How Digital Twins Can Reshape Our Entire Food System
Written by Nhi Corcoran
Beyond Energy Efficiency
The conversation around digital twins has largely focused on industrial optimisation and energy savings. While these applications are valuable—potentially saving $2 trillion annually according to recent estimates—we're missing the bigger picture. Digital twins represent something far more transformative: the key to creating resilient, sustainable food systems that can feed 9.7 billion people by 2050 without breaking our planetary boundaries.
The Current Crisis Hidden in Plain Sight
Right now, 733 million people face acute hunger daily while we waste one-third of all food produced. This isn't just a logistics problem—it's a systems failure. Our food value chains operate in silos, disconnected from the environmental, social, and economic realities that shape them. Climate change is accelerating this crisis: droughts reduce shipping through the Panama Canal by 49%, extreme weather disrupts supply chains at a cost of $184 million annually, and rising temperatures force fish species to migrate 70 kilometers per decade.
Traditional sustainability approaches—carbon accounting, ESG reporting, offset programs—treat symptoms rather than addressing root causes. They're backward-looking, siloed, and fail to capture the interconnected nature of our challenges.
Digital Twins: The Missing Link for Systemic Change
Digital twins aren't just virtual replicas—they're living, breathing models that continuously ingest real-time data to create actionable intelligence. Unlike static simulations, they evolve, learn, and adapt. This makes them uniquely suited to tackle the complexity of global food systems.
Digital twins can transform agricultural production systems and supply chains, curbing greenhouse gas emissions, food waste and malnutrition, offering possible remedies across six critical supply chain steps: agricultural inputs, primary production, storage and transportation, food processing, distribution and retail, and consumption.
Imagine a digital twin that doesn't just track your supply chain's carbon footprint, but models how climate patterns, socio-political tensions, and market dynamics interact to affect your operations. Picture being able to test different scenarios: What happens if drought hits your key supplier region? How does a trade embargo affect your distribution network? What's the social impact of switching suppliers on local communities?
Real-World Applications Across Sectors
Agriculture and Food Production
Leading companies are already pioneering this transformation. Digital twins provide real-time insights into soil conditions, crop health, irrigation needs, and pest management, supporting decision-making and increasing overall sustainability. For instance, soil monitoring digital twins coupled to sensors track moisture, temperature, organic matter, and pollutants, guiding fertiliser dosage and plant density with direct impact on environment, human health, and production costs.
The market potential is massive: AI in agriculture in the U.S. is projected to increase from $1.7 billion in 2023 to $4.7 billion by 2028. Companies are using digital twins to create virtual models of entire agricultural ecosystems, from fields and facilities to crops and livestock, enabling them to optimise yield while minimising environmental impact.
Manufacturing and Industrial Applications
Schneider Electric's LeVaudreuil site uses digital twins of its plant installations to optimise energy management (-25%), reduce material waste (-17%), and minimise CO2 emissions (-25%). The company demonstrates how sustainability and efficiency work together—while helping reach net zero by 2025, these digital twins also create more cost-effective operations.
Other manufacturing leaders show similar results: LG Electronics factory in Changwon, Korea improved productivity by 17%, product quality by 70%, and reduced energy consumption by 30% using real-time production data integrated into their digital twin system.
Infrastructure and Smart Cities
In Italy, Acquedotto pugliese invested 3.4 million euros to create digital twins of water infrastructure, preventing leaks and malfunctions through real-time monitoring. Meanwhile, Rotterdam harbor uses digital twins to simulate tidal levels and optimise ship traffic, preventing vessels from waiting unnecessarily and consuming fuel.
Digital twins can reduce a building's carbon emissions by 50%, significantly enhancing sustainability efforts, while implementing digital twins can improve operational and maintenance efficiency by 35%.
From Reactive to Regenerative
The industrial digital twins mentioned focus on optimisation within existing systems. We need to go further. The vision is digital twins that don't just make current operations more efficient—they help redesign entire value chains to be regenerative by default.
Consider these possibilities:
Proactive Risk Management: Instead of reacting to supply chain disruptions, anticipate them weeks or months in advance
True Impact Measurement: Move beyond Scope 1, 2, and 3 emissions to understand your full socio-ecological footprint
Circular by Design: Model how waste from one process becomes input for another, creating truly circular value chains
Social Justice Integration: Ensure your sustainability transition doesn't leave communities behind by modelling social impacts alongside environmental ones
The Technology Stack Enabling Transformation
The convergence of several technologies makes this transformation possible:
AI-Powered Analytics: Digital twins' ability to consider at once all the factors that could impact a sustainability outcome gives this technology an edge over older modeling techniques. Companies like ACCIONA Energía achieved 4.6% reduction in energy consumption and increased production capacity by 16 m3/h through AI-optimised energy recovery systems.
