Digital Twins and Virtual Experimentation: Testing the Future Before Building It

IXL Center Team
Oct 28
2 min read

Why This Matters Now

The world is becoming too complex, costly, and fast-moving to innovate through physical trial and error alone. Digital twins, high-fidelity virtual replicas that integrate real-time data, simulation, and artificial intelligence, mirror how systems behave in the real world.

This technology is transforming how organizations design, test, and operate, from aerospace and healthcare to manufacturing, finance, and city planning. By creating digital environments for experimentation, companies can test bold ideas safely, uncover new efficiencies, and reduce environmental and financial risk.

By 2030, the global digital twin market is expected to surpass 130 billion dollars as organizations recognize that virtual experimentation is not only faster but also smarter.

The Strategic Questions Every Executive Should Be Asking

How can digital twins help us innovate faster while reducing operational risk?
Where can virtual experimentation improve decision-making or sustainability outcomes?
How might combining artificial intelligence and simulation enhance forecasting accuracy?
What new skills and partnerships are required to operationalize digital twins across our business?
Can we use virtual testing to explore markets and solutions that physical prototypes cannot reach?

Cross-Industry Market Signals

Leaders across industries are already building their strategies:

Dassault Systèmes provides virtual twin experiences for industries ranging from healthcare to construction, allowing organizations to simulate real-world performance digitally.
PTC integrates industrial Internet of Things data with virtual models to optimize product development and factory performance.
GE Aerospace applies digital twins to aircraft engines, enabling predictive maintenance and improving safety across global fleets.

The Risk of Inaction

Organizations that fail to integrate digital twins risk:

Higher costs from inefficient research and development and reactive maintenance.
Limited visibility into operations that slows down decision-making.
Missed opportunities for sustainability and performance gains.
Falling behind competitors that design, test, and scale virtually.