PRODUCTION – 26 March 2024, Rhineland-Palatinate, Oppenheim: The display of a tablet shows the points at which the vine is to be pruned. After uploading the scanned vine, the prototype app for smartphone and tablet evaluates the data using AI and specifies the pruning points. Pruning grapevines is a time-consuming process that requires specialist knowledge and skilled workers. Artificial intelligence should help with pruning. Photo: Andreas Arnold/dpa (Photo by Andreas Arnold/picture alliance via Getty Images)
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In agriculture, digital twins are emerging as a powerful way to manage resources more efficiently. These virtual replicas of farmland integrate real-time data from sensors, drones, and weather stations to simulate crop growth, soil health, and environmental impacts. Farmers can test strategies for irrigation, fertilization, and pest control in a risk-free virtual environment before implementing them in the field.
Institutions like Texas A&M AgriLife Research are building digital twins for South Texas crops, while ag-tech company LandScan has secured a patent for almond production optimization. By combining AI models with field-level data, these systems can forecast harvest outcomes six to eight weeks in advance, improving resource efficiency by up to 30% and increasing yields by as much as 20%.
Industry analysts estimate that 40% of large farms will be using digital twins by the end of 2025. This growth signals not only a significant expansion in the ag-tech market but also a compelling investment case, as improved productivity and reduced resource use directly align with sustainability goals.
Predictive Analytics For Energy Grids
Utilities around the world are turning to predictive analytics to make energy distribution more resilient and efficient. AI-powered platforms can forecast consumption patterns, integrate renewable energy sources, detect potential faults, and optimize the performance of entire grid systems.
Solutions like Schneider Electric’s Distributed Energy Resource Management System (DERMS) and Kognitwin Grid use AI models to balance demand and supply, preventing outages and enhancing reliability during extreme weather events. The Open Power AI Consortium, formed by the Electric Power Research Institute (EPRI) and Microsoft, brings standardized AI tools to more than 30 energy companies, fostering collaborative innovation and industry-wide adoption.
Electrical wires during high temperatures in Ashburn, Virginia, US, on Monday, June 23, 2025. Electricity use on the biggest US grid, which serves nearly a fifth of Americans from Washington DC to Illinois, is expected to climb to a 12-year high as intense heat spurs air conditioning needs. Photographer: Pete Kiehart/Bloomberg
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“The technologies that will truly scale are those that deliver impact across three dimensions: planet, people, and prosperity,” says Sol Salinas, Executive Vice President, Sustainability Lead, Capgemini Americas. “Sustainability is no longer a cost center; it’s a growth engine. Technologies that deliver financial value through efficiency, risk reduction, and new market opportunities will earn trust and investment.”
The investment case is strong: smart grid upgrades and predictive capabilities are driving billions in infrastructure spending. These systems are increasingly viewed not just as operational improvements but as critical climate adaptation measures that protect energy access during periods of instability.
Blockchain For Environmental Transparency
Blockchain technology is transforming how companies track and verify sustainability claims. Immutable ledgers now allow for precise, verifiable records of product origins, certifications, and environmental practices throughout supply chains. By capturing data in real time companies can detect fraud, automate compliance, and demonstrate transparency to regulators and consumers.
Beyond supply chain tracking, blockchain platforms are enabling innovative approaches to carbon and energy markets. Power Ledger’s peer-to-peer solar energy trading model allows consumers to buy and sell excess renewable energy locally, while blockchain-based carbon credit systems offer a secure and transparent marketplace for emissions offsets.
Recent developments in low-energy consensus mechanisms, such as Proof-of-Stake, are making blockchain more environmentally sustainable. This shift is encouraging broader adoption among corporations seeking both accountability and climate impact mitigation.
The Wave Of Sustainable Innovation Powered By AI And Big Data
For investors, the real story lies in how data creates measurable value across regenerative systems. “Data is the infrastructure that is driving the advantage of regenerative systems,” explains Nic Gorini, Managing Partner of Spin Ventures. “It unlocks resource, market, and operational efficiencies, and increases profitability across circular and regenerative value chains.”
Gorini points to upcoming regulations, such as the Digital Product Passport in the European Union, as accelerants for adoption. “You don’t manage what you can’t measure, and data makes regenerative systems measurable. That’s when the capital shows up.”
According to Gorini, the most transformative ventures will be those that simplify complexity into usable intelligence. “This is a platform shift. Ventures that abstract complexity into usable intelligence across land, logistics, retail, and health will dominate. They are building the Salesforce of natural capital.”
Viral Adoption And Market Potential
What makes these technologies go viral is the compounding value they create. AI models that predict soil health improve yields but also inform supply chains, which in turn influence consumer markets and even personal health. “AI and real-time data turn biological volatility into commercial foresight,” Gorini notes. “Whether predicting soil health, shifting inventory based on carbon profiles, or modeling climate-resilient sourcing strategies, these tools enhance agility and unlock margin.”
Salinas agrees that adoption depends on accessibility. “These technologies must be intuitive and embedded into education and workforce development. Startups that make sustainability simple, actionable, and auditable will shape the future.”
Investing In AI And Big Data For The Next Wave Of Sustainable Innovation
Startups have a chance to lead in areas where legacy systems fall short. Measuring the carbon impact of digital operations, providing hyperlocal climate intelligence, and building traceability infrastructure are all open opportunities. Larger corporations can accelerate adoption by acquiring or partnering with innovators.
For investors, the calculus is changing. Gorini frames it as the beginning of a new economic flywheel: “Lower input risk, higher asset performance, stronger brand equity, and compounding value over time. The market will price that in sooner than most expect.”
AI and big data have already proven their ability to transform industries. The next five years will test how effectively they can continue driving this wave of sustainable innovation gains while delivering returns to investors. The companies that succeed will be those that integrate these technologies not as add-ons, but as core elements of their strategy. The net-zero transition demands speed, precision, and scalability. AI and big data offer all three, making them not just tools for innovation, but essential engines of sustainable growth.
Source: https://www.forbes.com/sites/monicasanders/2025/08/30/how-ai-and-big-data-are-pushing-the-next-wave-of-sustainable-innovation/
