Right now, most organizations are using artificial intelligence to shave time off admin. Large language models are drafting emails, summarizing documents, automating customer support. These tools are helpful, but they barely touch the surface of what AI is capable of.

The real opportunity for businesses integrating AI lies not only in automation, but also in simulation – using it not just to do things faster, but to make smarter decisions before they are made.

AI can now model real-world complexity, test strategy, and forecast the likely impact of decisions – before they’re made. That changes the nature of leadership: from acting quickly to acting wisely.

Too often, major decisions in both business and government are based on historic data, small-scale polling or executive instinct.

But in a fast-changing world, that is no longer enough. I saw this during the Covid-19 pandemic where even in Downing Street, critical decisions were made with patchy data and too much uncertainty.

Business leaders face the same risks today when making high-stakes calls – made with tools not designed for speed or complexity.

Benefits of simulation

Simulation offers a different, more exciting path. AI can now function in effect as a strategic rehearsal room; a digital environment where pricing decisions, product changes, or policy proposals can be tested against realistic, data-rich models of how people are likely to respond. This means fewer surprises, better timing, and more confident delivery.

Synthetic populations – realistic, accurate, data-driven models of audiences – are now helping companies simulate how customers are likely to respond to a product, price or message before going live.

It’s a faster, more accurate way to stress-test decisions, now being used by a growing number of businesses to avoid costly missteps and fine-tune strategy early.

Predicting human behavior is one of the most crucial and unsolved challenges in both policy and business. Too often, intuition replaces evidence simply because the tools to simulate reactions have been lacking. That’s now changing.

But data alone is not enough. Too often in business, policy, and public debate, we talk past each other because we fail to understand the lived experiences that shape how people think and act.

By grounding simulation models in both rigorous science and a realistic understanding of those diverse perspectives, we give decision-makers a truer picture of how people are likely to respond – not just in theory, but in the real world.

Complex business decisions

Management consultants Gartner predict that over half of complex business decisions will involve AI by 2027. But most firms are still in phase one: using AI tools to automate tasks, not shape choices. That’s a major missed opportunity.

Take the recent American Eagles ‘Great Jeans’ advert. Whether the controversy was intentional or not is still up for debate – but it’s undeniably drawn backlash and headlines. Predictive AI tools can be used to simulate how different audiences are likely to respond to campaigns like this before they go live.

Rather than relying on gut instinct or hoping a creative risk will land – brands can rehearse reactions in advance – testing everything from sentiment and tones to audience sentiment and media placement.

This is not about replacing human judgement, but complementing it – using AI to bring forward insight that would otherwise only arrive after the fact. Just as forecasting revolutionized financial services, predictive simulation is on track to become a normalized part of business decision-making.

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Co-Founder of Electric Twin.