IoT Integration: IoT sensors monitor everything from soil conditions, water consumption, and animal health to pest activity and equipment maintenance in real time, providing the continuous data stream that makes digital twins truly dynamic.
Cloud Computing and Edge Analytics: This infrastructure enables the processing of massive datasets from multiple sources while maintaining real-time responsiveness.
The Data Challenge—and Opportunity
The biggest barrier isn't technology—it's data. Not the lack of it (we're drowning in sustainability data), but the challenge of finding relevant, up-to-date, actionable information for your specific use case.
Organisations typically follow processes built over many years based on legacy modeling and analytics techniques or even intuition. Digital twins offer a fresh analysis, revealing scenarios that don't seem logical at first but make sense based on actual data and analysis.
For example, a company using a digital twin to plan a warehouse found that a larger facility with more loading docks—which would cut truck idling time and emissions—was actually the better environmental choice than the smaller warehouse they initially assumed would be more sustainable.
Overcoming Implementation Barriers
Despite the promise, significant challenges remain:
Technical Complexity: If the benefits of digital twins are to be fully leveraged, the potential negative technical and social–ecological effects must be assessed and mitigated.
Cost and Accessibility: Lower-middle income economies are unable to make use of the technology due to the expertise, methods and infrastructure involved, creating a geographical divide in implementation.
Skills Gap: The technology requires multidisciplinary expertise combining agriculture, computer science, and sustainability knowledge.
A Call for Systems Thinking
The global market for digital twins is set to increase from about €16.42 billion in 2024 to €240.11 billion by 2032, with an annual growth rate of 39.8%. Manufacturing is expected to be the fastest-growing sector, but the real opportunity lies in extending this thinking beyond industrial efficiency to systemic transformation.
The climate crisis demands that we move from incremental improvements to regenerative redesign. Digital twins offer us an unprecedented opportunity to model, test, and implement the just transition our planet needs. Not just optimising current systems, but reimagining them entirely. Not just reducing harm, but creating positive impact. Not just surviving the climate crisis, but building the resilient, equitable future we all want to live in.
We're democratising sustainability by making complex systems thinking accessible to every organisation, from startups to multinationals. Because the scale of change we need requires everyone to be part of the solution.
The question isn't whether digital twins will revolutionise sustainability—it's whether we'll use them to optimise the status quo or to transform it entirely. The choice is ours, and the time is now.
What's your vision for how digital twins could transform your industry? Let's discuss in the comments.
Sources & further reading
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Boston Consulting Group. (2024). Mainstreaming food innovation. World Economic Forum. https://www3.weforum.org/docs/WEF_Mainstreaming_Food_Innovation_2024.pdf
CargoNet. (2023). 2023 Q2 theft trends. https://www.cargonet.com/news-and-events/cargonet-in-the-media/2023-Q2-theft-trends/
Climate Trace. (2024). Global emissions data. https://climatetrace.org/
Destination Earth. (2024). Digital twin platform. https://destination-earth.eu/
Food and Agriculture Organization. (2024). The state of food security and nutrition in the world 2024. FAO.
Hexagon. (2024). 2024 digital twin statistics. https://hexagon.com/resources/insights/digital-twin/statistics
Our World in Data. (2024). Sustainability metrics. https://ourworldindata.org/
Pylianidis, C., Osinga, S., & Athanasiadis, I. N. (2021). Introducing digital twins to agriculture. Computers and Electronics in Agriculture, 184, 105942.
Schneider Electric. (2023, May). How manufacturers can use digital twins for sustainability. World Economic Forum. https://www.weforum.org/stories/2023/05/digital-twins-manufacturing-sustainability/
Swiss Re Institute. (2023). Complex supply chains research. https://www.swissre.com/institute/research/topics-and-risk-dialogues/economy-and-insurance-outlook/complex-supply-chains.html
TechTarget. (2024). How digital twins can help support sustainability. TechTarget Sustainability. https://www.techtarget.com/sustainability/feature/How-digital-twins-can-help-support-sustainability
Tzachor, A., Richards, C. E., & Jeen, S. (2022). Transforming agrifood production systems and supply chains with digital twins. npj Science of Food, 6, 1-4.
United Nations Department of Economic and Social Affairs. (2024). World population prospects 2024. UN DESA.
Verdouw, C., Tekinerdogan, B., Beulens, A., & Wolfert, S. (2021). Digital twins in smart farming. Agricultural Systems, 189, 103046.
World Bank. (2025, January 17). Food security update. https://reliefweb.int/report/world/food-security-update-january-17-2025
World Economic Forum. (2023). How manufacturers can use digital twins for sustainability. https://www.weforum.org/stories/2023/05/digital-twins-manufacturing-sustainability/
