AI can generate multiple well-reasoned strategic options in the time it takes a team to brainstorm one. However, it still requires a senior leader's wisdom and domain expertise to select the best path. Leaders who combine their experience with AI's rapid analysis will dominate.

AI excels at probabilistic thinking and pattern matching (optimization), while humans excel at possibility thinking and innovation. The most powerful approach, the "centaur model," uses AI to handle optimization, freeing human cognition for imaginative tasks that create the future.

An AI model's response is not a prediction of what a single user might say, but a probabilistic continuation based on the entirety of its training data—a vast corpus of human writing. Its power stems from this massive-scale pattern matching on our collective cultural output, making it an echo of humanity's written history.

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.

AI's greatest impact on economics will be the ability to run complex, agent-based simulations. This allows economists to model the dynamic, equilibrium responses of millions of economic actors to policy changes—like a Fed balance sheet reduction—providing a much richer understanding than traditional, static models allow.

AI's predictive power is based on identifying patterns in historical data. While effective when the future resembles the past, this makes it inherently unable to account for new inventions, crises, or paradigm shifts not represented in its training text. It predicts from old maps, not what will come next in a new world.

AI models operate in a 'probability space,' making predictions by interpolating from past data. True human creativity operates in a 'possibility space,' generating novel ideas that have no precedent and cannot be probabilistically calculated. This is why AI can't invent something truly new.

While both humans and LLMs perform Bayesian updating, humans possess a critical additional capability: causal simulation. When a pen is thrown, a human simulates its trajectory to dodge it—a causal intervention. LLMs are stuck at the level of correlation and cannot perform these essential simulations.

Instead of fearing AI's superior cognitive intelligence (IQ), humans should focus on cultivating wisdom, intuition, and embodied intelligence. Dr. el Kaliouby suggests this is a uniquely human advantage that technology cannot replicate, allowing us to leverage AI without being defined or replaced by it.