Nasscom in partnership with EY has released its 2024 AI Adoption Index, highlighting significant advancements and opportunities in India’s AI landscape especially at a time when the growth in the Indian AI market, although at a nascent stage, is expected to mirror the global AI market growth rate of 25-35% over the next 3-4 years. The report underscores the rapid evolution of AI technologies, especially the transformative impact of Generative AI, which has revolutionized creative experimentation and catalysed innovation across industries.
The 2024 AI Adoption Index 2.0 surveyed 500 companies across seven sectors—BFSI, CPG and Retail, Healthcare, Telecom, Media and Entertainment, Energy and Utilities, Manufacturing, and Transport and Logistics—covering 75% of India’s GDP.
While India’s overall AI adoption maturity index remains at 2.47 on a 4-point scale, a marginal increase from the 2022 score of 2.45, several key trends are shaping India’s AI landscape. Majority of Indian organizations are progressing to the mid-level maturity stage, with defined AI strategies and initial implementation of select use cases, aiming to scale these solutions further. 75% of the surveyed organizations have AI strategy defined at PoC level, while 40% of the surveyed organizations show moderate to high maturity in PoC-to-production. To drive the leap from AI-ready to AI-first organizations, Indian enterprises will need to move beyond the PoCs to scale AI implementations.
Despite a slowdown in tech spending, AI budgets remain strong, with 40% of companies having dedicated AI funds and 64% allocating at least 5% of their tech budget to AI. However, while India is a major talent hub for AI, enterprises struggle to find domain-specific and strategic AI expertise, often starting with “AI-as-a-service” models. To boost AI adoption, Indian companies need “right-sized” operating models, combining internal and external talent, consistent leadership oversight, and AI Centers of Excellence (CoEs) to scale AI initiatives.
The report also states that while data standardization has improved, a more focused strategy is needed for AI-ready backend data security and access. Moreover, as AI has not yet scaled sufficiently for companies to develop robust research and innovation capabilities, enterprise IP creation in AI-related technologies remains limited. Despite rapid global adoption of Generative AI, Indian enterprises indicate a slower rate of adoption, likely due to data and use case readiness required to effectively leverage Generative AI. While sectors such as BFSI and retail are in the PoC stages of GenAI solutions, the majority of the legacy sectors such as energy & utilities and manufacturing are yet to start PoCs.
Speaking on the report, Sangeeta Gupta, Sr. Vice President & Chief Strategy Officer at nasscom, said, “As AI evolves from an emerging technology to a fundamental pillar of business strategy, Indian enterprises have a unique opportunity to lead this transformation. The 2024 AI Adoption Index demonstrates that while we’ve made significant strides, the journey from experimentation to widespread adoption requires decisive action and sustained commitment.”
The report also provides a detailed analysis of AI adoption across seven key sectors. While sectors such as BFSI, Retail & CPG, Energy & Utilities (E&U), Healthcare, and Transportation exhibit similarities in their propensity to identify AI use cases of benefit for their organizations, and in moving the use cases to PoC and production, sectors such as Manufacturing and Telecom, Media and Entertainment (TM&E) have moved beyond the PoC stage and are collaborating with industry disruptors in implementing AI solutions.
Over 50% of companies in BFSI, CPG and retail, E&U, healthcare, and TM&E sectors have a PoC-heavy AI approach, while 39% in manufacturing and 65% in transport and logistics focus on transformational AI strategies. Budget allocation also differs, with 55% of BFSI, CPG and retail, E&U, healthcare, and TM&E sectors relying on ad-hoc AI budgets, whereas more than 50% in manufacturing and transport and logistics have dedicated AI funding. Over 60% of organizations in E&U, manufacturing, and transport and logistics sectors have central IT teams leading AI efforts, though top leadership commitment to AI remains a challenge in sectors like transport and logistics and TM&E. Data standardization is fairly advanced, with over 60% of companies in BFSI, manufacturing, CPG and retail, transport and logistics, and TM&E having enterprise-level data standards. In terms of AI governance, around 35% of BFSI, manufacturing, and transport and logistics companies have robust AI risk frameworks, but many sectors, including healthcare, lack processes to ensure AI outcome compliance through regular audits.
To accelerate AI adoption and transition from AI-ready to AI-first, Indian enterprises, both large and SMBs, need to focus on several strategic actions. Large enterprises should prioritize data standardization, strategic partnerships for swift PoC-to-production transitions, and balanced AI use for both efficiency and innovation, while carefully managing AI risks and integrating sustainability into their AI strategies. SMBs should emphasize contextual use cases, explore partnerships with tech SMEs to jumpstart AI initiatives, ensure strong leadership commitment for agile PoC-to-production processes, gain knowledge of data regulations, and foster peer learning to overcome adoption barriers.
