AI Surveillance Useful In Monitoring Challenging Terrain, Detecting Real-Time Threats: Rajendra Kumar

Secretary (border management) says to be effective in securing and managing borders, stakeholders need to synergise efforts through tech-intensive surveillance.

Source: https://www.etvbharat.com/en/bharat/ai-surveillance-useful-in-monitoring-challenging-terrain-detecting-real-time-threats-rajendra-kumar-enn26021903615

By ETV Bharat English Team

Published : February 19, 2026 at 3:46 PM IST

By Gautam Debroy

New Delhi: Stating that Artificial Intelligence (AI) can play an important role in transforming border management by enhancing and strengthening India’s ISR (Intelligence, Surveillance and Reconnaissance) ecosystem, Rajendra Kumar, Secretary (Border Management), said on Thursday that technologies like AI-powered surveillance sensors, drones, etc. can be very useful in monitoring challenging terrain and detecting threats in real time.

“AI can also play an important role in resource optimisation and optimal deployment of our border guarding forces for effective management of border areas. By enabling faster, data-driven decisions, AI can significantly improve efficiency in managing complex border security challenges,” he said, in an exclusive interview with ETV Bharat.

When asked whether AI has been used in border management, Kumar said, “As these technologies are constantly evolving, various stakeholders managing the borders would need to synergise their efforts through tech-intensive surveillance to be effective in securing and managing our borders. The use cases for deploying AI in border management are also constantly evolving.”

AI For Defence

Kumar said AI can act as a critical force multiplier in national defence, by accelerating decision-making, enhancing surveillance, and optimising logistics.

“AI-powered systems can analyse vast amounts of satellite, drone, and sensor data, to detect border intrusions and identify threats in real time. In cybersecurity, AI can identify and mitigate threats faster than humans, securing critical infrastructure. AI can drive unmanned autonomous vehicles (UAVs) and robotic systems for high-risk reconnaissance, protecting personnel,” he said.

According to Kumar, AI can also enable predictive maintenance of military equipment, ensuring operational readiness. “Ultimately, AI increases battlefield intelligence, agility, and efficiency,” he said.

Improve Governance, Services, Last-Mile Delivery

The border management secretary also said that AI can improve governance, delivery of citizen-centric services and last mile delivery, by automating administrative tasks, using predictive analytics for data-driven policymaking and fostering transparency.

“Citizen-centric services can be improved via multilingual AI chatbots, personalised services in various domains like health and education, and faster, automated grievance redressal. For this, the government needs to develop a full AI stack, comprising AI compute infrastructure and models, which will enable various ministries and departments to quickly develop and deploy their own applications for various use cases. Together, these innovations can enhance public service delivery, making it more efficient and inclusive,” he said.

AI Summit A Showcase Of Whole-Of-Nation Approach

“I think hosting the India AI Impact Summit 2026 is a major achievement for the country, which will enhance its global leadership in digital and emerging technologies. It helps in bringing the focus sharply on ‘AI for Development’ and in prioritising tangible, population-scale solutions using AI,” said Kumar.

He said the summit showcases our unique “whole-of-nation” approach towards the development and deployment of AI, utilising Digital Public Infrastructure (DPI) to democratise technology and ensure equity in access.

“This initiative also helps bridge the global AI divide, showcasing how AI can drive sustainable growth and empower underserved communities,” Kumar said.

India A Leading AI User & Creator

According to Kumar, India is rapidly emerging as a leading AI user and creator, focusing on a ‘bottom-up’ approach through population-scale applications and DPI. “Ranked among the top three nations in the world in AI competitiveness, India is leveraging its massive talent pool and a rapidly growing start-up ecosystem, with over 30,000 AI-focused start-ups to drive innovation at scale. Its light-touch regulatory approach, combined with its rich and diverse data, positions it as a critical and unique player in the global AI landscape,” said Kumar.

To further develop India’s AI ecosystem, Kumar said we need to focus on boosting our sovereign AI capabilities and build localised, multilingual AI-driven solutions in diverse domains, such as healthcare, education, agriculture, logistics, etc.

