha becomes harder to isolate from Beta. Active managers increasingly struggle to prove their value beyond what passive index investing delivers at lower cost.

The result: returns from active management are narrowing, crowding toward index returns. For many investors, the historical case for paying active management fees has weakened considerably.

Yet here’s where Spier’s analysis becomes intriguing—the “goodbye” isn’t absolute.

What Artificial Intelligence Cannot Replace

AI erased information advantage. It did not erase the need for thinking.

The shift from information gathering to information synthesis fundamentally changes what separates superior fund managers from the rest. In the previous paradigm, competitive advantage came from spending weeks compiling scattered data. Today, the advantage shifts to framework construction—how you structure problems, which questions you ask, and how rigorously you test hypotheses.

This distinction matters profoundly. Large language models excel at pattern recognition and synthesis of known information. They are nearly useless at identifying logical blind spots, questioning underlying premises, or resisting consensus illusions. When model outputs converge, algorithmic errors amplify rather than average out.

The investors who will thrive are those who ask better questions of the data, not simply those who process information faster.

The Soft Skills Edge: Discipline, Patience, and Counter-Cyclical Courage

If informational advantages are eroding, Spier identifies a new competitive terrain: behavioral and psychological factors that resist replication.

Superior fund managers will increasingly differentiate themselves through:

• Investment discipline that avoids reactive decisions during volatility
• Emotional resilience that enables long-term holding through cycle downturns
• Counter-cyclical conviction that buys fear and sells greed when most are doing the opposite
• Organizational consistency that enforces systematic decision-making across market regimes

Unlike technical analysis or data processing, these capabilities build deeper moats. They cannot be downloaded as software. They require months or years to develop and internalize.

The Real Transformation: From Information Processing to Structured Judgment

What the AI era actually demands is a phase transition in how active investors justify their existence.

The competition among professional managers no longer centers on “who sees deeper” but increasingly on “who thinks more clearly under uncertainty.” The winners will construct robust investment systems, organize disciplined teams, and maintain philosophical consistency across market cycles—not simply deploy the fastest algorithms or most sophisticated data pipelines.

In this sense, value investing hasn’t said goodbye. It has evolved. The past belonged to information hoarders and research obsessives. The future belongs to system builders and disciplined thinkers—investors with long time horizons, institutional discipline, and the psychological capacity to act counter to consensus.

Spier’s 2025 reflection isn’t a pessimistic prediction of industry decline. It’s a declaration of transition. The age of beating markets through superior information access is genuinely over. But the age of beating markets through superior thinking, discipline, and long-term systems has only begun. For fund managers willing to evolve, that transformation may prove even more rewarding than the era it replaces.