Responsible AI (RAI) has rapidly shifted from being merely an ethical consideration to a core business priority for Indian enterprises, with companies increasingly recognising its role in building brand integrity and fostering long-term stakeholder trust, according to a report launched by Nasscom on Thursday.
The report highlighted that Indian businesses are showing strong momentum in their RAI journeys. Around 30% of organisations have established mature RAI practices, while 45% are actively implementing formal frameworks, marking a positive trend compared to 2023. A key finding shows a direct correlation between AI capabilities and responsible practices: companies with higher AI maturity tend to have stronger RAI frameworks, with nearly 60% of businesses confident in scaling AI responsibly having mature practices in place. This progress spans organisations of all sizes. Large corporations lead at 46%, while SMEs and startups are gaining ground at 20% and 16%, respectively. Sector-wise, banking, financial services, and insurance (BFSI) leads at 35% maturity, followed by technology, media, and telecom (TMT) at 31% and healthcare at 18%.
“As AI becomes deeply embedded in critical decisions across finance, healthcare, and public services, responsible AI is no longer optional; it is foundational to building trust, ensuring accountability, and sustaining innovation. The real measure of India’s AI leadership will not just be in the scale of adoption, but in how responsibly and inclusively these systems are designed and deployed. For businesses, this means moving beyond compliance checkboxes to embedding responsible practices across the entire AI lifecycle. With the right investments in governance, talent, and transparent frameworks, India can set global benchmarks for trustworthy AI that serves society at large,” said Sangeeta Gupta, senior V-P & chief strategy officer, Nasscom.
The report also highlighted workforce enablement as a key focus, with nearly 9 in 10 organisations investing in training and sensitisation. Businesses feel most confident about meeting data protection obligations, though compliance related to monitoring AI remains a concern. Accountability is still largely top-down, with about 48% of organizations placing primary responsibility with the C-suite or board, while 26% now assign it to departmental heads. Governance mechanisms, including AI ethics boards and committees, are also strengthening, particularly among mature organizations, where 65% have constituted such bodies, though some remain cautious about their effectiveness.
Despite these advances, organisations continue to face significant challenges. Hallucinations (56%), privacy violations (36%), lack of explainability (35%), and unintended bias or discrimination (29%) are the most common risks. Key barriers include lack of high-quality data (43%), regulatory uncertainty (20%), and shortage of skilled personnel (15%). Regulatory uncertainty is a major concern for large enterprises and startups, while SMEs report high implementation costs as a significant obstacle, highlighting the diverse challenges across business sizes.