India AI Machine Learning Market Size and Forecast by Offering, Hardware, Solution, Service, Application, Deployment Model, Organization Size, and End User Industry: 2019-2033

  Dec 2025   | Format: PDF DataSheet |   Pages: 110+ | Type: Niche Industry Report |    Authors: David Gomes (Senior Manager)  

 

India AI Machine Learning Market Outlook

  • In 2024, the Indian industry was valued at USD 1.30 billion.
  • Regional outlook suggests the India AI Machine Learning Market is expected to be USD 15.82 billion by 2033, registering a CAGR of 30.1% throughout the forecast period.
  • DataCube Research Report (Nov 2025): This analysis uses 2024 as the actual year, 2025 as the estimated year, and calculates CAGR for the 2025-2033 period.

Industry Assessment Overview

Industry Findings: The government’s IndiaAI Mission is reframing procurement and compute access by explicitly funding public AI compute, indigenous model development and startup financing; the Cabinet approval (Mar-2024) for IndiaAI — including plans for public GPU pools and foundational model support — makes it clearer that buyers and ministries will favour vendors that align with national capacity and skills programmes rather than purely offshore product pitches.

Industry Progression: Large hyperscaler commitments are converting into tangible on-ground capacity and partner programmes: Microsoft announced a US$3.0B investment in India to expand Azure cloud and AI capacity and build skilling partnerships (Jan-2025), which immediately expands hosting options and partner enablement for domestic enterprises and accelerates the commercialisation path from pilots to production.

Industry Player Insights: Company-led, India-specific commercialization is visible through strategic partnerships that localise capacity and skills: Microsoft’s follow-on strategic partnerships in India (announced Jan-2025) with government and industry players to enable sector-specific AI adoption and skilling show how vendor commitments in-country create partner programmes, skilling pipelines and localized deployment options that reduce vendor risk for regulated sectors and speed enterprise ML rollouts.

*Research Methodology: This report is based on DataCube’s proprietary 3-stage forecasting model, combining primary research, secondary data triangulation, and expert validation. [Learn more]

Market Scope Framework

Offering

  • Hardware
  • Solution
  • Service

Hardware

  • GPUs
  • TPUs
  • ASICs
  • Edge Inference Devices

Solution

  • Consumption-based Hosted Models & MLaaS (Model APIs, LLMaaS)
  • ML Platforms & MLOps
  • Automated Machine Learning (AutoML & AutoOps)
  • Pre-built Vertical ML Applications
  • ML Governance, Security & Monitoring Tooling

Service

  • Model Customization & Fine-tuning Services
  • Data & Labeling Services
  • Professional Services & SI

Application

  • NLP & Conversational AI
  • Computer Vision
  • Forecasting & Time Series
  • Recommendations & Personalization
  • Control & Robotics

Deployment Model

  • On-premise
  • Cloud-based
  • Hybrid

Organization Size

  • Large Enterprise
  • Mid Enterprise
  • Small Enterprise

End User Industry

  • IT and Telecom
  • Media and Entertainment
  • Energy and Power
  • Transportation and Logistics
  • Healthcare
  • BFSI
  • Retail
  • Manufacturing
  • Public Sector
  • Other
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