BlackRock's unique Aladdin technology is a scenario-planning AI used by the world's largest capital pools (pension funds, central banks). It models geopolitical events and recommends capital movements, effectively giving BlackRock immense influence over global financial markets.

One of Simile's surprising yet common use cases is simulating corporate earnings calls. This multi-agent simulation allows executive teams to test their messaging and anticipate audience and investor reactions, providing a rehearsal space for high-stakes financial communications before they happen.

Beyond simple concept testing, AI simulations allow businesses to model downstream consequences. A car company can simulate how launching a new EV might change market perception of its entire gas-powered product line, revealing second-order effects that are impossible to test in the real world.

AI platforms use proprietary knowledge graphs to map market ripple effects, actively surfacing risks and opportunities investors might otherwise miss. This addresses the core anxiety of “what am I missing?” that plagues portfolio managers, going beyond simply answering direct questions.

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.

To adopt AI without sacrificing accuracy, BlackRock established a "first draft principle." AI can generate the initial version of any document—from client presentations to prospectuses—but it must then pass through the rigorous, multi-layered human review process already in place, ensuring control and quality.

For a multi-trillion dollar manager, agility isn't about small trades but leveraging scale for superior market access and research. The key is acting early to identify risks or opportunities before liquidity dries up, effectively using information advantages to front-run market stress.

Advent created an AI trained on its entire investment history, including deals they passed on. This 'IC Robot' analyzes new proposals and flags assumptions—like margin growth—that deviate from historical precedent, serving as a powerful, data-driven check on the investment committee's biases.

To overcome the limitation of having only ~100 years of real financial data, CFM is exploring the use of Generative AI to create vast synthetic market histories. This would allow them to train and test their quantitative models on a scale of a "million years," making them more robust.