Simulate the future, before you build it
Christopher Lyrem
Founder & CEO, Disruptivity
Disruption is a recurring feature of economic development. Drawing on his study of 300 market disruptions over the past 300 years, Christopher Lyrhem explores why industries change, why established companies often struggle to adapt and how businesses can prepare before change becomes unavoidable.
Watch his full presentation in the video.
A central finding is that newcomers drive the overwhelming majority of disruptions. Established companies tend to prioritise efficiency, incremental improvements and short-term returns, while their past success can make it harder to challenge existing business models. Customers too, usually express their needs in terms of what they already know. Creating fundamentally new customer value therefore requires looking beyond current demand and imagining possibilities that are not yet obvious.
Lyrhem argues that AI is a general-purpose technology whose impact will extend far beyond improving individual tasks. Like earlier technological shifts, it could reshape supply chains, distribution, customer value and the economics of entire industries. He explores four areas of transformation: general-purpose robotics, autonomous mobility, an “intelligence internet” powered by AI agents, and the changing nature of research and knowledge work.
These developments could enable robots to perform a wide range of physical tasks, autonomous vehicles to transform both transport and retail, and AI agents to make software creation and digital services accessible to many more people. As the cost of research and analysis falls, businesses can investigate questions and explore opportunities that previously required substantial time and resources.
Looking further ahead, Lyrhem highlights the potential of large quantitative models—AI models built around mathematical and scientific relationships—to expand simulation and decision-making.
This vision is a shift from predicting the future through analysis alone towards testing possible strategies in dynamic models of companies and markets.
The practical implication is to bring foresight and strategy together. Companies need a continuous process for exploring future scenarios, questioning assumptions and translating emerging insights into decisions. This requires giving independent analysis a regular place in management discussions, including findings that challenge the organisation’s current direction. The aim is to build the capacity to anticipate change and act while there is still time to shape the outcome.