Despite the wide availability of powerful AI models, a sustainable edge in the zero-sum game of investing comes from a combination of unique, curated data sets, bespoke technology for scale, and the experienced human context to ask the right questions of the models.

The historical information asymmetry between professional and retail investors is gone. Tools like ChatGPT and Perplexity allow any individual to access and synthesize financial data, reports, and analysis at a level previously reserved for institutions, effectively leveling the playing field for stock picking.

David Kaiser of Methodical Investments posits a contrarian view on AI's market impact. Instead of creating perfect efficiency, he argues AI and the data it processes might actually create more mispricings and inefficiencies. This provides opportunities for disciplined, rules-based strategies that don't constantly adapt to short-term noise.

Contrary to classic theory, markets may be growing less efficient. This is driven not only by passive indexing but also by a structural shift in active management towards short-term, quantitative strategies that prioritize immediate price movements over long-term fundamental value.

Widespread use of similar AI models by average investors will likely lead to herd behavior and crowding in certain securities. This pushes prices away from fundamental value, creating predictable inefficiencies and new alpha opportunities for sophisticated investors who can model these effects.

An individual using a consumer AI tool for investing is like bringing a "swear gun to a howitzer fight." Institutional firms hire thousands of PhDs to leverage AI, creating an insurmountable advantage. Retail investors should stick to low-cost ETFs.

The narrative that AI will disadvantage retail day traders is flawed; they are already being systematically beaten by sophisticated firms like Citadel. AI merely changes the identity of the winner who extracts value from the retail gambler, not the outcome for the gambler.

An investor's job fundamentally boils down to pattern recognition and superior analysis. Since AI can process thousands of documents in seconds and backtest infinite historical patterns instantaneously, it threatens to eliminate the "alpha" or informational edge that human investors currently possess in the knowledge economy.

The expectation that universal, instant access to information would lead to more efficient markets has been proven wrong. Instead, it has amplified sentiment-driven volatility. Stock prices have become less tethered to fundamentals as information is interpreted through the lens of crowd psychology, not rational analysis.