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AI Adoption Index 2.0: Tracking India’s Sectoral Progress in AI Adoption

August 29, 2024 1336 0 Digital Transformation Data Science & AI Community

AI Adoption Index 2.0: Tracking India’s Sectoral Progress in AI Adoption

The 2024 AI Adoption Index 2.0 highlights the significant advancements and opportunities in India's AI landscape at a time when the growth in the Indian AI marketis expected to mirror the global AI market growth rate of 25-35% over the next 3-4 years, and as AI technologies evolve rapidly driven by the transformative impact of Generative AI. The Index 2.0 studyoffers in-depth insights into the AI adoption trends across seven sectors and 500 surveyed companies covering BFSI, CPG and Retail, Healthcare, Telecom, Media and Entertainment, Energy and Utilities, Manufacturing, and Transport and Logistics—covering 75% of India's GDP.

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Key Highlights

India’s AI market is growing rapidly and has strong support tailwinds from multiple critical pillars–

  • India’s AI market is expected to grow at a 25-35% CAGR over the next 3-4 years, inline with global growth.
  • Strong national-scale support pillars have emerged – the centrally-funded IndiaAI mission, supportive policy framework, AI and GenAI-ready tech services industry and startup ecosystem, and India’s 2nd largest installed AI talent base.
  • Rapid digitalization by enterprise users – 70% of surveyed companies spend over 20% of IT budgets on digital and emerging technologies.
  • AI consumption has broadened and deepened through as-a-service models, embedded and productized AI offerings.

 

The 2024 AI Adoption Index is a bigger and differentiated assessment compared to the 2022 Index 1.0 framework–

  • Index 2.0 covers seven sectors representing 75% of India’s GDP, 500 surveyed companies, and nine assessment dimensions, compared to four sectors, 315 companies, and six dimensions in 2022.
  • Index 2.0 assesses enterprise AI execution ability over Index 1.0’s focus on strategic planning for AI.
  • Index 2.0 focuses on “Building Scale with AI” and the urgent action steps needed for this objective, vis-à-vis, Index 1.0 where the focus was on “Enabling Practical AI Execution”

 

India’s aggregate 2024 AI maturity is at the Enthusiast stage with a score of 2.47 on a scale of 4, 4 being the highest or Evangelist stage–

  • India’s 2024 AI adoption index score is 2.47 on a 4-point scale, compared to 2.45 in 2022, and 87% companies are in the middle stages of Enthusiast and Expert AI adopters.
  • There is a 2X rise in the number of companies in the Expert stage in 2024 compared to 2022, which is the next maturity stage after Enthusiast, and where scaled AI adoption is observed.
  • Factors that have improved since 2022 are – strong focus on data standardization, modernization of the IT stack and application portfolio, and embracing Cloud over on-premise. Companies have also taken measures to formalize AI risk, ethics, and governance frameworks.
  • Factors that need urgent attention are – leadership commitment to AI is inconsistent and it reflects in ad-hoc, PoC-driven strategy, budgeting and execution, use case selection is a major challenge, and AI-led innovation – self or partner-led – is very nascent and lagging.

 

Sectoral analysis, by each of the nine dimensions, reveals that manufacturing and telecom, media and entertainment (TM&E) companies have moved to the Expert stage, other sectors are catching, but healthcare is significantly lagging–

  • Manufacturing’s performance is due to dominance of automotive and electronics, while TM&E sector maturity is driven by digital-native business models.
  • 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.
  • E&U, manufacturing, and transport and logistics sectors have central IT teams leading AI efforts, though top leadership commitment to AI remains a major challenge across most.
  • BFSI, manufacturing, and transport and logistics companies have built robust AI risk frameworks, but healthcare, a data-sensitive sector, majorly lacks these processes.

 

Recommendations to accelerate AI adoption span across common foundational interventions to contextualized approaches based on enterprise need and propensity to utilize AI effectively–

  • In transitioning 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, gain knowledge of data regulations, and foster peer learning to overcome adoption barriers.

 

For a detailed read, download this free report.

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