CIOInsider India Magazine
AI Use Cases in ESG: A Handbook for Business Leaders
Abhishek drives Brillio’s ESG strategy, spearheading initiatives in carbon neutrality, diversity and inclusion, and community impact — including the award-winning Brillio Bringing Smiles program. He actively contributes to several boards and advisory councils, including the UN Global Compact, IMT Ghaziabad, NSB, Indian Oil’s HR Vista, FKCCI, and ASSOCHAM.
The relationship between AI and ESG is increasingly important, as businesses can no longer ignore their environmental footprint while claiming to be technology-focused. The high computational requirements of AI development have a significant effect on energy consumption. For instance, major tech firms have seen a marked increase in greenhouse gas emissions in recent years, primarily due to the energy-intensive nature of AI and machine learning activities. This highlights the fragile equilibrium between technological progress and environmental sustainability. As AI development accelerates, the need for strong ESG practices becomes more urgent than ever. Companies must understand that sustainability and technological progress are not opposing forces but rather interconnected objectives. Abhishek R, Sr Director and Global Head - ESG, Brillio, shared more insights on the topic through an interaction with CIO Insider. Below are the excerpts from the exclusive interview.
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How do you perceive AI’s role in serving value in the workforce?
Research indicates that by 2030, a significant number of individuals will need training in various AI tools. It is expected that the adoption of AI will reduce work hours by 20 to 40 percent, leading to major transformations in the workforce. Although some roles may be eliminated, many new job opportunities will emerge. Those who effectively integrate AI into their responsibilities will be more likely to find success in their careers. AI will serve as a catalyst, and employees who master its use will have a competitive advantage. The extent to which individuals leverage AI in their current positions will influence their future success. As automated systems take over repetitive tasks, individuals can focus on more important projects, improving productivity and the overall quality of work within organizations.
What is the level of effectiveness of ESG
frameworks in promoting the responsible development and deployment of AI?
The growth of ESG adoption is increasing rapidly, as it represents the first framework requiring companies to provide transparent, data-backed evidence of their operations. This shift addresses the green-washing problem by enhancing corporate actions' visibility and measurability. Compliance is transitioning from being merely focused on data to becoming more insights-driven, and is expected to evolve into an approach powered by AI. ESG now encompasses a wider range of factors, including board structure, implemented frameworks, human rights, investments in employee development, pay equity, and data security. With AI integration, the compliance reporting process will become faster and more accurate, promoting greater trust and reducing redundancy. As more data is submitted by individuals, AI will be essential in verifying the authenticity of compliance claims, thereby further strengthening trust in corporate actions.
How does the synergy among technology partners, academic institutions, and industry organizations contribute to ESG initiatives?
CSR is typically seen mainly in terms of monetary contributions. Nevertheless, it's crucial to acknowledge the significance of intellectual resources, including the skills, knowledge, and experience brought by employees and volunteers. These assets, along with financial backing, greatly improve the efficacy of CSR efforts.
Human analysis can be labor-intensive, and this is where technology can provide more dependable data, richer insights, and effective solutions.
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What are your predictions for how technology, ESG, and regulatory environments will converge in the future?
I think the emphasis on ESG has increasingly shifted toward technology and is influenced by donor data in the aftermath of the pandemic. Numerous companies are taking advantage of this as a chance to create carbon data capture ventures, resulting in the development of a variety of tools for analyzing carbon data. From a business perspective, I believe that CSR in India has typically been regarded as an annual initiative; however, with the rise of technology and data accessibility, we can now anticipate more precise data, in-depth insights, improved information, predictive analytics, and benchmarks to gauge our performance against competitors. This progress will provide a clear assessment, allowing organizations to pinpoint what is performing well and what needs improvement. Human analysis can be labor-intensive, and this is where technology can provide more dependable data, richer insights, and effective solutions.
Additionally, concerns about data centers will continue to grow, as they are major consumers of energy and water; we should investigate the evolving models for these centers, especially by incorporating larger amounts of renewable energy. Therefore, many of these issues will come to the forefront as AI increasingly establishes its significant influence, backed by substantial financial investments in this sector.
