The next frontier of AI is biological digital twins
Canada’s ambitions in artificial intelligence are often framed around software innovation, computing power and digital services. Policy debates focus on generative AI, productivity tools and automated decision-making in offices, schools and government.
These discussions matter. But they overlook an emerging frontier of artificial intelligence that is beginning to transform how societies manage living systems.
The next frontier of artificial intelligence will not only be digital. It will be biological.
Across agriculture, food production and environmental monitoring, a new class of systems is beginning to emerge: biological digital twins. These systems create dynamic computational models of living environments by integrating continuous data from animals, infrastructure, climate conditions and operational activities.
Unlike traditional monitoring tools, digital twins do not simply report what is happening. They simulate how a living system is likely to respond before decisions are made.
In sectors such as aerospace, advanced manufacturing and energy, digital twins have already transformed how complex infrastructure is managed. Engineers can test changes in virtual models before applying them to physical systems. Equipment failures can be predicted earlier and performance can be optimized continuously.
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A similar transformation is beginning to take shape in food production and that creates an opportunity for Canada.
If the country engages early, it can help shape both the technological and institutional architecture surrounding biological digital twins. If it waits until these systems are standardized globally, Canadian producers and policymakers may instead find themselves adapting to frameworks designed elsewhere.
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