The UK’s Transport AI Action Plan – A Regulatory Roadmap for the future

UK Government’s newly published Transport Artificial Intelligence Action Plan was developed by the Department for Transport (DfT) to “improve transport for everyone in the UK” and for the Plan to “steer future priorities for AI in transport and support rapid and responsible implementation”. The Plan comprises a strategic framework of short and longer-term ambitions by way of a 23-point action plan for public and private sector stakeholders to unlock the value of AI across the UK transport sector to deliver the DfT’s priorities. 

Of notable interest, a core commitment announced by DfT is for the delivery of measures that allow for advanced trials and commercial pilots of self-driving vehicles in 2026, prior to the official ‘go-live date’ in 2027 previously announced for the Automated Vehicles Act 2024 (see our separate article).

To ensure greater accountability and to engender continued sector development, the Plan envisages stronger AI governance mechanisms by DfT. This includes the creation of an internal Transport AI Board with the purpose to monitor and uphold stakeholder accountability against nominated actions in the Plan, together with a defined commitment to revisit the actions and priorities. 

Objectives 

The Plan outlines four core objectives directed at DfT in collaboration with stakeholders across both the transport and technology sector:

Responsible AI Adoption

DfT have outlined immediate short term objectives to ensure effective collaboration between transport regulators, public sector bodies and partners (such as the Ada Lovelace Institute and Alan Turing Institute) for the identification of AI opportunities and risk management in the transport sector, as well as identification of public procurement levers for the prompt delivery of AI solutions at a local and national level. In the long term, DfT have considered it necessary to identify areas for policy, regulatory and legislative change for responsible delivery of AI solutions for greater risk management 

Maximising economic benefit whilst reducing environmental impact 

The Plan outlines DfT’s commitment to foster sustainable growth through the use of transport AI solutions. The Plan sets out commitments for continued funding for AI research and development together with stronger collaboration with the transport industry for the identification, investment in, and implementation of AI solutions. The long-term vision envisages sustainable AI development with prolonged funding and support for academic research and investment into AI products. 

Securing the UK’s position at the forefront of transport-related AI applications

The Plan sets out ambitious objectives for DfT to establish the UK transport sector as a global leader in transport innovation by promoting open access to transport data and fostering international collaboration. To achieve such a goal, DfT seeks to promote the facilitation of strengthened AI research and leveraging international relationships to establish data sharing frameworks.

Enhancing DfT’s Internal Capabilities

The Plan recognises the need for DfT to itself embrace and adopt AI in its service delivery. DfT outlines commitments to establish appropriate governance mechanisms tailored to different areas including research and development, industry adoption, and regulatory standards. It also aims to build AI-related skills and capabilities among its staff and sector partners. To support better decision-making, DfT will develop smart data tools and AI evaluation methods to support future procurement and implementation of AI technologies.

Action Areas

The Plan further identifies five “action areas” that underpin the above objectives, together with 23 actions to which DfT are to seek to implement within the Plan, categorized within these action areas:

1. Leadership: DfT to maintain a strong leadership structure to underpin the objectives in the Action Plan, to provide for greater guidance, governance, and oversight on stakeholder compliance with objectives and priorities. This will include stronger collaboration between the public sector with private sector stakeholders and academia to engender better innovation and overcome challenges. The Action Plan specifically identifies public procurement of AI in transport sector as a key focal point for DfT’s engagement with local authorities in implementing the objectives in the action plan.
2. Skills and Capabilities: Assessment of capabilities in DfT to ensure that public and private sector stakeholders have the skills, tools and capabilities to implement the actions required in the Plan. This will include targeted training for DfT and stakeholders on the adoption and use of AI in the sector, together with incentivized knowledge sharing between DfT and its arm’s length bodies and private sector collaborators.
3. Infrastructure and Data: Building on the objectives outlined in the Transport Data Strategy 2023 to establish mechanisms to enable the productive and targeted use of AI in the transport sector together with linking data and challenge owners with AI innovators both passively through application programming interfaces or stakeholder events.
4. Applications: Collaboration with AI sector leading partners to showcase innovative use cases and deployments of AI in the transport sector. The Plan further envisages a roadmap and DfT led assessment on opportunities in which AI can improve transport security, climate emissions and engender greater efficiency and cost saving initiatives together with risk level analysis presented the application of AI on risks owned by DfT.
5. Engagement: Greater collaboration and transparency as between DfT and other government bodies as well as private sector counterparts to prompt innovation and investment in transport AI solutions.

Comment

The Transport Artificial Intelligence Action Plan signifies the UK public sector’s positioning as a leader in AI regulation in the transport sector, setting out an objective focused roadmap with a strong regulatory emphasis on responsible innovation, effective collaboration across the public sector at central and local government levels, and engagement with private sector stakeholders to ensure effective identification and implementation of AI in transport.

This Plan marks a further rung on the continued AI regulation ladder in the transport sector following the previous Transport Data Strategy (2023), the AI Regulation White Paper (2023) (Burges Salmon comment) and the Automated Vehicles Act (2024) (Burges Salmon comment) laying the groundwork for sector-specific governance intersection of AI and transport regulation. 

If you would like to discuss how current or future regulations impact what you do with AI, please contact  Brian Wong, Tom Whittaker, Lucy Pegler, Martin Cook, Liz Smith or any other member in our Technology team.  For the latest on AI law and regulation, see our blog and newsletter.

[This article was written by Zac Bourne]

This Plan marks a further rung on the continued AI regulation ladder in the transport sector following the previous Transport Data Strategy (2023), the AI Regulation White Paper (2023) and the Automated Vehicles Act (2024) laying the groundwork for sector-specific governance intersection of AI and transport regulation