Infosys Q&A: How Can AI Create More Inclusive Cities?

As the pace of digital and green transformation quickens, AI remains a key driver—shaping not just smarter, but also more sustainable and inclusive urban environments.

AI’s potential—ranging from optimizing energy consumption and cutting emissions to revolutionizing public services and enhancing accessibility—is increasingly vital to achieving net zero goals and fostering equitable innovation.

Balakrishna (Bali) DR, Executive Vice President and Global Services Head for AI and Industry Verticals at Infosys, is dedicated to advancing AI and intelligent automation across all service areas and internal processes, boosting both operational efficiency and strategic value for the organisation.

Here, Bali shares the role AI plays in net zero efforts and how Infosys’ solutions contribute to this movement.

In your own words, what is Infosys and how does it contribute to the tech space?

Infosys is a global leader in digital services and consulting, partnering with enterprises worldwide to help them navigate disruption and lead in a rapidly evolving digital landscape.

A key pillar of our impact in the technology sector is our unwavering focus on innovation. Infosys has consistently led the adoption of emerging technologies and modern delivery models to drive business transformation. 

Today, we are pursuing an AI-first strategy and making significant investments to embed artificial intelligence across our service offerings and internal operations. 

Through platforms such as Infosys Topaz — a comprehensive suite of AI-first services, solutions and platforms powered by Gen AI — we enable clients to unlock new value, drive efficiency at scale and build intelligent, connected ecosystems.

Our approach to AI is grounded in the belief that technology should enhance, not replace, human potential. 

While AI brings powerful capabilities for automation, prediction and decision-making, human judgment remains essential for strategic direction, contextual understanding and ethical responsibility. 

This belief shapes our talent agenda as well. We are actively reskilling our workforce and redefining roles to ensure our people are prepared to lead in an AI-powered economy.

Our commitment to Responsible AI reinforces this philosophy. We focus on building ethical, transparent and inclusive AI systems that prioritise fairness, accountability and long-term trust across our operations and client ecosystems.

Could you share more about Infosys’ broader AI strategy and the key goals you’re currently working towards?

At Infosys, we approach AI through a structured three-layered framework: foundational models, enabling platforms and business-specific AI applications. 

While we have made a deliberate choice not to pursue frontier models, we are investing significantly in small- to mid-sized language models tailored to enterprise needs. 

For example, we have developed a small language model (SLM) for the banking sector, fully integrated with our Finacle product suite. We are also fine-tuning models for IT operations and cybersecurity, packaging them as part of our client service offerings.

At the heart of our AI strategy is Infosys Topaz, our AI-first suite of solutions that leverages large language models and Agentic AI to build autonomous, goal-oriented systems.

We work closely with leading cloud providers, hyperscalers and open-source communities to accelerate AI adoption across the enterprise landscape. 

Through Topaz, clients can rapidly deploy pre-built AI solutions or co-create customised platforms. 

A recent example with a global telecommunications client illustrates this agility, where we delivered production-ready AI use cases within four weeks, significantly reducing time-to-value. 

These intelligent agents are designed to perceive, plan and act independently, enabling enterprises to reimagine and optimise complex workflows across sectors such as financial services, logistics, product innovation and customer engagement.

As we scale these capabilities, we remain committed to embedding the principles of transparency, fairness and accountability across all aspects of our AI programmes. 

This commitment extends to guiding clients in their responsible AI journeys and supporting policy development that fosters inclusive and equitable AI outcomes.

From an application standpoint, we are prioritising AI use cases that address real-world challenges, everything from combating climate change to enhancing public services. 

We see AI as a transformative force for nations such as the UK, enabling advancements that are sustainable, inclusive and ethically grounded. 

We are actively aligning with government initiatives, including the AI Opportunities Action Plan, to drive responsible innovation across sectors like healthcare, energy and agriculture, all with the broader aim of achieving net-zero carbon goals.

How is Infosys working with policymakers and organisations like the Centre for Data Ethics and Innovation to ensure AI systems are transparent, accountable and fair?

As AI becomes more deeply embedded in critical infrastructure and influences a growing number of everyday experiences, the need for transparency, fairness and accountability is paramount. These principles are essential to earning and sustaining public trust. 

At Infosys, Responsible AI (RAI) is a strategic priority, reflected in a range of initiatives designed to promote ethical, secure and inclusive AI practices.

A core element of our RAI agenda is close collaboration with public policy and regulatory institutions to help shape responsible frameworks for AI governance. 

