AI's primary value in pre-buy research isn't just accelerating diligence on promising ideas. It's about rapidly surfacing deal-breakers—like misaligned management incentives or existential risks—allowing analysts to discard flawed theses much earlier in the process and focus their deep research time more effectively.

As platforms like AlphaSense automate the grunt work of research, the advantage is no longer in finding information. The new "alpha" for investors comes from asking better, more creative questions, identifying cross-industry trends, and being more adept at prompting the AI to uncover non-obvious connections.

The "generative" label on AI is misleading. Its true power for daily knowledge work lies not in creating artifacts, but in its superhuman ability to read, comprehend, and synthesize vast amounts of information—a far more frequent and fundamental task than writing.

Historically, investment tech focused on speed. Modern AI, like AlphaGo, offers something new: inhuman intelligence that reveals novel insights and strategies humans miss. For investors, this means moving beyond automation to using AI as a tool for generating genuine alpha through superior inference.

Effective AI tools are not just about task automation; they encode an expert's strategic perspective. By building a point-of-view-driven research process into an app—prioritizing specific metrics and analyses—you can scale specialized expertise across an entire marketing team, ensuring consistent, high-quality insights.

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.

While AI can easily generate checklists and templates, its transformative potential comes from its reasoning capabilities. It can parse decades of industry data to suggest a course of action and, more importantly, articulate the arguments and counterarguments, educating the user on the second-order consequences of their decisions.

During the time crunch of earnings season, AI excels at synthesizing disparate information. It can instantly compare a CEO's positive guidance against the recently reported cash flow statements of multiple competitors, flagging potential overconfidence or a genuine outlier.

A single human rarely masters animation, design, accounting, and finance. Klarna's CEO experienced AI creating an animated financial explanation that no single human could have produced because the AI possessed deep expertise across all the required, disparate domains simultaneously.