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.

The discipline of writing down your thought process is crucial for decision analysis. AI now amplifies this by creating a searchable, analyzable record of your thinking over time, helping you identify blind spots and get objective feedback on your reasoning.

WCM avoids generic AI use cases. Instead, they've built a "research partner" AI model specifically tuned to codify and diagnose their core concepts of "moat trajectory" and "culture." This allows them to amplify their unique edge by systematically flagging changes across a vast universe of data, rather than just automating simple tasks.

Founders are consistently and universally wrong about their financial projections, particularly cash runway. AI tools can provide an objective, data-driven forecast based on trailing growth, correcting for inherent founder optimism and preventing critical miscalculations.

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.

To create a truly innovative AI, Bridgewater established its "artificial investor" as a separate venture. This prevented the AI from simply inheriting the biases and flaws of the existing human-driven system. The goal was for the AI to develop its own independent, uncorrelated ideas rather than becoming a digital copy of Bridgewater itself.

Advanced AI tools can model an organization's internal investment beliefs and processes. This allows investment committees to use the AI to "red team" proposals by prompting it to generate a memo with a negative stance or to re-evaluate a deal based on a new assumption, like a net-zero mandate.

By digitizing its 94-year library of proprietary research, Capital Group enables its investors to use AI for behavioral self-analysis. An investor can query the system to identify what mistakes they personally made in past market cycles with similar conditions, helping them avoid repeating errors.

Beyond automating data collection, investment firms can use AI to generate novel analytical frameworks. By asking AI to find new ways to plot and interpret data inputs, the team moves from rote data entry to higher-level analysis, using the technology as a creative and strategic partner.