The NASSCOM AI Adoption Index

Investments in Artificial Intelligence in India is still a small percentage (~1.5%) of the total worldwide spend. However, given its transformative nature and the rapid strides India has made in this space over the past few years, it is safe to state that the success of India’s Techade hinges on adoption of best-practices to convert this potential into tangible national value.

Considering the centrality of Artificial Intelligence as a technology and its contribution to India’s GDP, it is important to track, assess and monitor its adoption at the enterprise level.

NASSCOM have collaborated with Microsoft, Capgemini, Ernst & Young and EXL to bring the NASSCOM AI Adoption Index, the first-of-its-kind assessment in the Indian context. This comprehensive maturity assessment framework tracks and measures the degree of AI penetration in India and arrives at a composite score both at the country and sector levels.

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Key Findings

Four key sectors – Industrials and Automotive, Healthcare, Retail & CPG and BFSI are expected to contribute ~60% of the potential AI-driven value add to India’s GDP by FY 2026
India starts from a low base in terms of investment volumes but scores significantly higher than mature economies in AI skills penetration; 3.09 times the global average between 2015-2021
End-users see value in moving ahead on the AI adoption curve but are hamstrung by legacy systems and silo-ed data

AI strategy is not yet embedded with the broader corporate strategy for the majority; currently <15% have aligned their goals
Enterprise spending on Artificial Intelligence is still low; 67% allocate less than 10% of their IT budget to AI
50% need adequate data at the BU level to develop data standards
Building dedicated teams for AI (particularly is limited to less than 40%

Except for the Healthcare sector, the other 3 sectors score high on having a well-defined AI strategy
Majority of the companies across sectors have active POCs and defined use-case across multiple functions
Optimizing cost of operations is driving the majority to adopt AI; revenue growth and innovation also score higher

Quantifying the benefits of AI
Low maturity of the external ecosystem
Budgetary constraints
Cultural and behavioral challenges
Mature enterprises track the return on investments and PoC to production (35%), 45% track advanced digital RoI metrics

Continual impact assessment of AI projects
Integrating technology and business architecture
Streamlining IT and business alignment to weed out legacy
Continual upskilling in AI technologies ‘and’ domain
Effective lab-to-market for value-driven innovation

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