MIT SMR India Maps India’s AI Readiness in New Study
The research offers a comprehensive look at how India measures up on AI adoption, talent, and infrastructure as businesses race to compete globally
News
- Sovereign Wealth Funds chase AI infrastructure boom
- AI Capex Boom Could Turn Into Investment Bust, BIS Warns
- Indian IT Firms See Agentic AI Opening $400 Billion Opportunity
- OpenAI Hires Uber Veteran Prabhjeet Singh for India Push
- Adani, Jabil Plan AI Data Center Hardware Platform in India
- Arun Misra May Take over as Vedanta CEO in August
MIT Sloan Management Review India is set to unveil a much-anticipated report that charts India’s AI maturity and highlights the execution hurdles it faces.
Based on a nationwide AI readiness survey, the report will focus on where companies are positioned on the AI maturity curve and how that aligns with the overall strategy, governance, and modernization plans.
The study examines the foundation needed for AI to scale across enterprises, which ranges from infrastructure and data systems to governance frameworks and organizational alignment. It also examines how AI is being integrated into products, processes, and decision-making, as well as the challenges firms encounter when scaling from pilots to operations.
Responses have been drawn from senior technology and data executives across industries, including CIOs, CTOs, CDOs, and leaders of engineering, analytics, and digital transformation, spanning both long-established enterprises and digital-first firms.
The research also taps executive perspectives to show where ambition meets readiness, capturing how leaders balance bold AI goals with the practical steps needed to deliver results.
The report compares results from across sectors, highlighting execution gaps, and setting out recommendations on sequencing investments, building internal capability, and strengthening governance. It also assesses whether India’s rapid digital and infrastructure gains are enabling enterprises to shift from experimentation to sustained AI adoption.
The findings provide a baseline for leadership teams under pressure to deliver measurable outcomes from AI programs.

