An AI's ability to code complex games and physics simulations is a strong indicator of its overall power. This showcases its deep understanding and ability to handle sophisticated, multi-layered logic required for complex business applications, not just simple tasks.

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.

Many leaders test AI with simple, surface-level experiments. But modern AI is so advanced that these small tests create a false sense of understanding. According to Braze CPO Kevin Wang, genuine value is only revealed when AI is applied to complex, multi-team business problems and real-world workloads.

The primary benefit of using AI for revenue planning isn't just build speed. It's the ability to regenerate a complex, multi-tab model with thousands of formulas in minutes in response to feedback or methodology changes—a task that would previously take days of manual work.

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.

Whether AI models truly "reason" or are just sophisticated prediction machines is a philosophical question. From a business perspective, the distinction is irrelevant. The models simulate reasoning and empathy so effectively that the outcome is what matters, not the underlying mechanism.

Shopify's new SimGym tool, which uses AI agents to simulate how customers interact with a store, points to a new standard in marketing. Soon, launching a campaign, redesign, or product without first running it through a sophisticated AI simulation will be considered archaic and reckless.

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.

Go beyond using AI for simple efficiency gains. Engage with advanced reasoning models as if they were expert business consultants. Ask them deep, strategic questions to fundamentally innovate and reimagine your business, not just incrementally optimize current operations.