Earlier this year, when Prime Minister Narendra Modi inaugurated the India AI Impact Summit 2026, the message was unambiguous: India is not content being a consumer of artificial intelligence. It intends to shape the technology’s global trajectory. For those of us building AI solutions that protect people, manage cities, and secure critical infrastructure, that declaration carries enormous weight and equally enormous responsibility.
The summit, the fourth in a series of global AI convenings, was the first to be hosted by a Global South nation. More than 100 countries participated, and the agenda was structured around three foundational pillars: People, Planet, and Progress. Urban infrastructure and public safety were not peripheral topics at this gathering. They were central to India’s pitch for what purposeful, impact-driven AI looks like at scale.
India is now the world’s fourth-largest economy, with a nominal GDP of $4.19 trillion in 2025. Its urban population is growing rapidly, and with over 100 smart cities under active development under the Smart Cities Mission, the country is attempting one of the most ambitious urban transformations in history. Yet this growth generates its own stress: denser cities, more complex traffic networks, higher footfall in public spaces, and security challenges that traditional infrastructure simply cannot handle.
Manual monitoring systems, whether for surveillance, traffic management, or incident response, cannot cope with this scale. The gap between what legacy infrastructure delivers and what modern Indian cities demand is not incremental; it is fundamental. This is precisely the space where AI-led safety and urban intelligence solutions are not just valuable, but indispensable.
The Government’s Push: From Policy to Platform
What distinguishes India’s current AI moment from earlier waves of digitisation is the depth of government intent. The IndiaAI Mission, led by the Ministry of Electronics and Information Technology (MeitY), is driving investment across compute infrastructure, indigenous AI model development, and large-scale capacity-building. The India AI Impact Summit’s seven thematic working groups explicitly included ‘safe and trusted AI’ and ‘resilience, innovation, and efficiency’ both of which map directly to urban safety and infrastructure applications.
Also read: How Videonetics Helped Bangalore Traffic Authority through AI-powered Solutions
The Global Impact Challenge, one of the summit’s marquee initiatives, called for AI applications in urban infrastructure among its priority categories. At the same time, the government’s AI governance framework is increasingly treating regulation as part of the design process. This is a mature approach that the private sector must match. Building AI systems for public safety demands the highest standards of accountability, accuracy, and privacy compliance from the outset.
What ‘AI-Led Safety’ Actually Means on the Ground
AI in public safety is often discussed in broad terms. On the ground, however, its value is measured in response time, reduced congestion, and incidents prevented before they escalate.
Across deployments in smart cities such as Vadodara, Namchi, and cities in Arunachal Pradesh, AI-powered video management and analytics platforms are delivering measurable outcomes: real-time threat detection and coordinated emergency response, adaptive traffic management that reduces congestion at key junctions, automated number plate recognition for law enforcement, and crowd monitoring that prevents dangerous aggregations before they escalate.
In Bengaluru, AI-based adaptive traffic control systems are already demonstrating significant reductions in travel time and signal wait times, with over 60 cities across India following similar implementation paths. On highways, intelligent video analytics are detecting wrong-way driving, fires, stalled vehicles, and pedestrian intrusions in seconds, enabling responses that manual monitoring would catch far too late, if at all.
These are not pilots. These are production deployments at city scale, managing tens of thousands of cameras across hundreds of thousands of square kilometres of geography. The Indian AI market is projected to reach USD 17 billion by 2027, growing at 25–35% annually. A significant and growing portion of that expansion is being driven by government-led smart city and public safety programmes.
The Enterprise Opportunity: Where the Next Wave Is Coming From
Yet if smart cities represent the established front of India’s AI-safety story, the enterprise segment is where the next, and arguably larger, wave of demand is building. India’s private sector has arrived at a shared realization: AI-powered video intelligence is not merely a security tool. It is a business intelligence layer with direct operational and financial impact. The Nasscom AI Enterprise Adoption Index 2.0 (2024), which surveyed 500 companies spanning BFSI, retail, energy, manufacturing, transport, and logistics, found that every one of these sectors has identified live AI use cases with measurable value. The challenge is no longer awareness, it is implementation at speed and scale.
In Oil & Gas and manufacturing, industries where a single safety lapse can cost lives and hundreds of crores, AI video analytics now monitor PPE compliance, detect fire and smoke in real time, flag equipment anomalies before failure, and provide continuous surveillance of restricted zones. In Aviation, AI integrates terminal monitoring, airside access control, cargo tracking, and passenger flow management into a single operational picture – tasks that are simply beyond the capacity of manual systems at modern airport scale. In BFSI, applications span branch surveillance and ATM security through to behavioural analytics, with India’s AI-in-BFSI market projected to grow at a CAGR of 28.8% through 2033 (IMARC Group).
Retail and Hospitality are leveraging AI video to move well beyond loss prevention, tracking footfall patterns, analysing queue behaviour, optimising store layouts, and improving guest experience through real-time occupancy intelligence. Education institutions are deploying AI-driven surveillance and access management across large, distributed campuses. In Logistics and warehousing, intelligent video monitors inventory movement, prevents pilferage, and enforces safety compliance around the clock – environments where AI is not a luxury but an operational necessity.
AI Across Industries: From Security Tool to Strategic Asset
What unites these applications, across sectors as different as oil refineries, bank branches, hotel lobbies, and factory floors, is a fundamental shift in how video data is understood and used. For decades, surveillance meant recording: footage captured, stored, and reviewed only after an incident. Today, AI transforms every camera into a real-time analytical instrument. The video feed from a factory floor becomes a safety compliance system. The camera at a retail entrance becomes a customer analytics engine. The sensor network across an airport terminal becomes a unified, proactive threat-detection platform.
This is what we call True AI, not retrofitted, rule-based detection, but deep learning-powered intelligence that understands context, adapts to environments, and generates actionable business insight rather than just alerts. With 20+ patented AI technologies and over 100 analytics capabilities, the platform is purpose-built to operate at the scale and complexity that India’s enterprises, and its cities, now demand.
Sovereignty, Standards, and the Road Ahead
One of the most important themes to emerge from the AI Impact Summit 2026 was India’s emphasis on sovereign AI, the ability to build, manage, and control intelligent systems domestically, without structural dependence on foreign platforms. For AI in public safety and urban infrastructure, this is not just a policy preference; it is a security imperative. Video data from city surveillance networks, traffic corridors, and critical infrastructure cannot be routed through external systems without significant risk.
Indian technology companies that have built their AI and deep learning capabilities indigenously, designing for data sovereignty, STQC compliance, and cyber-security from the ground up, are uniquely positioned to serve this demand. This is not merely a commercial opportunity. It is a responsibility to build AI that is accurate, auditable, and aligned with the rights of the citizens it is meant to protect.
India’s AI Impact Summit sent a clear signal: the era of discussing AI’s potential is over. The era of deploying it at scale, responsibly, inclusively, and with measurable impact, has begun. For India’s cities, its infrastructure, and the millions of citizens who depend on both, AI-led safety is not a future ambition. It is an urgent present reality. The question is no longer whether to build it. The question is whether we will build it well.
The article has been written by Tuhin Bose, Chief Technology Officer, Videonetics
