Great British Railways (GBR) should strengthen the rail industry’s operational systems and data before attempting to deploy artificial intelligence at scale, according to Netcall transport sector director David Oliver.
Oliver argues that fragmented systems, manual intervention and inconsistent workflows could limit the value of AI as operators and infrastructure organisations move towards greater integration under GBR.
Operational foundations
In an analysis of the sector, Oliver says AI outputs will only be as reliable as the data and processes supporting them. He identifies incident management, access requests, reporting and other routine operational activities as areas where disconnected systems and manual handling can undermine data quality.
He also cautions against confusing an AI pilot with effective deployment across a complex and fragmented railway. In his view, organisations should first improve operational consistency and create trusted data environments that can support future automation.
Network Rail examples
Oliver points to Network Rail’s digitisation of operational and exception-management processes as an example of a more incremental approach. He highlights work to digitise land and consent management, bringing workflows, approvals and specialist support into a more connected digital environment.
He also cites the digitisation of parts of Network Rail’s RAMS (Risk Assessment Method Statement) approval process. According to Oliver, replacing heavily manual approvals with digital workflows has improved visibility, reduced administrative work and helped create more structured operational data.
These projects may not be presented as AI transformation, Oliver says, but they provide the process discipline and information quality needed for more advanced applications later.
Incremental technology investment
With the GBR transition expected to take place over the long term, Oliver says rail organisations are unlikely to replace their legacy technology estates in a single programme. Instead, he advocates platform-based approaches that connect existing systems and processes while reducing duplication.
Low-code development, workflow automation, robotic process automation and systems integration can be used to automate repetitive tasks, digitise approvals and give operational teams faster access to information without requiring every legacy system to be replaced.
Oliver says the GBRX AI Industry Action Plan also underlines the importance of data-sharing, digital foundations and collaboration between rail organisations. He argues that AI should build on those improvements rather than distract from day-to-day operational delivery.
“Long-term transformation is rarely achieved through one giant leap,” Oliver says. In his assessment, the organisations most likely to benefit from AI over the next decade will be those that steadily improve their processes and data foundations while introducing technology that can develop alongside GBR.