A Nasscom survey reveals that nearly 60% of Indian businesses confident in scaling AI responsibly maintain mature Responsible AI (RAI) frameworks, marking significant progress from 2023’s awareness phase to structured governance implementation.
The State of Responsible AI in India 2025, based on responses from 574 senior executives, identifies hallucinations (56%) as the primary risk, followed by privacy violations (36%), explainability gaps (35%), and bias/discrimination (29%). Large enterprises lead maturity at 46%, significantly ahead of SMEs (20%) and startups (16%), with BFSI (35%) and technology/media/telecom (31%) sectors demonstrating strongest governance.
Persistent Implementation Barriers Threaten Progress
Data quality shortages (43%) represent the dominant obstacle, compounded by regulatory uncertainty (20%) and skills gaps (15%). SMEs cite high implementation costs as their second major challenge, while large enterprises prioritize regulatory navigation. 90% of organizations invest in workforce sensitization and training, recognizing human factors as critical to responsible deployment.
Accountability structures remain C-suite dominated (48%) though departmental ownership grows (26%), with 65% of mature organizations establishing AI ethics boards despite effectiveness concerns.
Strategic Implications for India’s AI Leadership
Sangeeta Gupta, Nasscom SVP and Chief Strategy Officer, emphasized foundational importance: “Responsible AI becomes embedded in critical decision systems. India’s leadership emerges through inclusive, trustworthy deployment beyond mere compliance requirements.”
The report documents direct correlation between general AI maturity and robust RAI practices, positioning advanced enterprises to accelerate adoption while mitigating emerging risks. Healthcare (18% maturity) shows nearly half of firms actively strengthening frameworks.
Monitoring compliance remains challenging despite strong data protection confidence, highlighting need for enhanced observability across AI lifecycles. Nasscom advocates governance investments, talent development, and transparent frameworks to establish global benchmarks for societal-scale AI systems.
