The Maharashtra Cabinet, chaired by Chief Minister Devendra Fadnavis, has approved the Maharashtra AI Policy 2026, setting an ambitious roadmap to position the state as a leading hub for applied AI innovation in India. The policy aims to attract investments worth Rs 10,000 crore and generate 1.5 lakh jobs by 2031. It outlines a comprehensive strategy centred on the creation of six AI Centres of Excellence, five AI Innovation Cities, and large-scale skilling initiatives to train two lakh youth in artificial intelligence technologies.
The initiative is being seen as a significant step in strengthening Maharashtra’s digital economy, while also aligning with India’s broader push to build sovereign capabilities in emerging technologies. Industry leaders have welcomed the move, highlighting its potential to accelerate enterprise adoption and large-scale deployment of AI solutions.
Karan Kirpalani, Chief Product Officer at Neysa.ai, said: “Maharashtra’s AI policy is a well-timed move, signalling serious intent not just to participate in India’s AI buildout, but to lead it. As this capacity rolls out, the next phase of value creation will depend on how effectively it is put to use. Real impact comes from embedding AI into enterprise workflows, navigating regulatory complexity, and reaching production at scale, especially in financial services, healthcare, and public systems where the stakes are highest. This also lays the groundwork for sovereign AI, where critical data, models, and capabilities are governed within India’s own regulatory context. At Neysa, we see one critical shift from access to AI, to effective deployment. This policy’s multiplier effect depends on enabling enterprises to move from experimentation to production, reliably, securely, and at scale. For Maharashtra, that is the path to becoming a globally relevant applied AI destination”.
Echoing similar sentiments,Dr. Vishal Gauri, Chief Executive Officer of Seclore, emphasised the importance of data security in enabling scalable AI ecosystems. “Maharashtra’s Rs 10,000 crore AI policy is a strong step toward building a large-scale, production-ready AI ecosystem. With a clear focus on Centres of Excellence, AI innovation hubs, and industry adoption, the policy moves beyond intent and lays the groundwork for real deployment at scale. What this policy gets right is that AI adoption at scale cannot rest on infrastructure alone. As this ecosystem evolves, data will increasingly flow across enterprises, government systems, and third-party environments becoming the backbone for how AI is trained, deployed, and continuously improved.
This shift makes Data Security Intelligence critical to the policy’s success. It is no longer enough to secure infrastructure or applications in isolation; organisations need a smarter posture: persistent visibility and control over data itself and an understanding of how it is accessed, shared, and used across AI pipelines. As AI models interact with sensitive enterprise and citizen data, ensuring granular usage control, policy enforcement, and auditability will be essential to maintaining trust and meeting regulatory expectations. AI leadership in the next phase will depend as much on secure and responsible data management as it does on model deployment speed. Embedding security at the data layer will be key to enabling scalable, compliant, and trusted AI adoption across sectors.”
