Rajasthan AI/ML Policy 2026 – Policy Update

Policy Update
Shalija Singh

Background

Artificial Intelligence (AI) and Machine Learning (ML) are increasingly shaping public administration, economic activity, education, healthcare, agriculture, and urban development. Their adoption can improve administrative efficiency, enable data-driven decision-making and create new economic opportunities. At the same time, government use of AI raises concerns regarding privacy, cybersecurity, algorithmic bias, transparency, accountability and unequal access.

Against this backdrop, the Government of Rajasthan launched the Rajasthan AI/ML Policy 2026 on 6 January 2026 at the Rajasthan Regional AI Impact Conference in Jaipur. Rajasthan’s need for a dedicated AI/ML policy arises from its growing digital-governance ecosystem and the need to establish a coordinated framework for using AI to modernise public services, strengthen institutional capacity, promote innovation and ensure that the benefits of AI reach different regions and sections of the state.

The Department of Information Technology & Communication (DoIT&C) is the nodal department. The policy seeks to modernise public service delivery, enhance transparency, catalyse innovation, create high-value employment and ensure equitable access to the benefits of AI. It is aligned with the state’s broader vision of Viksit Rajasthan 2047.

The policy’s vision is to promote responsible, inclusive and innovation-driven development through AI while strengthening governance outcomes, public service delivery, institutional capacity and economic growth. Its principal pillars are AI adoption in governance, AI skilling and capacity building, incentives for industries, and an ethical and responsible AI framework, supported institutionally by a proposed Centre of Excellence for AI (CoE-AI).

The policy is also designed as a force multiplier for Rajasthan’s existing policy architecture. It supplements the Startup Policy 2022, RIPS 2024, MSME Policy 2024 and Data Centre Policy 2025, rather than creating an entirely separate industrial ecosystem.

Functioning

The Rajasthan AI/ML Policy adopts an ecosystem-based approach involving government departments, startups, MSMEs, industries, research institutions, academia and technology partners.

AI Adoption in Governance

The policy promotes responsible deployment of AI across government departments to improve efficiency, effectiveness and citizen-centric service delivery. AI Rajasthan identifies applications across areas including agriculture, healthcare, education, urban development, public safety and environmental monitoring.

The policy’s governance approach is important because AI systems used in public administration can influence decisions affecting citizens. Therefore, deployment needs to be accompanied by institutional responsibility rather than treated merely as technological automation.

Responsible and Ethical AI

The policy establishes responsible AI as a central component. Its framework covers trustworthiness, reliability, safety, security, transparency, explainability, privacy protection, data governance, fairness, inclusivity, bias mitigation, human oversight and accountability. These provisions should be understood primarily as policy principles and implementation-oriented guidance rather than standalone, legally binding requirements; their enforceability would depend on their incorporation into applicable laws, rules, procurement conditions, departmental guidelines or other binding instruments. This distinction is important because the policy provides a framework for responsible AI adoption, while detailed operational and regulatory mechanisms may need to be developed during implementation.

This is particularly relevant to state-level governance because departments may use sensitive administrative and citizen data. The framework therefore attempts to ensure that efficiency gains do not come at the cost of transparency or citizen rights.

AI Skilling and Capacity Building

The policy is at an early stage of implementation, with initial efforts focused on building institutional capacity and developing an AI-ready ecosystem. The policy reports more than 10,000 skilling fellowships as an implementation indicator; however, the available information does not specify whether this figure refers to fellowships announced, enrolled, or completed. Therefore, the figure should be treated as a reported implementation indicator rather than evidence of completed training outcomes. In addition, 6,786 officers and employees have been trained, indicating early progress in strengthening AI-related capacity within the state government. 

Industry and Startup Support

The policy covers startups, MSMEs, industries and R&D institutions, with support extending to asset creation, skilling, intellectual property creation, green incentives, data-centre support and access to AI cloud and computing infrastructure.

Its integration with RIPS 2024, MSME Policy 2024, Startup Policy 2022 and Data Centre Policy 2025 enables AI enterprises to access a wider investment and innovation ecosystem.

Centre of Excellence for AI

The proposed Centre of Excellence for AI is intended to function as the state’s apex institutional hub for AI strategy, research, implementation and governance. Its proposed functions include research collaboration, ethical and regulatory guidance, startup support, AI use-case development, capacity building, monitoring and evaluation, and maintenance of a state-level AI knowledge repository. While the CoE-AI has not yet been operationalised, the implementation process has progressed towards institutional establishment. In May 2026, DoIT&C issued an invitation for proposals for the establishment and operationalisation of an AI Centre of Excellence in Rajasthan, indicating that the initiative had moved towards the procurement and institutionalisation process.

Performance

Since the policy was launched only in January 2026, a conventional two-to-three-year assessment of post-policy outcomes is not yet possible. Performance can instead be assessed through the pre-policy baseline and early implementation indicators available during 2026.

