When you hear about AI "agents," you probably picture an automated assistant, diligently clearing your inbox or scheduling meetings. We tend to think about the efficiency of offloading tedious tasks. While that’s useful, it’s a failure of imagination.  

Focusing on simple automation misses the exponential value these agents could unlock. One area we’ve been focusing on lately has been exploring when their true power isn't in doing tasks but in simulating futures. 

The real revolution pairs agents with "digital twins"- dynamic, virtual replicas of real-world systems. This combination creates a sentient sandbox, a flight simulator for business strategy where you can war-game decisions before you bet the farm on them. Instead of asking an AI to write a marketing email, you can ask a team of AI agents - playing the roles of your customers, competitors, and suppliers - how they’d react to an entirely new business model. 

This isn't a theoretical exercise; it's already a competitive advantage for those who get it. The BMW Group is building a "Virtual Factory," a digital twin of its entire global production network. Inside this virtual world, AI agents run thousands of simulations to perfect factory layouts and robotics, projecting planning cost reductions of up to 30%. They’re not just building cars; they’re rehearsing how to build them perfectly.    

UPS has deployed ORION, a true agentic AI that powers a digital twin of its distribution network. This isn't a simple route planner. It’s an intelligent system that autonomously makes decisions, learning from every delivery. The results are staggering: $300 million in annual savings and 100 million fewer miles driven.    

These leaders understand that the most complex variable in any business is people. Your strategy lives or dies on how customers, competitors, and regulators behave.  

Now, this doesn’t mean you’d be able to create the level of simulation like the larger corporates I’ve just shared but think about what you use to make business decisions. How much data, counsel, and conversation do you use? We all end up taking advice and data to a point. I’m simply offering another pathway to help aid in decision-making. What if you spent the time to build up digital twins and context in an LLM to then run scenarios to help expand or test your thinking. the more time you spend providing the context or training a model the more likely you are to get more helpful results.  

If you’re interested in learning more about how, reach out and I can share some of our early explorations.