Bengaluru: Artificial intelligence (AI) could help improve Bengaluru’s public transport system by optimising bus routes, adjusting service frequency to passenger demand and integrating different modes of transport. However, experts have stressed that effective governance, institutional coordination and the ability to implement technological solutions remain major challenges for the city.

The issue was discussed at the Mobility Symposium 2026, organised by MoveInSync in Bengaluru on October 8. Experts highlighted how transport data and AI-based tools could make public transport more responsive to commuters, while cautioning that technology alone cannot resolve the city’s wider mobility problems.

AI could make bus services more responsive

Sreenivas Bhandari, vice-president of transit at the Open Network for Digital Commerce (ONDC), said AI could help public transport agencies move away from rigid schedules and make services more responsive to actual passenger demand.

By analysing passenger movement and travel patterns, transport authorities could identify routes that require more frequent services and those where schedules need adjustment. Such information could help agencies allocate buses more efficiently and improve service planning.

AI-based analysis could also support better coordination between city buses and Metro services. Feeder buses could be planned around Metro passenger demand, helping commuters connect between different modes of transport more conveniently.

For a city such as Bengaluru, where daily commuters rely on multiple transport options, better coordination could help reduce waiting times and improve the overall travel experience.

Transport data sharing is crucial

Bhandari highlighted the importance of open data, common standards and application programming interfaces (APIs) to connect different public transport systems.

Transport agencies generate considerable amounts of information through vehicle tracking systems, passenger information systems and historical travel records. Bringing these datasets together could help authorities understand passenger demand and identify gaps in services.

At present, information held by separate transport operators may not always be easily accessible through a common platform. Better integration could help commuters plan journeys across buses, Metro services and other transport options.

A shared digital framework could eventually allow passengers to plan, book and track an end-to-end journey through a single application, instead of switching between multiple platforms.

The approach would also make transport information more accessible to commuters who may not be familiar with complex digital tools.

Governance remains the bigger challenge

While AI can identify potential improvements in route planning and network design, experts stressed that implementing those recommendations requires more than technology.

Ashwin Mahesh, founder of LVBL Accelerator, said governments need the institutional capacity, planning systems and trained personnel required to put technology-driven recommendations into practice.

AI may identify an efficient route or indicate where additional buses are needed, but transport authorities must still make decisions about funding, infrastructure, service priorities and coordination between agencies.

The discussion also highlighted the limitations of focusing too heavily on digital applications without addressing the practical realities of public transport.

Technology-based solutions need to account for the social and political conditions in which transport systems operate. Without institutional support and effective implementation, even well-designed digital tools may have limited impact on everyday commuting.

Urban planning also shapes mobility

Mahesh also pointed to Bengaluru’s wider urban planning challenges, including the concentration of employment opportunities in a limited number of areas and high housing costs.

These factors make it difficult for many residents to live close to their workplaces. As a result, large numbers of commuters need to travel across the city, placing pressure on transport infrastructure.

The concept of a “15-minute city”, in which residents can reach many everyday needs within a short journey, is difficult to achieve without changes in employment and housing patterns.

This means that improving public transport cannot depend on route optimisation alone. Better coordination between transport planning, housing and employment locations is also important for reducing long commutes.

AI can help monitor road infrastructure

Nikhil Maroli, co-founder and director of RoadMetrics, highlighted another possible application of AI in urban mobility.

Computer vision and AI tools can analyse road images to identify defects, footpaths and lane markings. Such information could help authorities monitor road conditions, prioritise repairs and plan maintenance work more systematically.

If implemented effectively, these tools could help civic agencies identify infrastructure problems and respond more efficiently.

However, the usefulness of such systems would depend on whether the information they generate is acted upon by the relevant authorities. Data collection and automated detection must be supported by clear responsibility for maintenance and timely execution.

Bengaluru needs coordination beyond technology

The discussions at the symposium underlined the need to combine technological innovation with stronger institutional coordination.

AI could support decisions on bus routes, service frequency, passenger demand and road maintenance. Shared transport data could also make journeys easier to plan across different modes of public transport.

Yet these improvements depend on government agencies being able to share information, coordinate their work and implement solutions consistently.

For Bengaluru, the challenge is therefore not simply adopting more advanced technology. It is ensuring that transport authorities have the systems, skills and administrative support needed to turn technological possibilities into practical improvements for commuters.

Excerpt:

AI could help optimise Bengaluru’s bus routes and schedules, but experts say governance, data sharing and effective implementation remain key challenges.

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Bengaluru bus network AI optimisation, Bengaluru public transport governance challenges, Mobility Symposium 2026 Bengaluru, AI in Karnataka urban mobility, Bengaluru bus route planning technology

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Bengaluru Bus Network: AI Potential and Governance Challenges

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AI could improve Bengaluru’s bus routes and schedules, but experts say governance, transport data sharing and implementation remain major challenges.

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