Pre-policy baseline

Rajasthan entered the AI policy phase with an existing digital-governance ecosystem. The Economic Review 2024-25 noted that the state’s Integrated Financial Management System (IFMS) contained financial and accounting data dating back to 2010-11 and was being positioned for AI integration to improve prediction and decision-making.

The 2025-26 Economic Review further recorded the launch of the AI/ML Policy and identified AI as a strategic instrument for public-service modernisation, transparency, innovation, employment generation and equitable access.

Early implementation indicators, 2026

Source: Government of Rajasthan, AI Rajasthan; Rajasthan Economic Review 2024-25 and 2025-26; DoIT&C; PIB.

The state has also moved towards developing the computational infrastructure required for AI. DoIT&C issued an RFP for the procurement of GPU servers at the Rajasthan State Data Centre (RSDC), bearing Tender No. F4.14(21)/RISL/Tech/ep/25-02778-8364507/BSDC-095, which was uploaded on 24 March 2026. The AI-CoE procurement process was also initiated. 

At the institutional level, the January 2026 AI conference resulted in MoUs with Google, IIT Delhi, National Law University Jodhpur and the Wadhwani Foundation for AI research, skilling, ethical frameworks and innovation. The policy document identifies potential use-case development in health, education, agriculture, infrastructure planning, water and tourism (Rajasthan AI/ML Policy 2026, p. 13).

These figures and developments demonstrate early policy mobilisation, but they should not yet be treated as evidence of final outcomes. The number of fellowships, partnerships or procurement processes measures policy activity rather than improvements in citizen welfare, productivity or governance.

Impact

Since the Rajasthan AI/ML Policy 2026 was launched only in January 2026, its impacts are largely prospective at this stage. The assessment therefore distinguishes between expected impacts based on the policy’s objectives and design, and early evidence of implementation, such as skilling initiatives, institutional planning, partnerships and procurement. These early indicators demonstrate policy activity but do not establish measurable improvements in service delivery, productivity or citizen welfare. 

Governance

AI may improve the speed and accuracy of government processes by analysing large datasets, identifying patterns and supporting evidence-based decision-making. Rajasthan’s existing digital infrastructure may provide a foundation for such applications. The Economic Review has highlighted the role of data analytics in supporting evidence-based policymaking across government projects.

However, AI adoption may also change the nature of administrative accountability. When algorithmic systems influence decisions, responsibility should not become diffused between software developers, vendors and government officials. Rajasthan’s emphasis on human oversight, explainability and accountability may help strengthen these safeguards, although its effectiveness will ultimately depend on operational implementation.

Human Capital

The policy’s skilling component is expected to contribute to creating an AI-ready workforce. It targets a broad group of beneficiaries, including students, professionals, government officials, teachers and youth, while the AI Rajasthan platform reports 10,000+ skilling fellowships. This suggests an effort to build AI-related capacity across both the public sector and the wider workforce. Nevertheless, the eventual impact should be measured through completion rates, certification, employment, entrepreneurship, wage outcomes and actual deployment of acquired skills rather than enrolment numbers alone. 

Innovation and Investment

The policy’s integration with Rajasthan’s startup, MSME, investment and data-centre policies may help lower institutional barriers for AI enterprises. The state’s hub-and-spoke model is intended to extend the ecosystem from the state level through divisions and districts, potentially reducing the concentration of AI activity in Jaipur.

The proposed CoE-AI may further strengthen this ecosystem by connecting government demand with academic research and private-sector innovation. 

Responsible AI

The most significant long-term impact may be institutional. By explicitly incorporating privacy, fairness, explainability, security and human oversight into a state AI policy, Rajasthan seeks to embed responsible AI principles before large-scale deployment. 

Emerging Issues

• Absence of long-term outcome evidence: The policy is still new, making a 2–3-year impact assessment difficult at this stage.
  Suggestion: DoIT&C should publish an annual AI performance dashboard covering projects, expenditure, beneficiaries, service-delivery outcomes, investment, employment and citizen satisfaction.
• Output versus outcome measurement: Fellowships, partnerships and AI projects show the level of activity, but do not necessarily reflect their actual impact.
  Suggestion: Each major AI intervention should have measurable KPIs such as reduction in processing time, cost savings, accuracy, accessibility and user satisfaction.
• Data privacy and governance: Greater use of government data can increase concerns around privacy and cybersecurity.
  Suggestion: High-impact AI systems should undergo documented risk assessments, data-quality checks, security audits and periodic reviews.
• Algorithmic bias: AI systems can sometimes reproduce biases present in datasets or arising from design choices.
  Suggestion: Bias testing, explainability standards, independent evaluation and grievance mechanisms should be mandatory for high-risk applications.
• Uneven departmental capacity: Departments have different levels of digital readiness and technical expertise, which may affect the pace of AI adoption.
  Suggestion: The CoE-AI should provide common technical standards, feasibility assessment, procurement support and capacity building for departments.
• Digital divide: AI-enabled services may leave out citizens with limited connectivity or digital literacy.
  Suggestion: Multilingual interfaces, assisted digital channels and district-level digital literacy initiatives should accompany AI-based service delivery.
• Computational infrastructure: AI requires substantial computing power, storage, cybersecurity and energy resources, which can pose implementation challenges.
  Suggestion: Rajasthan should develop shared public AI infrastructure while incorporating energy efficiency and cybersecurity into procurement standards.
• AI Procurement and Vendor Accountability: Clear AI procurement standards may be needed to assess system quality, data protection, transparency and interoperability. Establishing clear vendor responsibilities for data handling, security, system performance and potential harms will also be important for ensuring accountability in public-sector AI deployment. 

