How AI-ready are India's founder-led B2B businesses, actually.
The Index scores a cross-sector sample of founder-led B2B businesses in India — D2C, healthcare, professional services, manufacturing, and hospitality — using only public-data signals, so no company's cooperation is required to be scored.
Five dimensions, scored from public data only.
No company is asked to participate. Every score is built from what is already public — careers pages, tech-stack signals, product pages, and founder activity — so the Index can be run again on the same terms as it scales.
Data infrastructure
20 ptsWhether customer and operations data is centralized enough to feed AI tools, read from careers pages, detected tech stack, and CRM mentions.
Process documentation
20 ptsWhether core workflows are defined well enough to automate, read from SOP and systems-role hiring signals.
AI tooling adoption
20 ptsLive evidence of AI already in the stack, read from job postings, product pages, and changelogs.
Decision-maker readiness
20 ptsFounder and leadership public posture on AI, read from LinkedIn activity, interviews, and panel appearances.
Website and product AI-surface
20 ptsWhether the company's own site or product is AI-legible — structured data, schema, and AI-answerable content.
Cross-sector, not single-industry.
The sample spans D2C, Healthcare, Professional services, Manufacturing, Hospitality — founder-led B2B businesses at a comparable stage, so a score means the same thing regardless of which sector a company sits in.
Reported by sector, not by name.
No individual business in the sample is identified or scored publicly. Every business contributes anonymously to its sector's average — the Index reports where each sector stands, not where any single company stands.
Overall average across 40 founder-led businesses, cohort 1 (July 2026)
| Sector | Sample size | Average score |
|---|---|---|
| Healthcare | 8 | 52/100 |
| Professional services | 8 | 50/100 |
| Hospitality | 8 | 44/100 |
| D2C | 8 | 43/100 |
| Manufacturing | 8 | 36/100 |
The overall average is 45/100. Across 40 founder-led businesses, only 8 — one in five — cross 60, the threshold at which AI adoption is structurally supported rather than improvised.
Process documentation is the strongest dimension (10.9/20) while AI tooling adoption (8.0/20) and decision-maker readiness (7.8/20) lag furthest behind. Most businesses are more ready for AI than their adoption shows — the constraint is decision-making, not infrastructure.
Manufacturing is the least AI-ready sector at 36/100, despite above-average process documentation — the readiness is structural, the adoption is absent. Healthcare leads at 52/100.
One in three businesses scores below 35 — no meaningful public evidence of data infrastructure, AI tooling, or leadership engagement with AI.
Cohort 1 is a pilot sample of 40 businesses, scored from public signals on a single research date. Scores are directional, not audited — and because the sample skews toward publicly visible businesses, the true average is likely lower than reported. The Index is re-run with the same rubric each quarter.