TCS: How AI and Digital Twins Drive Sustainability

Artificial intelligence presents a complex sustainability paradox. While seen as instrumental for advancing environmental goals, AI technologies are also notable contributors to global emissions.

The 2025 TCS Digital Twindex Report suggests that today’s technology allows enterprises to balance profitability with purpose.

It finds that digital twins, AI, IoT and Green IT are helping to transform sustainability from a compliance issue into a driver of competitiveness.

The report outlines how sustainability is evolving from a risk mitigation strategy to a wider regenerative business model.

This new model focuses on restoring ecosystems in harmony with economic growth.

Organisations that use AI-powered digital twins can simulate the ripple effects across value chains.

This allows them to anticipate and lessen supply chain disruptions while optimising the use of resources.

The result could be a move from linear reactive business models to circular regenerative frameworks that create new value.

Haley Price, Head of Sustainability at TCS North America, adds: “Businesses are looking to move from linear to circular [...] Often these regenerative capabilities are self-funding.”

A tech ecosystem for sustainability impact

According to TCS’s findings, emerging technologies are creating powerful ecosystems. These integrate sensors, AI digital twins and cloud platforms to measure and optimise environmental footprints in real-time.

Hemakiran Gupta, Head of Global Sustainability Services at TCS, says: “If we can bring the technologies that are available today and stitch them together [...] organisations will build purpose-led resilient businesses.”

This integration supports a new generation of adaptive operational platforms that can adjust to changing environmental, economic and social conditions.

By operationalising large datasets from sources such as energy meters and supply network enterprises can feed AI models that forecast risks and suggest actions to improve efficiency and reduce emissions.

The predictive power of digital twins

Digital twins function as the real-time nerve centre for these sustainability efforts. By creating dynamic virtual replicas of physical systems, they enable anticipatory, adaptive and intelligent operations.

“Digital twins are a powerful tool for sustainability, acting as a predictive brain that uses real-time sensor data to optimise operations,” explains Zeeshan Rashid, TCS Global Head Advisory for Sustainability.

This synergy between digital twins and AI allows businesses to model and implement eco-friendly solutions, paving the way for a more sustainable future.

Through the continuous analysis of operational data, these AI-driven virtual models can identify inefficiencies, test alternative scenarios and drive proactive interventions while minimising the need for expensive physical trials.

Navigating AI's sustainability credentials

AI can accelerate sustainability work by synthesising vast data points across supply chains, offering insights that would be impossible to achieve manually. This capability can lead to faster ESG reporting, risk assessment and scenario planning.

However, the energy demands of AI pose a major challenge. The computational intensity of training models and running simulations results in high energy consumption and emissions. This highlights the need for ethical AI deployment.

Haley Price says: “Every successful business will be using AI in the future [...] This means that every business must have a specific approach in place to ensure that their AI efforts are responsible, ethical and ultimately help to make the world a better place."

In response, organisations are increasingly using Responsible AI frameworks to balance the promise of AI with its environmental footprint.

This approach helps ensure AI acts as a catalyst for ethical and equitable sustainability.

Speaking in the report, Amanda Gardiner of the UN Global Compact, says: “What excites me about Generative AI is turning data into action. AI lets you go beyond reporting to truly equip teams with the ability to use data strategically.”

The integration of these technologies forms the basis of Industry 4.5, an era defined by augmented human-machine collaboration and pervasive digital resilience.