Noshin Kagalwalla, Vice President & Managing Director of SAS India, shares his perspective on the challenges and opportunities in AI adoption, offering pragmatic approaches for Indian businesses to harness AI’s potential for measurable ROI. From fostering sustainable growth in AI investments to unlocking the transformative potential of Generative AI in sectors like banking, healthcare, and public services, Noshin underscores how AI can serve as a cornerstone for India’s growth story. He also highlights the critical role of leadership in ensuring responsible AI practices, demonstrating how ethics and transparency can shape a future where technology truly serves humanity.
Many Indian companies are cost-conscious, which often delays AI adoption despite its benefits. How can businesses strike a balance between making substantial investments in AI and ensuring a clear return on investment (ROI)?
At SAS, we prioritize a phased approach for our clients, where enterprises can start small, demonstrate measurable impacts, and scale based on clear, strategic outcomes. According to our recent survey, Data and AI Pulse: Asia Pacific 2024 survey, about 40% of organizations across the Asia Pacific, including India, aim to triple their AI ROI; the pressure to deliver quick results is high, yet it’s crucial to understand that AI initiatives need time to yield sustainable outcomes.
Indian organizations are progressing steadily in AI implementation, especially large enterprises with established infrastructure and processes.
While AI promises market expansion, cost savings, and enhanced productivity, many find it challenging to invest without a clear path to tangible returns. This creates a delicate balancing act—companies are eager to harness AI’s potential but must be mindful of the significant upfront investments required. To justify greater AI adoption, organizations must make strategic, well-calculated investments that align with their business goals, ensuring they realize AI’s benefits and accordingly scale up their AI investments. Presently, over 27% of Indian organizations are focused on short-term outcomes rather than focusing on transformative outcomes.
Further, the AI investment approach of Indian organizations should combine external expertise with robust internal capabilities, such as AI modeling, cloud computing, software development, and analytics, allowing companies to build their AI maturity gradually. By aligning AI projects with business goals like customer satisfaction and operational efficiency, organizations can strike the right balance, realizing meaningful ROI while ensuring long-term, sustainable AI benefits.
Generative AI (Gen AI) has seen a rapid rise in global interest. How do you see Indian enterprises adopting Gen AI, and what sectors do you think will benefit most from this technology?
Indian enterprises are increasingly recognizing the potential to drive transformative outcomes with GenAI. While enthusiasm for Gen AI is high, especially with expectations for significant ROI, it’s essential for organizations to strategically focus on value-driven applications that enhance business productivity and operational efficiency. The sectors that will benefit more from Gen AI are Banking, Insurance, Government, Healthcare & Life Sciences where Gen AI can create an impact through personalized customer/citizen experiences, predictive analytics, and process automation. We recently drove a public sector project to enhance query responses with GenAI – by automating the extraction and interpretation of information from scanned PDF documents, response times were minimized, errors reduced, and resource allocation optimized, ultimately leading to efficiency in public communication, and fostering greater engagement and trust.
What role do you see AI playing in addressing India-specific challenges, such as in sectors like healthcare, agriculture, and education?
By leveraging AI across these critical sectors, India can enhance essential services and drive inclusive growth – in agriculture, for instance, AI-driven analytics supports climate resilience by offering climate monitoring and predictive insights, allowing farmers to adapt their practices to changing conditions and secure sustainable yields. Precision agriculture benefits from real-time data on soil health, crop needs, and weather, ensuring precise resource use that boosts productivity and reduces waste.
Additionally, AI aids in risk mitigation by forecasting adverse weather and pest outbreaks, equipping farmers with proactive strategies to minimize potential losses. In healthcare, AI extends access to care through predictive diagnostics and telemedicine, especially in underserved areas. Advanced techniques like computer vision on medical images improve early disease detection, while fraud detection tools identify irregular patterns, reducing risk in healthcare services. In education, AI-powered adaptive learning platforms deliver personalized learning, tailoring curriculums to individual strengths and needs. This approach extends quality resources to remote areas, enabling equitable access and helping students reach their potential.
The report stresses the importance of human oversight in AI training to mitigate bias and ensure responsible decision-making. What role should leadership play in fostering a culture of responsible AI usage?
As the C-suite takes on greater roles in integrating AI, leadership’s responsibility in fostering a culture of responsible AI usage becomes paramount. Executives must champion practices that emphasize human oversight, especially during model training, where AI foundations for behavior and decision-making are established. By promoting transparent processes, active bias mitigation, and thorough documentation, leaders can ensure that AI platforms are both responsible and trustworthy. Additionally, the commitment to ethics and accountability should extend to collaborations with external and internal partners, reinforcing a culture where AI initiatives align with the company’s core values and stakeholder expectations.
At SAS, the Data Ethics Practice (DEP) guides our efforts to help employees and customers deploy data-driven systems that promote equity. Comprised of experienced data scientists, developers, and others passionate about data’s power to uplift, the DEP ensures our platforms, people, and processes are human-centered.