(The above interview was published on February 19, 2026 on ETV Bharat. It is available at: https://www.etvbharat.com/en/bharat/ai-surveillance-useful-in-monitoring-challenging-terrain-detecting-real-time-threats-rajendra-kumar-enn26021903615)

Dr. Rajendra Kumar on AI, cyber resilience and India’s digital statecraft vision

Dr. Rajendra Kumar outlines how AI, DPI and cyber resilience are reshaping gover ..

Create a “UPI for AI” as a Digital Public Infrastructure

Source of image: Generated by the author using AI

Artificial Intelligence (AI) technology is advancing rapidly and the AI models are becoming more and more complex and capable. This is being driven by increasing computational resources, massive data availability and record investments being made in developing ever larger large language models (LLMs) with hundreds of billions of parameters. However, many of the most prominent LLMs are proprietary or closed-source, which may pose significant barriers in their usage by small businesses and start-ups due to the high costs involved in their subscription. There are also a large number of open-source AI models available, including many small language models fine-tuned for specific domains or use cases, which can be used freely by anyone. However, these models have their own individual Application Programming Interfaces (APIs) and protocols that may require separate integrations for each model in various applications. This model fragmentation makes the entire process quite cumbersome and inefficient for developers developing applications for various use cases and users trying to seamlessly switch between models to discover the best one suited for their specific requirements.

Can a unified interface like that of UPI be developed for open-source AI models for easier access, interoperability and discoverability? Developing such a unified interface as a Digital Public Infrastructure (DPI) can address these concerns. The key factors for success of UPI lie in its open architecture, interoperability, and instant real-time transactions through Virtual Payment Addresses (VPAs) or mobile numbers. This creates a level playing field for various payment apps and services. Similarly, an open network of AI models would allow developers to swap between different models from different providers through a Unified Model API without rewriting their application’s core logic. Each model can be provided a Virtual Model Address like that of VPAs in UPI for routing the request to the correct model. Such an architecture would also allow for seamless interoperability between models from different providers based on accuracy, speed or specific domain requirements.

Such a Unified Interface (UI) for AI platform requires several steps for implementation. First, standardization is required to address the issue of API fragmentation in the AI ecosystem. This would involve defining compliant APIs, model data and Input-Output (IO) formats, and a virtual address system for each model. A universal standard would also require broad industry buy-in, which can be addressed through a combination of policy measures and engagement with the industry.

Secondly, a central routing and arbitration layer incorporating a central public registry of AI models would need to be created for intelligent routing of user’s requests to the best-suited model based on performance, costs or domain specific requirements. This central routing layer would also ensure interoperability.

Thirdly, a governance and regulatory compliance layer would need to be created to ensure fair access, maintain security and prevent misuse. This would involve defining security standards for authentication, data privacy and encryption to protect sensitive data shared with the AI models. It would also require a compliance framework to be put in place with clear rules to address AI bias, transparency and accountability. A dispute resolution mechanism would also need to be established.

Last, but not the least, a systematic drive for adoption of the UI for AI would need to be undertaken to ensure that all the model providers are onboarded through a broad consensus for uniform API standards. Continued engagement with them would also be required to keep the ecosystem robust and secure. Start-ups and application developers can be provided with incentives to build applications on top of the unified interface. Government ministries and departments can train specific AI models using their own domain datasets and undertake large-scale development of AI-driven applications for their use cases using this unified AI interface. This would drastically cut down the time required for developing and going-live with their applications.

The concept of a “UPI for AI” as a digital public infrastructure is both feasible and desirable and needs to be actively pursued to simplify model access and enhance interoperability. This would also encourage innovations in AI technologies, model training and their deployment in a large number of use cases. For maximum impact and accessibility, such an endeavour needs to be undertaken by the government through its IndiaAI Mission. This would also help in ensuring security, data privacy and regulatory compliances.

