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According to a recent BCG report, India’s domestic Artificial Intelligence (AI) market is projected to more than triple to $17 billion by 2027, making it one of the fastest growing AI economies globally. While headlines focus on AI’s dramatic advances in creative tools or large language models, a quiet revolution is taking place in the back-end systems that power cities – logistics, energy, mobility and workforce orchestration – that are having a profound impact on how we live, move and work.
AI can make everyday systems smarter, faster, and more humane. One of the least discussed, yet high-impact areas of this change is urban commuting, a daily routine that impacts the lives of millions of people and contributes significantly to emissions, productivity loss and infrastructure stress. And yet, until recently, it was left out of the digital transformation conversation.
Today, that has changed.
Consider this: The average urban worker spends 1.5 to three hours commuting every day. Among megacities like Kolkata, Bengaluru and Pune, all three feature in the list of the top five cities in the world with the slowest traffic speeds in the 2024 TomTom Traffic Index; This means millions of collective hours are lost every day. But beyond time, there is an invisible web of inefficiencies – from underutilized vehicles to high fuel costs, employee burnout and unsustainable environmental impacts.
AI is uniquely positioned to solve this because traveling is not a ‘big bang’ problem – it’s a series of micro decisions. When should the vehicle be started? What is the best route? How do we balance shared mobility without compromising security or time? What happens when traffic flow changes due to rain? Or when a co-passenger is running late?
These are problems that traditional systems cannot handle at scale. But AI thrives here – not just by reacting, but by predicting and adapting in real time.
The true power of AI lies not in replacing human decisions, but in enhancing operational intelligence. In mobility, this means turning scattered data – GPS feeds, traffic patterns, employee shifts, EV charging status, compliance protocols – into actionable insights.
Modern AI systems can forecast demand, dynamically match supply, cluster routes to reduce miles traveled, and even model what-if scenarios for fleet usage. For electric vehicle (EV) fleets, which have their own charging cycles and constraints, AI can plan schedules that minimize downtime and optimize battery health. It’s not just about efficiency; It’s all about orchestration on a large scale.
the outcome? Lower costs of operation, lower emissions, and improved employee satisfaction – all powered by AI that works behind the scenes.
As environmental, social and governance (ESG) standards gain popularity globally, businesses are being asked tough questions: How sustainable is your supply chain? What is your carbon footprint as a result of employee travel? Is your workplace fair and safe for all employees?
AI provides a data-backed, auditable way to meet these mandates. By tracking and optimizing every kilometer of travel, organizations can reduce Scope 3 emissions (these are indirect emissions resulting from a company’s activities that are not under its direct control), meet decarbonization targets, and even simulate the impact of switching to an EV fleet or alternative shift schedule.
Additionally, AI-enabled systems improve transparency and traceability – which is essential for compliance in sectors like finance, healthcare and IT, where data integrity, security and timely audits cannot be compromised.
Critics often fear that AI will make processes inhumane. The opposite is true in the mobility sector. AI, when implemented responsibly, improves the human experience. For example, it can ensure safe journeys by marking high-risk areas, monitoring driver behaviour, suggesting alternative routes during late nights and automating security checks – especially important for female employees. At the end of the day, it’s not just about moving people; It’s about moving people forward for the better.
India, with its complex urban infrastructure and growing workforce, presents both challenges and opportunities for AI in smart mobility. Unlike Western countries with centralized planning and adequate infrastructure, Indian cities need adaptive, economical and highly localized AI solutions.
This is where Indian AI innovation shines – in building systems that are robust, resource-efficient and built for the unpredictability of the real world. As the global narrative shifts towards sustainability and resilience, India’s AI-powered mobility innovations can serve as templates for emerging economies around the world.
Like societies transformed by electricity and the Internet, AI is becoming the invisible operating system beneath our most essential systems – from health care to logistics to employee mobility.
Let’s celebrate not just what AI can do, but also what it’s already doing — often quietly, without fanfare, making the world a little smarter, cleaner, and more livable every day.
The next decade will not be about AI replacing humans. It will be about AI empowering humans to solve problems – one route, one shift, one city at a time.
This article is written by Sriram Kannan, Founder and CEO, Routematic.
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