Bridging the AI Revolution in Transport: Turning vision into impact

Transport Artificial Intelligence (AI) Action Plan

From Strategy to Action DfT’s action plan outlines 30+ priority actions, from developing AI risk frameworks and procurement toolkits to creating sector-specific Communities of Practice and deploying AI-readiness pilots.

Each action maps to one or more of the four overarching objectives of the plan:

1. Adopt AI responsibly
2. Maximise economic and environmental benefits
3. Secure UK global leadership in transport AI
4. Enhance DfT capability through AI

Key actions grouped by the five strategic action areas

1. Leadership

• 1.1 Develop leadership statements with industry for AI implementation across transport sub-sectors.
• 1.2 Investigate barriers to AI in local transport systems and create plans to overcome them.
• 1.3 Enable advanced trials and early commercial pilots of automated craft (air, marine) before 2027.
• 1.4 Ensure regulators are equipped to balance innovation and safety in AI oversight.
• 1.5 Partner with local authorities to drive AI-led transformation in road and traffic network management.

2. Skills and Capabilities

• 2.1 Review and improve AI commercial frameworks and procurement guidance.
• 2.2 Launch AI apprenticeships and secondments into DfT and transport agencies.
• 2.3 Deliver internal AI training across DfT, including for senior leadership.
• 2.4 Establish a Transport AI Community of Practice to share learning and accelerate adoption.
• 2.5 Collaborate with the wider transport sector to align AI skills priorities with future programmes.

3. Infrastructure and Data

• 3.1 Publish the Transport Data Action Plan 2025 to enable productive use of data for AI.
• 3.2 Create mechanisms (e.g., APIs, hackathons) to link data owners with AI innovators to trial solutions.

4. Applications

• 4.1 Showcase AI use cases, run hackathons, and map opportunity areas across transport.
• 4.2 Assess how AI can improve transport security and system resilience.
• 4.3 Explore AI’s role in reducing environmental impacts and adapting to climate change.
• 4.4 Develop a roadmap for cyber-physical interfaces (e.g., robotics) for real-world deployment.
• 4.5 Deploy AI within DfT operations to unlock analytical insight and efficiency.
• 4.6 Require infrastructure projects to assess AI benefits and publish use cases.
• 4.7 Analyse AI-related risks and mitigations across transport systems.
• 4.8 Explore geospatial foundation models for transport planning and decarbonisation.

5. Engagement

• 5.1 Support SMEs through innovation investment and programmes like TRIG.
• 5.2 Collaborate with transport agencies and ALBs to define AI ambitions and action plans.
• 5.3 Conduct public engagement and behavioural research to understand perceptions and build trust in AI.

Transport AI: A National Economic Imperative

The economic case for transport AI is compelling. The UK transport sector is the largest consumer of energy and a major contributor to emissions. It represents a significant portion of household expenditure and underpins both domestic logistics and global trade.

Already, AI applications are improving everything from predictive maintenance on the railways to real-time traffic optimisation and autonomous port operations.

• The UK self-driving vehicle industry alone is projected to be worth £42 billion and create 38,000 high-skilled jobs by 2035.
• The UK’s AI sector already contributes over £3.7 billion to the economy and employs more than 50,000 people — with a forecasted global market value exceeding $1 trillion by 2035.
• In the aviation sector, drones and advanced air mobility systems could add £45 billion to the UK economy by 2030.
• Targeted maritime investment impact: A £560 million R&D investment in UK smart shipping technologies could generate a £1.6 billion boost in turnover and create 11,500 new full-time jobs, contributing up to £750 million in GDP over 30 years while also delivering £56 million in wider technology spill-over benefits.
• Maritime’s immediate sector gains: The UK’s £8 million Smart Shipping Acceleration Fund is already catalysing AI-driven projects (e.g. autonomous vessels, port optimisation), laying groundwork for new job creation in coastal communities, increased productivity, and longer-term economic returns through higher-value domestic innovation.
• The Department for Transport has invested £4.7mn on the latest First of a Kind programme, where ‘AI for Complex Processes’ will be supported.
• The UK government has awarded £32 million to nearly 100 AI-driven projects aimed at reducing train delays, enhancing infrastructure maintenance, and cutting emissions across rail-related supply chains. Among recipients are initiatives for autonomous condition detection, safety enhancements, and logistics improvements.
• Under its AI Opportunities Action Plan, the government has spurred over £14 billion in AI investment across sectors—assisting innovators like those in rail to thrive in a supportive ecosystem.

Find out more about how Innovate UK Business Connect supports AI in transport.