Collaborating for innovation in transport: How AI is shaping the future

We organised an ‘AI Hackathon in Transport’ with the UK’s Department for Transport (DfT) and Google Cloud, and with participation from key industry stakeholders such as Network Rail, TfL, HS1 Ltd, LNER, Trainline, CAA, DVLA, and National Highways, as well as leading universities including Imperial College London, the University of Birmingham, and the University of Bristol. The hackathon highlighted the vast opportunities for closer collaboration and the use of AI to help address the critical needs of the transport sector, including increased safety, smart traffic management, and greater inclusivity.

Despite rapid technological progress, only a limited number of AI use cases have been thoroughly explored and implemented across UK transport modes. These efforts have mainly focused on areas such as route optimisation, customer service, and operational efficiency. The challenges – as uncovered at the hackathon – are clear: access to quality data, the need to modernise legacy infrastructure, attracting AI technical talent, and pinpointing the most impactful AI use cases, all underpinned by a robust data ethics framework.

Laying the foundation for AI success

To successfully implement AI, transport organisations must first ensure they have access to high-quality, integrated datasets. Collaborating with organisations such as the DfT to leverage public datasets, and partnering with transport providers for data sharing, are critical steps. Moreover, investing in APIs and data cleaning tools is essential to maintain data quality, which is the backbone of any AI-driven solution.

Conducting thorough assessments of existing transport systems, such as traffic management systems, passenger information systems, and ticketing platforms, is also necessary to identify and prioritise upgrades and adapt legacy infrastructure. Rather than overhauling entire systems, organisations should focus on modular, scalable updates that allow for the seamless integration of AI tools without disrupting current live operations.

Another key foundational step is running strategic planning sessions and pilot projects to help identify and refine digital transformation opportunities that align with goals and deliver clear ROI. Strategy and pilot projects should avoid separating innovation from business as usual activities to reap the full transformation opportunities.

Securing top AI talent is another crucial building block for successful AI deployment amongst transport organisations. The industry can attract skilled professionals and top academic talent by creating a stimulating environment with the opportunities to work with complex datasets on interesting real-life challenges. Additionally, organisations should invest in upskilling their current workforce through targeted training programmes, enabling them to keep pace with evolving AI technologies.

While formal AI regulation is still in its infancy, organisations are recognising the need to stay ahead of potential challenges around ethical usage, IP, bias, and human-centred role design as new models and tools are implemented. Establishing a robust AI governance framework that includes data privacy, security, and ethical guidelines is crucial. Such a framework must be actively promoted and used to ensure the responsible and effective use of AI technologies, helping transport organisations build trust among users and stakeholders.

Turning strategy into action – beyond existing solutions

Transport organisations need to move beyond broad strategies and focus on specific, actionable steps to harness AI's transformative potential. By collecting and analysing network and user data, for example, transport providers can develop AI-powered tools that offer tailored route recommendations based on individual travel preferences and patterns. This goes beyond the capabilities of current apps by incorporating predictive analytics and real-time data from multiple sources, offering users highly personalised and dynamic travel experiences that adjust to a wider range of real-time conditions.

From personalised journey planning and accessibility improvements to traffic flow optimisation – when you move beyond broad strategies, AI has been shown to be a transformative tool driving significant improvements in operations and customer interactions for organisations such as Amsterdam Airport Schiphol and PostNord.

Unlocking AI for more inclusive travel, urban mobility, and cleaner air

When it comes to delivering on inclusivity ambitions and commitments, AI-driven tools can be instrumental in making transport more accessible to users with disabilities, for example, by enhancing personalised assistance tailored to individual needs. This could include dynamic guidance for wheelchair users that accounts for accessibility barriers, real-time alerts for visually impaired users, and adaptive interfaces that cater to users with cognitive disabilities. Such features would ensure that the AI tools can exceed current standards for accessibility, creating a more inclusive transport system.

Furthermore, AI's ability to analyse and predict traffic patterns can be leveraged to optimise traffic light sequences and manage congestion. A solution proposed during the hackathon used deep learning models to coordinate traffic flow, successfully reducing congestion and emissions. This demonstrates the transformational application of AI in improving urban mobility, improving the efficiency of transport logistics, and lowering the environmental impact of transportation.

Co-creation will accelerate the promise of AI

AI technologies in the transport sector will continue to play a role in building a transport system that is safer, more efficient, inclusive, and sustainable. But long-term change will only happen with greater, more diverse collaboration of human insight. As events like the ‘AI Hackathon in Transport’ demonstrate, breakthrough solutions with real value to all stakeholders can emerge when solution architects and data scientists from across industry, technology partners, and government converge to address challenges and co-create together.

We look forward to taking AI innovation further by bringing the transport industry together to co-create more inspiring ideas.