These efforts are aimed at fostering confidence in AI technologies while ensuring that their deployment aligns with societal values.

We work actively with the UK government and its agencies, including the Responsible Technology Adoption Unit (RTA), formerly known as the Centre for Data Ethics and Innovation (CDEI). Now part of the Department for Science, Innovation and Technology (DSIT), the RTA plays a vital role in advancing responsible innovation. 

Our collaboration with DSIT includes contributing to the AI Opportunities Action Plan, which is focused on promoting safe and ethical AI adoption across key sectors.

As AI adoption grows, how are you seeing organisations addressing the environmental impact of AI systems?

There is increasing recognition among organisations of the environmental impact that comes with scaling AI. As AI adoption grows, so does its energy consumption and carbon footprint. 

Training large AI models requires substantial computational power, which raises critical questions about sustainability. In response, many companies are taking active steps to adopt energy-efficient AI architectures, streamline model training processes and implement low-carbon AI strategies. 

The aim is to reduce environmental impact while preserving the performance and scalability that AI demands.

Encouragingly, AI is also becoming a key part of the solution. 

Organisations are leveraging AI to optimise resource usage, forecast climate-related events and directly reduce emissions. Advanced models are processing vast amounts of environmental data to deliver more accurate predictions on weather patterns, natural disasters, and long-term climate trends. 

Beyond forecasting, AI is being applied to optimise core resource consumption such as water and energy. 

By analysing usage patterns, these systems can identify inefficiencies and recommend targeted conservation strategies, helping organisations make measurable progress toward sustainability goals.

The shift to net zero is pushing businesses to rethink their business models, often taking on new capabilities like energy storage. What role can AI and innovation have in supporting these organisations to adapt?

We are witnessing organisations across multiple sectors such as retail, consumer packaged goods, supply chain and logistics accelerating their shift toward electric fleets. 

This transition, combined with the growing adoption of decentralised renewable energy sources, is fundamentally transforming the global energy landscape. 

Businesses are at the centre of this evolution as energy grids become more complex with power generation distributed across local communities.

This decentralisation offers new opportunities for companies to actively participate in the net-zero transition, going beyond their traditional roles as energy consumers.

However, these opportunities come with significant challenges. 

Managing complex micro-grids, deploying advanced smart infrastructure and integrating on-site generation or storage often lie outside the core expertise of industries like logistics, real estate and telecommunications. 

This is where innovation and AI play a critical role. 

AI-powered digital platforms are vital in rapidly reskilling teams to meet the demands of these new business models. They enable organisations to modernise their energy systems and manage consumption intelligently without detracting from their primary business focus.

Additionally, emerging models such as Energy-as-a-Service (EaaS) are making this complex transition more accessible. EaaS provides businesses with the necessary tools and insights through flexible contracts. 

Supported by AI, these solutions allow organisations to improve energy efficiency, optimise sustainable supply chains and manage energy use across their operations effectively. 

AI serves as the intelligence layer that not only makes this transformation possible but ensures it is highly effective and sustainable.

How is AI currently being deployed to optimise traffic flow and reduce emissions in urban areas? Are there any measurable impacts you have observed so far?

AI is emerging as a powerful enabler for cities striving to become more resilient and sustainable. It is actively employed to optimise traffic flow, reduce energy consumption and enhance resource allocation across various urban services. 

Smart city initiatives are successfully leveraging AI to tackle challenges such as congestion, poor air quality and energy inefficiency, thereby making urban environments more livable and sustainable for residents.

In traffic optimisation specifically, AI systems analyse real-time data from road networks, public transportation and connected vehicles. This enables dynamic traffic management, allowing AI to intelligently adjust traffic signals, reroute vehicles around incidents or congestion and alleviate bottlenecks. 

These improvements contribute to reducing vehicle idling, lowering fuel consumption and crucially, decreasing harmful emissions.

While the full, quantifiable impact of these initiatives is still being assessed as they scale, early outcomes are encouraging. In cities where AI-driven traffic management systems have been deployed, measurable benefits such as reduced commute times and improved air quality have been observed. 

These efforts support broader national environmental and innovation objectives, demonstrating how AI can enhance urban efficiency while improving quality of life.

Explore the latest edition of Sustainability Magazine and be part of the conversation at our global conference series, Sustainability LIVE. 

Discover all our upcoming events and secure your tickets today.

Sustainability Magazine is a BizClik brand