SAS, a global leader in AI and analytics, empowers governments and enterprises to turn data into actionable insights. Dr. Radhakrishna B, Director, Customer Advisory at SAS, in an exclusive conversation with Elets Technomedia, discusses how AI is transforming governance in India—enhancing citizen services, enabling real-time decision-making, supporting fraud detection, and promoting ethical, inclusive, and regionally adaptive technology adoption.
Digital governance requires multi-stakeholder collaboration. How does SAS collaborate with government bodies, academia, and industry to foster inclusive technology adoption?
At SAS, we recognise that digital governance is not a solo effort; it thrives on collaboration to ensure that technology adoption is inclusive, impactful, and sustainable. With a presence in over 134 countries and partnerships with more than 1,600 government departments and agencies, SAS brings deep domain expertise to solve complex public-sector challenges. Whether it’s tax and revenue optimisation, law enforcement analytics, or government operations, our AI and data-driven solutions are designed to deliver real outcomes.
We also believe in moving beyond the hype. Our collaborations, such as the Economist Impact Report we recently sponsored, help us understand the evolving needs of the public sector. The report highlights how AI can enhance service delivery, cybersecurity, and policymaking, offering a blueprint for governments to adopt intelligent automation responsibly.
We collaborate with academic institutions across India to help bridge the skills gap through curated courses and bootcamps, instilling the values of responsible innovation in the next generation of technologists. SAS is also part of CORE-AI, one of India’s multi-stakeholder coalitions that brings together think tanks, start-ups, research organisations, universities, and industry players to shape the responsible development, governance, and deployment of AI in India.
Your role involves customer advisory at SAS, focusing on AI and analytics. How can governments leverage AI-driven insights to improve policy implementation and citizen engagement?
Governments today sit on vast amounts of data, and AI is the key to unlocking its value. At SAS, we help public-sector organisations turn data into actionable insights that drive better policy outcomes and citizen services.
For example, we’ve partnered with entities such as MCGM, the Maharashtra Sales Tax Department, and the Odisha Mining Corporation to implement AI-driven solutions that enhance decision-making and operational efficiency. In the public safety domain, we’ve developed AI-ML models that transformed an emergency response system to be faster, smarter, and more responsive.
We’re also helping government bodies use generative AI to scan large repositories of documents, extract relevant information, and deliver it in a user-friendly format. This not only improves internal productivity but also builds public trust by ensuring transparency and timely access to information.
As AI adoption grows in governance, how can initiatives balance innovation with the urgent need for data privacy and ethical AI use?
It is critical to embed fairness, transparency, and accountability into every stage of the AI lifecycle. Addressing concerns around algorithmic bias, data privacy, and AI-driven decision-making requires well-defined governance frameworks.
Beyond policy, responsible AI also requires inclusive model development. This means ensuring datasets represent India’s diverse demographics, embedding ethical AI principles into public-sector solutions, and creating mechanisms for continuous AI auditing and risk assessment. Government-backed AI ethics boards and regulatory sandboxes can further help refine AI applications before large-scale deployment, reducing unintended consequences and bias.
Realising this vision requires active collaboration across governments, academia, industry, and society. Organisations like SAS are contributing to this collective effort through platforms such as CoRE-AI, where cross-sector collaboration helps shape ethical AI frameworks. Within SAS, our Data Ethics Practice is a guiding hand for our responsible innovation efforts, ensuring our platforms, processes, and services keep the focus on people with an “ethical by design” approach. We are committed to working with customers, partners, and academia to increase awareness of the need for AI that is ethical, equitable, and sustainable.
SAS has driven initiatives around AI-powered fraud detection. What are the regional strengths or challenges you see in scaling these solutions across diverse Indian states?
India’s diversity is both a strength and a challenge when it comes to scaling AI-powered fraud detection. On one hand, states with mature digital infrastructure and strong data governance are well-positioned to adopt advanced analytics solutions quickly. On the other hand, regional disparities in data availability, digital literacy, and policy readiness can slow down adoption in other areas.
That’s where SAS’s modular and scalable approach becomes valuable. Our solutions are designed to adapt to varying levels of digital maturity, allowing states to start small and scale as their capabilities grow. We also emphasise capacity building by working closely with local agencies to train teams, ensure data quality, and build trust in AI-driven decision-making.
Considering emerging technologies like generative AI, how do you foresee their impact on governance transparency and citizen trust?
Generative AI has the potential to revolutionize governance by bridging information gaps and enhancing transparency. For instance, it can power multilingual, conversational platforms that help farmers access real-time insights on weather, pest control, and market trends, making government services more accessible and citizen-centric.
Synthetic Data Generation (SDG) further amplifies this impact by enabling the creation of anonymized, statistically accurate datasets. These can be used for policy simulations, urban planning, and public health research without compromising privacy. SAS’s recent acquisition of Hazy has strengthened our capabilities in SDG to support governments in deploying generative AI responsibly. By ensuring data privacy and reducing bias in training data, we’re helping build AI systems that are not only effective but also trustworthy.
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India is expanding AI initiatives across states with unique socio-economic profiles. How should governance models adapt to regional variations while maintaining AI efficacy?
India’s diversity demands a flexible yet principled approach to AI governance. While the core principles of responsible AI—such as fairness, transparency, and accountability—remain constant, implementation must be tailored to regional contexts.
This means investing in digital infrastructure where it’s lacking, upskilling local talent, and designing AI models that are culturally and linguistically inclusive. Governance frameworks should allow for experimentation through regulatory sandboxes while ensuring that ethical standards are upheld.
At SAS, we believe that with the right balance of innovation and regulation, India can lead the way in using AI to deliver inclusive, citizen-first governance. Our commitment is to support this journey with solutions that are not just powerful, but also principled and adaptable.
How is SAS helping government organisations use advanced analytics to address real-world challenges?
Across India, SAS has partnered with various state governments to build solutions that make a real difference in people’s lives. One such initiative involved creating a State Resident Data Hub that supports over 12.5 crore residents, especially those from vulnerable populations. By streamlining the distribution of social benefits, this system ensures payments are accurate, timely, and reach those who need them most.
In the fight against fraud, SAS worked with a state government to strengthen its property tax analytics. Using anomaly detection and pattern recognition, the system flags suspicious activity and prevents revenue leakage. This resulted in greater transparency, stronger financial controls, and restored public trust.
Our solutions have also helped a state GST department improve operational efficiency and risk profiling. The department saw an 18% increase in revenue, demonstrating how data-driven governance can directly boost economic outcomes.
We’ve also deployed an AI-ML model for a state-level emergency response system, transforming how distress calls are prioritised and resources dispatched, resulting in around 60% faster response times. Our aim is to help government organisations move from reactive problem-solving to proactive, data-driven governance.
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