Way Forward

The Rajasthan AI/ML Policy 2026 provides a broad framework for integrating AI into governance, human-capital development and economic activity. Its combination of responsible AI principles, skilling, industry incentives, infrastructure development and institutional mechanisms gives the state a foundation for building a statewide AI ecosystem.

The immediate priority, however, should be moving from policy announcements to measurable outcomes. The government should develop a transparent monitoring and evaluation framework that distinguishes inputs, outputs and outcomes. Public reporting should track not only the number of AI projects or trained individuals but also improvements in service delivery, administrative efficiency, employment, investment and inclusion. Periodic independent audits of AI systems deployed by government departments could complement this framework by assessing accuracy, fairness, transparency, data protection and compliance with responsible AI principles.

The Centre of Excellence should become the principal institutional bridge between government, academia, startups and industry. It should undertake independent evaluation of AI use cases, establish common standards and support departments in moving projects from experimentation to responsible scale.

At the same time, responsible AI must remain an operational requirement. Privacy, cybersecurity, fairness, explainability and human accountability should be embedded into procurement, deployment and evaluation rather than treated only as guiding principles.

For Rajasthan, the success of AI policy will ultimately depend on whether technological adoption produces measurable public value. If the state can combine AI innovation with institutional accountability, human-capital development, inclusive infrastructure and robust governance safeguards, the Rajasthan AI/ML Policy 2026 can contribute meaningfully to the state’s Viksit Rajasthan 2047 vision and offer lessons for responsible AI governance at the sub-national level.

Selected References and Important Links

1. Government of Rajasthan, 2026, Rajasthan AI/ML Policy 2026, Department of Information Technology & Communication.
   https://ai.rajasthan.gov.in/ 
2. Department of Information Technology & Communication, Government of Rajasthan. (2026a). Policies & guidelines. https://doitc.rajasthan.gov.in/content/hindi/PoliciesandGuidelines.aspx 
3. Department of Information Technology & Communication, Government of Rajasthan. (2026b). Rajasthan AI/ML Policy 2026. AI Rajasthan. https://rising.rajasthan.gov.in/storage/app/public/files/pdf/rajasthan-ai-ml-policy-2026.pdf 
4. Department of Information Technology & Communication, Government of Rajasthan. (2026c). Tenders and procurement – AI-CoE and GPU infrastructure. https://doitc.rajasthan.gov.in/Content/Tenders.aspx 
5. DD News, 2025, Rajasthan Cabinet Approves AI-ML Policy 2026, Promotes Ethical and Responsible AI, DD News.
   https://ddindia.co.in/2025/12/rajasthan-cabinet-approves-ai-ml-policy-2026-promotes-ethical-and-responsible-ai/ 
6. ETGovernment, 2026, How Rajasthan’s AI-ML Policy 2026 Aligns Governance and Skilling with India’s AI Mission, ETGovernment, The Economic Times. https://government.economictimes.indiatimes.com/news/digital-india/rajasthans-ai-ml-policy-2026-pioneering-governance-and-skill-development/126411395  
7. Finance Department, Government of Rajasthan. (2026). Economic Review 2025–26.
   https://finance.rajasthan.gov.in/docs/budget/statebudget/2026-2027/Economicreviewe.pdf?utm_  
8. Pioneer News Service, 2026, Rajasthan CM Sharma Launches AI-ML Policy 2026, The Pioneer.
   https://dailypioneer.com/news/rajasthan-cm-sharma-launches-ai-ml-policy-2026 
9. Press Information Bureau, 2026, Launch of Rajasthan AI/ML Policy 2026 and related institutional partnerships. Government of India. https://www.pib.gov.in/PressReleasePage.aspx?PRID=2212007&reg=3&lang=1

About the Contributor

Shailja Singh is an undergraduate student of Political Science with an interest in public policy, governance, international relations and policy research.

Acknowledgement

The author sincerely acknowledges the IMPRI team for their guidance, valuable feedback, and continuous support throughout the preparation of this Policy Update.

Reviewers

Dolly kaushik & khushi

Disclaimer

This article is intended for academic purposes only. The views expressed are those of the author and do not necessarily reflect the views of IMPRI or any government.

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