(The above article appeared on October 30, 2025 in The Economic Times online. It is available at: https://economictimes.indiatimes.com/tech/artificial-intelligence/create-a-upi-for-ai-as-a-digital-public-infrastructure/articleshow/124943526.cms?from=mdr)

(The author is a senior IAS officer and currently the Secretary, Department of Border Management, Government of India. The views are personal.)

Digital India 2.0: Digital Transformation for Viksit Bharat @2047

Digital Transformation and Economic Growth

Source: Generated using Meta AI by the author

Viksit Bharat @2047 aims to transform India into a developed nation by 2047. Broadly, the vision of Viksit Bharat can be divided into five key thematic areas: thriving and sustainable economy; empowering citizens; innovation, science and technology; good governance and security; and enhancing India’s global standing. As India has achieved remarkable success in digitalising its economy under the Digital India programme, can this programme be reimagined to leverage digital transformation in these areas to achieve the vision of Viksit Bharat?

Digitalization can significantly contribute to a thriving economy. India’s over $400 billion digital economy in itself is a major contributor to the overall economy and its continued growth is essential for achieving the vision of Viksit Bharat. Digital public infrastructure (DPI) like Aadhaar and UPI have revolutionalised online identity authentication and payments and have empowered individuals and businesses. Similar DPI initiatives, public-private partnerships (PPPs) and leveraging Artificial Intelligence (AI) and other emerging technologies can digitally transform sectors like manufacturing, healthcare, education, agriculture, etc. and enhance economic growth.

Improving access to digital services and infrastructure and digital empowerment through initiatives like BHASHINI can enhance digital inclusion, particularly for disadvantaged communities.

Digital transformation is also essential for fostering innovation and technological advancement. It can also be used to promote green technologies and sustainable practices. Smart cities initiative is already showing how scalable digital transformation and PPPs can address challenges like sustainable urban planning and climate change. Digitalisation can also enhance good governance and improve India’s standing as a global leader in sustainable economic growth.

To achieve the vision of Viksit Bharat and create such an economy and society wide impact over the next two decades, the Digital India programme needs to be reimagined as a cross-sectoral mission based on a whole of government and whole of society framework.

This new mission, Digital India 2.0, needs to be architected on certain key foundations for accelerating digital transformation across various sectors. First, it needs to focus on creating world-class digital infrastructure including AI-ready data centres and high-speed connectivity through fibre and mobile reaching all villages. With AI emerging as a key platform technology that would drive transformation across various sectors in future, the need for making India a global hub for AI-ready data centres with high-performance hardware and robust network infrastructure cannot be overemphasized. Expansion of data centre infrastructure would also address the need to ensure data privacy, security and data storage within the country.

Second, digital government and digital services need to undergo a major transformation through a focus on delivering integrated, pro-active and personalised services using AI. This would require building a unified AI stack as a digital public infrastructure (DPI) comprising AI-ready data centres, access to curated data sets, and AI models and applications to enable the ministries and departments to develop their own use cases quickly.

Third, the growth of the digital economy needs to be accelerated so that its share increases to at least 25% of the overall GDP of $30 trillion by 2047 from its present level of around 11%. This requires sustained growth in electronics and semiconductors, IT-ITES, and emerging technologies, such as AI, 6G, quantum computing, IoT, etc. However, a major contribution to the growth of the digital economy is likely to come from digitalisation of the traditional sectors, e.g., agriculture, health, education, financial services, retail, etc. Building a vibrant start-up ecosystem in these domains is essential for achieving this goal.

Fourth, we need to revamp our legal and regulatory framework to support the rapid growth of the digital economy. The major issues that need to be addressed include concerns on data privacy, cyber security, accountability of online platforms including social media, and fairness and transparency of AI algorithms. Though privacy concerns have been addressed through the new Digital Personal Data Protection (DPDP) Act, a full revamp of the 25 year old IT Act needs to be undertaken to address these issues comprehensively.

