By Prashant Rai, Sr Business Solutions Manager, SAS
As India accelerates its digital transformation journey, the government has taken a proactive stance in promoting artificial intelligence (AI) and analytics to enhance governance and improve public services. In 2023, the national-level India AI Mission was launched to strengthen the country’s AI ecosystem. This initiative includes setting up Data and AI Labs in Tier 2 and Tier 3 cities, developing innovation hubs for indigenous Language Models (LMMs), and creating robust frameworks for responsible AI implementation.
Over the past few years, the Indian government has embedded AI and data capabilities within flagship programmes such as Digital India, Smart Cities Mission, Ayushman Bharat Digital Mission (ABDM), and the PM-Kisan scheme.
The intent is clear: to evolve from data collection to insight-driven policy execution. States like Telangana, Maharashtra, and Karnataka have piloted AI-led projects for predictive maintenance, citizen grievance redressal, and precision healthcare. Globally too, governments are embracing AI for anticipatory governance, right from Singapore’s Smart Nation initiatives to Estonia’s e-Governance framework and India is now poised to lead in the Global South by institutionalizing data-led governance at scale.
Despite these advancements, many government organizations still face structural and operational challenges. Legacy systems, siloed data, limited infrastructure, and resource constraints hinder efforts to deliver timely, targeted, and transparent services. Data and AI offer a path forward by unlocking insights and enabling decision-making at scale.
How Data, AI, and Analytics Can Help with Sectoral Strategies
Agriculture
Farmers face multiple challenges including soil degradation, overuse of fertilizers, unpredictable climatic conditions across India’s 128 agro-climatic zones, and limited access to affordable insurance. AI-powered systems can enhance soil health monitoring by capturing real-time data on moisture, nutrient levels, and temperature to guide optimal irrigation and fertilizer use. Predictive analytics can forecast yields, assess risk more accurately, and make insurance more accessible.
SAS has partnered with both public sector and private companies in their agriculture initiatives globally, enabling real-time decisioning by integrating and analysing diverse data formats, including satellite and field images, sensor and IoT feeds, and large-scale transactional datasets. These capabilities allow timely advisories, targeted interventions, and continuous monitoring of agricultural programs to improve productivity, reduce risk and strengthen agricultural value chains.
Healthcare
Public health systems often struggle with identifying disease patterns, forecasting outbreaks, and targeting high-risk populations. Delays in fraud detection and resource allocation add to challenges. AI can revolutionize this by providing near real-time visibility into disease trends, healthcare claims, and treatment outcomes.
For instance, a state-run healthcare trust collaborated with SAS for an end-to-end solution across various stages of their claims process. The solution leveraged predictive modelling, exception reporting and network link analysis for prioritized alerts and case management tools to strengthen the institution’s fraud management capabilities.
Advanced analytics ensures that all mandatory documents are submitted at the time of pre-authorization and claim processing, while AI-driven OCR and document intelligence detect duplicate, forged, or tampered documents with high accuracy. This significantly reduces manual intervention and prevents fraudulent claims from entering the system.
Beyond resource forecasting, fraud detection, and other integration opportunities in Health Management Information Systems, AI-powered chatbots and triage tools also have the capabilities to streamline patient engagement and reduce staff workload.
Social Benefits
Delivering social welfare services efficiently remains a challenge due to fragmented beneficiary records, legacy systems, and a lack of a unified household identifier. AI and analytics can consolidate data across departments into curated repositories supported by a Quality Knowledge Base (QKB).
Such systems allow end-to-end coverage, from policy design and beneficiary enrolment to monitoring, impact assessment, and scenario modelling. This results in better targeting of benefits, automatic service delivery, and optimized budget utilization.
One of the major challenges faced by social security programs has been the accurate identification of eligible beneficiaries across multiple schemes. The risk of duplicate beneficiaries availing benefits from different departments, as well as the inclusion of ineligible beneficiaries, has been a persistent issue impacting scheme efficiency and fiscal discipline. SAS addressed this challenge in a recent initiative that involved seamlessly integrating large, complex datasets from more than 40 government departments into a unified analytics environment.
Using advanced data management and entity resolution capabilities, SAS enabled the creation of golden records for citizens, ensuring a single, trusted view of each beneficiary across schemes. This significantly reduced duplication and improved the accuracy of eligibility determination.
The E.A.S.Y. Approach to AI-Driven Governance
To make digital governance truly transformative, India must move from experimentation to execution using a structured framework — E.A.S.Y.: Evaluate, Accelerate, Support, and Yield. This approach captures the essence of how governments can institutionalize AI and data-driven governance to deliver measurable citizen impact.
E – Evaluate: Build a Data-Driven Evidence Base
Evaluation is the foundation of effective governance. Data and analytics enable policymakers to move beyond anecdotal decision-making toward evidence-based policy formulation. Through real-time dashboards, scenario simulations, and impact assessment tools, governments can continuously evaluate how schemes perform across regions, demographics, and income groups. Evaluation also fosters accountability, when citizens and auditors alike can see performance metrics transparently, governance becomes participatory and trusted.
A – Accelerate: Use AI to Speed and Scale Public Services
Acceleration is about infusing automation, intelligence, and scalability into public administration. AI and advanced analytics can fast-track service delivery, streamline back-office processes, and enable proactive decision-making. Acceleration is not just about speed; it’s about the ability of systems to learn, adapt, and scale with evolving citizen needs.
S – Support: Ensure Ethical, Inclusive, and Secure Systems
No digital transformation can succeed without trust. The “Support” pillar emphasizes the creation of systems that are ethical, inclusive, and purpose-built with strong safeguards for privacy, fairness, and accountability. AI systems must be explainable and auditable. This means that decisions made by algorithms should be transparent and justifiable. Bias detection models, consent management frameworks, and robust cybersecurity protocols must form part of every AI implementation.
Y – Yield: Deliver Tangible and Measurable Outcomes
The goal of digital governance is to yield measurable impact with improved citizen satisfaction, optimized public spending, and accelerated socio-economic growth. AI-driven governance should therefore include built-in performance metrics such as reduced grievance resolution time, improved service coverage, or increased policy adoption rates, for example.
These measurable results demonstrate how technology translates into development.
Yield also has a long-term perspective. By institutionalizing continuous learning, from data to decisions to outcomes, governments can evolve from being service providers to experience enablers, ensuring that every citizen interaction adds value and trust.
What Lies Ahead
India is laying the groundwork for a future where digital governance is not just efficient but anticipatory, adaptive, and citizen centric. Investments in digital infrastructure, skill development, and ethical AI practices will enable India to emerge as a global leader in data-driven governance. By fostering collaboration across central, state, and local bodies, supported by a vibrant private sector and academic ecosystem, India can ensure that digital transformation benefits every community.
By making governance E.A.S.Y., AI and analytics can help bridge the last mile and deliver smarter, fairer, and more sustainable outcomes for every citizen. In doing so, technology becomes not just an enabler of efficiency but a force for inclusion, trust, and national progress in the world’s largest democracy.