AI, the role of Agents and the future of transportation
)
Artificial Intelligence Agents (AI Agents) are poised to take centre stage in 2025, significantly impacting public transportation by enhancing route planning, fare management, and passenger communication. Unlike traditional algorithms or static software solutions, these intelligent agents are capable of learning, decision-making, and real-time adaptation. By dynamically engaging with passengers, operators, and urban infrastructure, they can significantly enhance the efficiency and functionality of the transportation network, creating a more streamlined and responsive public transit experience.
These AI agents will provide a highly personalised travel experience by anticipating commuter needs and offering tailored solutions. By analysing travel history, user preferences, and real-time feedback, these agents can optimise routes to avoid congestion and suggest faster alternatives. They can also coordinate seamless multimodal connections, including buses, trains, and rideshares. Leveraging data such as GPS tracking, weather conditions, and passenger load levels, these agents will not only improve individual journeys but also contribute to enhanced overall network performance. The ability to process and act upon real-time data means that AI Agents can adjust routes, provide accurate estimated times of arrival, and proactively communicate with passengers to keep them informed of any changes or delays, increasing passenger satisfaction and confidence in the public transit system.
Public transport agencies can utilise AI Agents to implement dynamic fare management strategies, such as demand-responsive pricing and off-peak discounts. By analysing variables like commuter density, time of day, and seasonal fluctuations, these agents can adjust fares to manage ridership and optimise revenue. For instance, reduced fares during off-peak hours may encourage increased use of public transport, while higher fares during peak times can help mitigate overcrowding. These adaptive pricing models will enable agencies to balance financial sustainability with equitable service provision, ensuring accessibility for all user groups. Additionally, AI Agents can provide fare recommendations to passengers, suggesting the most cost-effective ticket options based on travel frequency and patterns, which helps improve the overall customer experience and makes public transport more attractive compared to other modes of travel.
In semi-urban and rural areas, where transportation demand is more variable, AI Agents will play a critical role in enhancing accessibility. By applying predictive analytics, these agents can adjust schedules and dispatch vehicles efficiently to underserved areas, ensuring that even remote communities receive consistent and reliable public transport services. This demand-responsive approach will help bridge the accessibility gap in regions with fluctuating transport needs. Furthermore, AI Agents can work with smaller, on-demand transit services to create an integrated network that responds to real-time requests. By utilising advanced algorithms and cloud-based systems, these agents can dynamically allocate vehicles based on demand patterns, ensuring optimal coverage. Additionally, real-time data sharing between transit services and centralised AI platforms can enhance coordination, enabling seamless service for users while minimising wait times and resource wastage, and making transportation more flexible and accessible for people who may not live near fixed-route services. This capability is particularly valuable for elderly populations or individuals without access to personal vehicles, allowing them to maintain independence and participate fully in their communities.
As AI Agents evolve, their capabilities in integrating transit planning, dynamic fare optimisation, and real-time passenger interaction will fundamentally transform public transportation. This evolution will lead to a smarter, more sustainable, and more inclusive transit system, ultimately benefiting all users through improved convenience, reduced travel times, and better resource allocation. The integration of AI will also help reduce the environmental impact of public transportation by optimising vehicle deployment, minimising empty trips, and encouraging greater use of public transit options.
The future of public transport will be one where AI-driven intelligence ensures that the system is responsive, efficient, and tailored to meet the diverse needs of its users, ushering in a new era of connected and sustainable urban mobility.
The Osmodal team will once again be attending the Transport Ticketing Global event on 4th & 5th March in London. The event brings together the key decision-makers and influencers from the ticketing arena and promises to deliver another program of rich content exploring the future of ticketing. We’re excited about TTG2025. If you’d like to learn more about the work Osmodal is delivering for clients globally, we’d love to chat.