The State of AI in Indian Enterprise
Scoring ~55 of India's largest listed companies on a seven-signal framework — built from public evidence, not borrowed surveys.
Everyone says they're doing GenAI. Who actually is?
Instead of asking executives what they think they are doing, AIM examined what India's largest companies are actually doing — deployment by deployment, hire by hire.
India sits at the top of Operationalizing — past pilots, short of scale.
Five stages of enterprise AI
Awareness, no production AI
Pilots & POCs, few live
Multiple use cases in production
AI across functions, owned platforms
AI-native ops, revenue & moat
India 2026 sits at the top of Operationalizing.
Seven signals. One score.
Realised value — production use cases and GenAI/agentic deployments — carries 45% of the weight.
BFSI leads. Energy lags.
Seven sectors, ranked by composite score. The dashed line is the national average.
Inside each sector.
Tap any card for leaders, laggards, signature use cases and the 3-year outlook.
76% sit in the middle.
The Operationalizing-Scaling band is crowded. Only four firms reach Transforming.
Every company. Every score.
Filter by maturity band or sector. Tap any company for its signal breakdown, evidence and what would move the score.
| # | Company | Score | Band |
|---|---|---|---|
| 01 | Reliance Industries | 82 | Transforming |
| 02 | HDFC Bank | 81 | Transforming |
| 03 | ICICI Bank | 74 | Scaling |
| 04 | Bharti Airtel | 72 | Scaling |
| 05 | Jio (Reliance Jio) | 71 | Scaling |
| 06 | Bajaj Finance | 70 | Scaling |
| 07 | SBI | 68 | Scaling |
| 08 | Tata Motors | 67 | Scaling |
| 09 | Mahindra & Mahindra | 65 | Scaling |
| 10 | L&T | 64 | Scaling |
| 11 | Maruti Suzuki | 62 | Scaling |
| 12 | Sun Pharma | 60 | Operationalizing |
| 13 | Dr Reddy's | 59 | Operationalizing |
| 14 | Apollo Hospitals | 58 | Operationalizing |
| 15 | Reliance Retail | 58 | Operationalizing |
| 16 | HUL | 56 | Operationalizing |
| 17 | ITC | 55 | Operationalizing |
| 18 | Adani Green | 54 | Operationalizing |
| 19 | NTPC | 52 | Operationalizing |
| 20 | Axis Bank | 64 | Scaling |
| 21 | Kotak Mahindra Bank | 63 | Scaling |
| 22 | Asian Paints | 55 | Operationalizing |
| 23 | Hero MotoCorp | 52 | Operationalizing |
| 24 | Cipla | 54 | Operationalizing |
| 25 | Lupin | 50 | Operationalizing |
| 26 | Fortis Healthcare | 49 | Operationalizing |
| 27 | Trent | 48 | Operationalizing |
| 28 | Avenue Supermarts (DMart) | 45 | Operationalizing |
| 29 | Nestle India | 46 | Operationalizing |
| 30 | Power Grid | 42 | Operationalizing |
| 31 | Tata Power | 45 | Operationalizing |
| 32 | ONGC | 38 | Experimenting |
| 33 | Coal India | 35 | Experimenting |
| 34 | Vodafone Idea | 40 | Experimenting |
| 35 | Adani Enterprises | 48 | Operationalizing |
Where each sector is built — and where it is hollow.
A heatmap of seven sectors across the seven scoring signals. Hover or tap any cell for the rationale.
It is not capex.
- Named AI executive owning P&L impact
- Proprietary models and data moats
- AI tied to a published revenue or margin number
- AI ownership above the CIO
- Anything beyond hyperscaler pilots
- A disclosed outcome — saved cost or new revenue
3 · 5 · 10 years out
Operationalizing → low Scaling
Scaling. Agentic AI in production at scale.
Transforming. AI-native, top-3 globally.
Good, bad, or ugly?
Mostly good. The leading edge has moved from pilots to production — and the next five years decide who builds AI-native moats, not just AI-enabled workflows.
State of AI in Indian Enterprise 2026
A proprietary, repeatable measure of enterprise AI maturity — owned by AIM, not borrowed from surveys.
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