Fifth, rapid advancements in strategic and emerging technologies with ownership of intellectual property is a sine qua non for becoming a global leader in digital economy. We need to quickly formulate national strategies in these critical areas and fund the flagship initiatives. The IndiaAI Mission is a step in the right direction. However, we need to build our own foundational models in AI to ensure strategic autonomy in this rapidly advancing technology. Similarly, a national policy on data governance also needs to be formulated to ensure easier access to data by all the ministries, states, industry, start-ups, researchers, etc. This would allow rapid innovations to happen in these technologies.

Last, but not the least, skilling and capacity building in digital technologies at all levels is vital for rapid growth in the digital economy. India should rightly aim at becoming the skill and talent capital of the world.

Digital India 2.0, with its focus on a whole-of-government and whole-of-society approach, can accelerate digital transformation across various sectors to achieve the vision of Viksit Bharat.

(The views expressed are personal.)

Transforming Governance with a Unified AI Stack

Source: Generated through AI by the author

With rapid advancements in artificial intelligence (AI), organisations are scrambling to implement the technology in their business processes and service delivery frameworks to improve efficiency and enhance citizen experiences.

AI is set to impact nearly every sector, but to harness its potential, organisations need an ‘AI-first’ strategy that includes scalable, flexible AI solutions for business transformation. This requires an integrated AI stack — comprising infrastructure, data, AI models, and applications — enabling AI deployment across various use cases. Can such an AI stack be developed as a digital public infrastructure (DPI) by the government to provide seamless, proactive services to citizens and businesses?

To create a DPI, it is essential to understand the components of an enterprise-level AI stack. The foundation of this stack is a compute infrastructure layer, which includes compute capacity, storage, networking and tools for developing, training and deploying AI models. This layer would utilise Graphics Processing Units (TPUs), Central Processing Units (CPUs) and Tensor Processing Units (TPUs) optimised for AI workloads. Cloud platforms offer scalability, while edge computing may be necessary for real-time services in remote or low-bandwidth environments.

The second layer consists of the data layer, which focuses on collecting, storing, cleaning and annotating data for use by the AI models. Data security and compliance with the privacy laws must be ensured through encryption, anonymisation and access control. Data comes from various sources like structured and unstructured databases, web, Internet of Things (IoT), Application Programming Interfaces (APIs), etc. It must be cleaned and prepared for the AI model training to enhance accuracy and fairness. Ministries and departments have created huge databases under the Digital India programme that can be shared to train AI models for delivering predictive and proactive services to citizens and businesses.

The next layer is the model development layer, which focuses on designing and training models on the processed data from the data layer to address specific use cases, such as text or image/video generation, predictive analytics, etc. This involves selecting suitable AI frameworks, libraries, algorithms for the type of AI tasks involved, their optimisation and validation. Many open-source options, including pre-trained foundational models, can be customised for specific domains. However, developing indigenous foundational models is crucial to ensuring strategic autonomy and creating world-class capabilities within the Indian technology ecosystem. This doesn’t need to be resource-intensive, as demonstrated by DeepSeek.

The developed AI model is then deployed or exposed through APIs or microservices enabling integration with the enterprise systems, web and mobile applications. Next comes the application layer, which integrates AI models into real-world systems to deliver AI-enhanced products and services. This may involve reengineering business processes, automating tasks and redesigning user interfaces. For example, an AI application for predictive analytics might generate advance warnings for heavy traffic at specific locations during peak hours and send automated alerts for immediate action.

Finally, the AI stack also needs to have a governance layer to ensure that the associated risks, if any, are managed and trust is built in the AI systems. The government’s IndiaAI Mission should focus on creating a common AI stack as DPI, which all ministries and departments can use to build their own AI applications. This will prevent duplication of efforts and resources and create a vibrant innovation ecosystem focused on transforming public services with an ‘AI-First’ strategy. The AI stack could also be made available to startups and the private industry to promote collaborative development and deployment of AI applications.

(The above article appeared in The Economic Times on February 9, 2025. It is available at https://economictimes.indiatimes.com/tech/artificial-intelligence/transforming-governance-with-a-unified-ai-stack/articleshow/118073623.cms?from=mdr. The views expressed are personal.)