Shashi Shekhar Singh is Head of Operations at Yango Ride MENAP & Africa, where he leads the company's expansion across more than 10 early-stage markets. He brings over 12 years of operations and P&L experience from roles at Swvl, UberEats, Coca-Cola, and Ericsson, including managing global operations across eight countries at Swvl and ten cities at UberEats. Over two years at Yango, he has driven the company's growth across Africa and Asia through data-driven, tech-led operations.

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At a Future Cities fireside chat on September 9, Yango Group's SVP of Operations argued that genuinely integrated urban mobility by 2035 will be decided by execution and economics rather than by autonomous technology, and that the most valuable infrastructure investments sit in the connections between transport modes.

The conversation about the future of cities usually begins with the vehicle. A driverless taxi easing through an intersection, a metro that runs with no operator, a delivery robot on a sidewalk. Shashi Shekhar Singh would rather talk about the space between them.

Speaking on September 9 at a Future Cities fireside chat on urban mobility in 2035, Singh, senior vice president of operations at Yango Group, made a case that cuts against the way most cities market their ambitions. The hardest and most valuable work, he argued, is not building the autonomous car, rather making sure every mode of transport behaves as one system.

His framing lands at a moment when autonomy targets have become civic branding. Dubai, where Yango operates, has committed to converting 25 percent of all transport trips to autonomous journeys by 2030 under its Dubai Autonomous Transportation Strategy, a goal the government projects will generate about 22 billion Dirhams in annual benefits. Robotaxi fleets from Baidu's Apollo Go, WeRide, and Pony.ai are already testing on the emirate's roads while in the United States, Waymo runs paid driverless rides across fourteen metros.

Singh's point is that a working machine is not the same as a working network. “By 2035, passengers should not have to think in terms of separate transport modes. They should be able to say where they need to go and have the system work out the best combination of ride-hailing, rail, public transport, walking or micro-mobility based on what is happening across the network at that moment.”

He described a change in design philosophy.

“The real shift is from designing around the taxi, metro, bus or scooter to designing around the journey itself, autonomy will be part of that future, but it will only be useful if it works as part of the wider transport network.”

Asked what stops mobility pilots from scaling, Singh was blunt, “technology is not the main barrier, execution and economics are,” he said. Cities can already demonstrate autonomous vehicles and digitise public transport, he noted. The difficulty begins when those systems have to operate together, every day, across different authorities, operators, and infrastructure, and when the economics also have to make sense for the private companies expected to run and scale them.

He grounded the claim in his company's own work. Yango's research with INSEAD was on how governments scale technology. Published in 2026 as AI as Public Infrastructure, it documented a familiar pattern of stalled pilots and fragmented ownership.

“Our research with INSEAD on how governments scale technology found many of the same problems: fragmented data, procurement structures, unclear governance and existing processes that were never designed for the new technology,” Singh said.

He same patterns exist across the United States, Europe, and the Gulf. Transit agencies have spent years launching apps, pilots, and partnerships that rarely knit into a single coherent journey. The result is a landscape of impressive parts and a disjointed whole.

Singh sees opportunity precisely in that disjointedness.

“Some of the most important investments will sit between the major transport systems,” he said. “A rail network, autonomous fleet or public transport system can work well on its own, but passengers still need to move efficiently between those services.”

That handoff, the station access, the pickup and drop-off zones, the flow of vehicles around a transport hub, and eventually the merging of journey planning and payment, is where he expects capital to move as cities mature.

On artificial intelligence, Singh was pointedly unromantic.

“The useful part is not AI for its own sake,” Singh said. “It is having better information about what is happening across the transport network and using it to make better decisions about a journey.”

Real-time data already shows where a bus actually is rather than where a timetable claims it should be, and pairing that with routing can tell a passenger when to switch from a ride-hail to public transport partway through a trip. As networks grow more connected, he said, AI can help make sense of far larger volumes of live information, though the test stays the same.

“But the measure of success should remain practical: whether it makes the journey simpler for the passenger and allows different parts of the transport network to work together more effectively,” he said.

For investors and city planners watching the autonomy race, Singh's argument is a useful corrective. As the driverless vehicle is arriving, it is meant to add up to a better city which depends on the far less glamorous work of connection, governance, and a business model that survives contact with daily operations.

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