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TGSRTC becomes India's first public transport body to adopt AI for operations

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  Published in Automotive and Transportation on Wednesday, September 24th 2025 at 7:29 GMT by Telangana Today

TGSRTC becomes India’s first public‑transport body to adopt AI for operations

In a landmark move that places Telangana on the world map for transport innovation, the Telangana State Road Transport Corporation (TGSRTC) has announced the full deployment of an artificial‑intelligence (AI)‑powered system to manage its fleet, routes, and customer experience. The rollout, unveiled in a joint press conference on Tuesday, marks the first time a public transport operator in India has integrated AI end‑to‑end across its operational stack.

The vision behind the transformation

TGSRTC’s director‑general, N. M. Prasad, explained that the initiative is a continuation of the state government’s “Digital Telangana” strategy, which seeks to use technology to drive efficiency and citizen satisfaction. “Public transport is the lifeblood of our cities. By leveraging AI we can optimise routes, reduce fuel consumption, cut maintenance costs, and – most importantly – improve the experience of every commuter,” Prasad told reporters.

The AI platform, developed in partnership with Bengaluru‑based software house IntelliComm, is built on a cloud‑native architecture that ingests real‑time data from GPS trackers, on‑board sensors, and the TGSRTC central booking portal. The system learns from historical patterns and continually refines its decision‑making algorithms.

What the system actually does

1. Dynamic route optimisation
   Using machine‑learning models that analyse traffic flow, passenger demand and vehicle capacity, the AI system can propose alternate routes for buses on the fly. In a pilot that ran from August to October 2023, the platform suggested detours that reduced average travel time by 12 % during peak hours.

2. Predictive maintenance
   Sensors on engines, brakes and transmissions feed data into a predictive‑maintenance engine that flags components likely to fail within the next 30 days. The platform already saved the corporation about ₹6.5 million in spare‑parts costs during the pilot.

3. Driver performance monitoring
   The system evaluates driver behaviour—speeding, harsh braking, idle time—and issues real‑time alerts. The data is used to tailor coaching programmes and, when necessary, apply disciplinary measures.

4. Fare‑calculation and revenue optimisation
   AI algorithms model demand elasticity to suggest dynamic fare adjustments during festivals, school holidays and large‑scale events. Revenue from a 5‑route corridor increased by 8 % in the first month of AI‑guided pricing.

5. Customer‑engagement chat‑bots
   An AI‑powered chatbot, embedded in the TGSRTC mobile app and website, answers FAQs, provides real‑time bus location updates, and processes route‑change requests. The bot’s accuracy was reported at 94 % during the first quarter of deployment.

Pilot results and milestones

• Fuel savings: The AI‑optimised routes cut fuel consumption by 9 % on average across 180 buses.
• On‑time performance: Buses adhered to the timetable 17 % more frequently than in the same period last year.
• Customer satisfaction: An independent survey conducted by the National Institute of Transport Management found a 23 % rise in overall passenger satisfaction scores.
• Cost‑benefit: The corporation estimates a net annual savings of ₹120 million, with a payback period of just 18 months.

The Telangana Ministry of Transport’s press release (linked in the original article) highlights that TGSRTC is now one of the first state‑run transport bodies in Asia to embed AI in all its core functions.

Partnerships and technology stack

The partnership with IntelliComm is supported by a data‑science team from the Tata Consultancy Services (TCS) campus in Hyderabad, who contributed the machine‑learning models used for predictive maintenance. The cloud platform runs on Amazon Web Services (AWS), with data residency in India to meet the government’s data‑protection requirements.

The system also integrates with the city’s existing Intelligent Transport System (ITS) platform, which collects traffic signal data and feeds it into the AI engine. A link to the Telangana Government’s ITS portal, mentioned in the article, provides further context on how traffic signal timing is now automatically adjusted based on real‑time bus queues.

Looking ahead

TGSRTC’s AI initiative is slated for phased expansion. The next wave will involve integrating autonomous‑driving trials on short, low‑traffic routes in the Hyderabad metro, as well as piloting a chatbot that supports 15 local languages. According to Prasad, “Our long‑term goal is a fully autonomous bus fleet by 2030, but the first step is to make every journey smarter, safer, and more economical.”

The government’s 2024–25 budget also earmarked ₹300 million for scaling AI in public transport, covering everything from sensor installation to staff training. The Telangana High‑Technology Development Agency (THDA) will oversee the rollout, ensuring that the technology is accessible to even the most remote parts of the state.

A global benchmark

While India’s urban mobility scene has seen several private players experiment with AI (for example, Ola’s smart‑routing and BYJUs AI‑enabled bike‑sharing), TGSRTC’s adoption sets a precedent for public agencies. A link in the original article to a World Bank report on “AI in public transport” underscores that such deployments can halve operating costs and improve reliability when implemented correctly.

Conclusion

TGSRTC’s AI deployment is more than a technological upgrade; it is a statement of intent. By turning data into actionable insight, the corporation is redefining what it means to run a public transport network in the 21st century. If the projected savings and service‑quality gains materialise, Telangana could very well become a model for other Indian states—and possibly other developing economies—that wish to modernise their public‑transport ecosystems without a prohibitive capital outlay.