Artificial intelligence and digital twins are increasingly pivotal in transforming business models toward sustainability and regeneration. A recent report from Tata Consultancy Services (TCS), The 2025 TCS Digital Twindex, highlights a significant shift in how companies approach environmental responsibility, moving from a reactive, compliance-focused stance to a proactive strategy that integrates sustainability into the core of their operations. This evolution is largely driven by the power of AI and digital twin technologies to create dynamic, real-time virtual replicas of physical systems, enabling businesses to simulate, predict, and optimize their environmental impact while enhancing operational efficiency and profitability.
The convergence of AI, digital twins, the Internet of Things (IoT), and Green IT is creating a new paradigm for businesses, allowing them to balance purpose with profit. By creating virtual models of their operations, companies can analyze the ripple effects of their decisions across complex global value chains, anticipate supply chain disruptions, and optimize resource consumption. This capability is critical in moving from linear “take-make-dispose” business models to circular, regenerative frameworks that restore ecosystems and create new value streams. The integration of these technologies is not just about mitigating risk; it’s about fundamentally redesigning business processes to be inherently sustainable and resilient in the face of climate change and other global challenges.
The Rise of Regenerative Business Models
The concept of a regenerative business model is gaining traction as companies recognize the limitations of traditional sustainability approaches. Unlike models that simply aim to reduce harm, a regenerative approach seeks to actively restore and improve the ecosystems in which a business operates. This involves a shift in mindset, from viewing sustainability as a cost center to seeing it as a source of innovation and competitive advantage. Haley Price, Head of Sustainability at TCS North America, notes that many regenerative capabilities are self-funding, which changes the conversation in the C-suite about the value of sustainability efforts. This shift is also driven by the increasing recognition that climate risk is business risk. Hemakiran Gupta, Head of Global Sustainability Services at TCS, states, “The beauty of accepting climate risk as business risk means companies will take more steps to reduce the risk.”
From Linear to Circular
A key aspect of the transition to a regenerative model is the move from a linear to a circular economy. Digital twins and AI are instrumental in this transition by enabling companies to design products and processes that are circular by design. This means creating products that can be easily disassembled, repaired, and remanufactured, and developing closed-loop systems where waste from one process becomes a resource for another. By simulating these circular systems, companies can identify opportunities to reduce waste, conserve resources, and create new revenue streams from what was previously considered waste. This not only benefits the environment but also enhances business resilience by reducing dependence on virgin materials and volatile commodity markets.
The Power of Predictive Simulation
Digital twins, at their core, are dynamic virtual models of physical objects or systems that are continuously updated with real-time data from sensors. When combined with AI, these virtual replicas become powerful tools for predictive simulation. Companies can use these “predictive brains” to test different scenarios and optimize their operations for sustainability without disrupting their real-world activities. For example, a manufacturing company could use a digital twin of its factory to test different production schedules to minimize energy consumption or to simulate the impact of using a new, more sustainable material. This ability to experiment in the virtual world before implementing changes in the physical world is a game-changer for sustainability innovation.
Optimizing Complex Supply Chains
Modern supply chains are notoriously complex and often a major source of a company’s environmental footprint. AI-powered digital twins provide a holistic view of the entire supply chain, from raw material extraction to end-of-life product management. This allows companies to identify inefficiencies, predict disruptions, and make data-driven decisions to improve sustainability. For instance, a company could use a digital twin to optimize transportation routes to reduce fuel consumption and carbon emissions, or to track the provenance of materials to ensure they are sourced ethically and sustainably. By providing this level of visibility and control, AI and digital twins are helping to create more resilient, transparent, and sustainable supply chains.
Navigating the AI Paradox
While AI is a powerful tool for advancing sustainability, it also presents its own environmental challenges. The training and operation of large AI models can be incredibly energy-intensive, contributing to carbon emissions and straining energy grids. This creates a paradox where a technology that is being used to solve environmental problems is also contributing to them. Recognizing this challenge is the first step toward addressing it. Companies are increasingly focused on developing and deploying “Responsible AI” frameworks that seek to balance the benefits of AI with its environmental and social costs. This includes efforts to develop more energy-efficient AI algorithms, to power data centers with renewable energy, and to be more transparent about the environmental impact of AI models.
The Future of Sustainable Operations
The integration of AI and digital twins into business operations is still in its early stages, but the potential for transformative change is immense. The global digital twin market is projected to grow significantly, from $10.1 billion in 2023 to $110.1 billion by 2028, indicating a rapid acceleration in adoption. By 2035, TCS predicts that AI-powered digital twins will be the standard for managing complex operations and supply chains. This will lead to a new era of “Industry 4.5,” characterized by deep collaboration between humans and machines, modular and adaptive systems, and a focus on both profitability and sustainability.
A Call to Action for Businesses
The transition to a sustainable and regenerative future will require a concerted effort from businesses, governments, and civil society. For businesses, the message is clear: embracing AI and digital twins is no longer a choice, but a necessity for long-term success. Companies that invest in these technologies will be better equipped to navigate the challenges of climate change, to meet the growing demands of consumers for sustainable products, and to unlock new opportunities for innovation and growth. As J. Carl Ganter, Managing Director at Circle of Blue, aptly puts it, “It’s our generational opportunity to think and act systemically… and combine AI, digital twins and human creativity to urgently model, test and choose the future we want.”
