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 tend to focus on AI's dramatic strides in creative tools or large language models, a quiet revolution is happening in the back-end systems that power cities — logistics, energy, mobility, and workforce orchestration— leaving 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 transformation is urban commute, a daily routine that affects millions of lives and contributes significantly to emissions, productivity losses, 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 employee spends anywhere from 1.5 to three hours daily commuting. In megacities like Kolkata, Bengaluru and Pune, all three of which feature in the 2024 TomTom Traffic Index’s list of world’s top five cities with the slowest traffic speeds; this scales to millions of collective hours lost every day. But beyond time, there's an invisible web of inefficiencies — from underutilised vehicles to high fuel costs, employee burnout, and unsustainable environmental impact.
AI is uniquely positioned to solve this because commuting is not a `big bang’ problem — it is a series of micro-decisions. When should a vehicle start? What is the optimal route? How do we balance shared mobility without compromising safety or time? What happens when rain changes traffic flows? Or when a co-passenger is running late?
These are problems that traditional systems can’t handle at scale. But AI thrives here — not just by reacting, but by predicting and optimising in real-time.
The true power of AI lies not in replacing human decisions but in augmenting operational intelligence. In mobility, this means transforming 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, and even model what-if scenarios for fleet utilisation. For electric vehicle (EV) fleets, which have their own charging cycles and constraints, AI can plan schedules that reduce downtime and optimise battery health. It’s not just about efficiency; it’s about orchestration at scale.
The outcome? Lower cost of operations, reduced emissions, and improved employee satisfaction — all driven by AI that works behind the scenes.
As environmental, social, and governance (ESG) standards gain traction globally, businesses are being asked tough questions: How sustainable is your supply chain? What’s your carbon footprint as a result of employee travel? Is your workplace equitable and safe for all employees?
AI offers a data-backed, auditable way to meet these mandates. By tracking and optimising every kilometre of travel, organisations can reduce Scope 3 emissions (these are indirect emissions as a result of the activities of a company which are not under its direct control), meet decarbonisation goals, and even simulate the impact of switching to EV fleets or alternate shift schedules.
Additionally, AI-enabled systems improve transparency and traceability — essential for compliance in sectors like finance, healthcare, and IT, where data integrity, safety, and timely audits are non-negotiable.
Critics often fear that AI will dehumanise processes. The opposite is true in the mobility sector. AI, when implemented responsibly, improves the human experience. For instance, it can ensure safer travel by flagging high-risk zones, monitoring driver behaviour, suggest alternate routes during late-night hours and automate safety checks — especially vital for female employees. At the end of the day, it’s not just about moving people; it’s about moving people better.
India, with its complex urban fabric and growing workforce, presents both a challenge and an opportunity for AI in smart commuting. Unlike western nations with centralised planning and ample infrastructure, Indian cities require adaptive, frugal and highly localized AI solutions.
This is where Indian AI innovation shines — in building systems that are robust, resource-efficient, and built for real-world unpredictability. As the global narrative shifts toward sustainability and resilience, India’s AI-powered mobility innovations could serve as templates for emerging economies worldwide.
Much like electricity and the internet transformed society, 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 what it’s already doing — often quietly, without fanfare, making the world just a little bit smarter, cleaner, and more liveable every day.
The next decade won’t 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 authored by Sriram Kannan, founder & CEO, Routematic.