Shipping and rail are both trying to knit together fragmented, multi-operator networks into something that feels seamless to the end customer. What lessons from rail’s push toward unified multi-modal ticketing do you think translate to how shipping and logistics coordinate across carriers, ports and freight forwarders?

The first thing I’d highlight is the need for a neutral orchestrating layer, because in rail the ticketing standard sits above the commercial operators rather than inside any one of them. Until the data backbone is genuinely neutral, “seamless” is likely to remain a word used on conference panels rather than something customers actually experience.

The second lesson is about what sits above competition. In rail, that role is played by safety, which overrides commercial interest and forces a level playing field. Shipping doesn’t appear to have a single equivalent, but from where I sit, decarbonisation, cyber resilience, and supply-chain transparency look as though they’re beginning to function in a similar way, because these are pressures no individual carrier, port, or flag state can resolve on its own, and they may quietly do for shipping what safety has done for rail.

The third lesson is the honest one, which is that rail’s progress has been slower and more uneven than the outside world tends to assume. Fares reform, ticketing platforms, delay-repay interoperability — each took years of imperfect compromise, so if there’s one thing worth passing across the fence it’s not that rail got it right, but that rail kept moving while alignment was still incomplete, and waiting on a perfect standard agreed by all is how you end up with none at all.

You’ve argued AI’s real value in transport is still ahead of us, past the hype. Where in day-to-day operations – scheduling, resource optimisation, customer experience – are you actually seeing it move the needle today, and where is it still overpromised?

Rail, like most transport industries, has been crying out for data standardisation across retail, operations, and infrastructure, and AI has been useful in building systems that can translate and transfer data between formats and functions that were never designed to speak to each other.

A related area where we’re seeing real value is in re-platforming legacy systems. AI has proved useful in helping us interpret, document and migrate those codebases without the risk of losing the operational knowledge embedded in them, which is knowledge that often only exists in the code itself because the people who wrote it have long since retired.

We’ve also been experimenting with AI in augmented rostering, which is the process of assigning crew to trains, and it’s a good example of where the real value of AI often gets missed. The other area where we’re seeing genuine value is in bridging knowledge gaps. Rail is a world of acronyms and conventions that can feel impenetrable to anyone outside it, and AI has been useful in helping us engage stakeholders at the right level.

Where I’d be more cautious is anywhere AI is being sold as a replacement for operational judgement. Scheduling and resource optimisation are the obvious examples, because on paper they look like problems AI should solve outright, but in practice the models are only as good as the assumptions they’re built on, and transport networks are full of edge cases, human factors, and local knowledge that doesn’t sit neatly in a training environment.

Geopolitical and regulatory exposure has a major impact for both rail and shipping. How is that uncertainty changing the way you plan investment and technology roadmaps today versus in the past?

In UK rail we’ve faced more structural change in the last three years than in the previous 15, with Great British Railways in prospect, the shifting role of the Department for Transport, franchise-to-contract reforms and open-access debates all in play at the same time, and the direction of travel is still not fully settled. From the outside looking in, shipping seems to be dealing with its own version of the same pattern, whether that’s the pace of the International Maritime Organization (IMO) decarbonisation, the extension of the EU Emissions Trading System (ETS) into maritime, sanctions regimes, or the routing consequences of the Red Sea.

That kind of volatility changes how anyone in transport has to plan. In a stable environment you optimise for the expected case, because the expected case is broadly what happens. In an unstable one you pay a premium to keep options open, which means modular architectures rather than monolithic ones, shorter contract terms with extension rights rather than long lock-ins, and a preference for systems you can reconfigure without ripping out foundations. It’s more expensive on paper than the optimised version, but the optimised version has a habit of being wrong by year three, at which point the real cost shows up.

This is why we increasingly design systems around adaptability rather than fixed assumptions. Technology should help operators respond to changing policy, regulation and market conditions, not become another constraint.

Decarbonisation is a live pressure across every transport mode. Beyond the direct emissions question, you’ve talked about digital tools helping customers and operators cut their footprint indirectly, through efficiency. How do you make the business case for that kind of “invisible” sustainability gain to clients and regulators?

Digital tools that fix bad routes, cut idle time, or fill empty vehicles save carbon but they cut fuel bills instantly and therefore cost. When you show a client that being green means spending less on diesel or electricity today, sustainability stops looking like an expensive virtue signal and starts looking like a smarter bottom line.

For regulators, it comes down to proof. You can’t just promise you’re doing better – you need the math to back it up. Digital tools automatically track real-time fuel, load, and battery use, giving operators clean, undeniable proof of their lower footprint. Turning messy operations into clear data makes compliance painless and gives companies a huge edge when bidding on public contracts.

That’s where digital platforms have an important role. We increasingly see our job as helping customers make operational improvements measurable, whether that’s reducing emissions, improving asset utilisation or demonstrating compliance.

Bringing MeTS’s 40 years in UK rail into a newly merged, pan-European group is as much a cultural integration as a technical one. What’s your approach to keeping the culture of accountability and open communication you’ve championed intact through a merger of this size?

Integrating 40 years of local heritage into a massive pan-European entity is always a high-stakes balancing act. One thing we’ve learned through successive acquisitions is that culture isn’t preserved through organisation charts. It’s preserved by protecting local expertise, keeping decision making close to customers and giving people ownership.

As we join a broader European group, the goal isn’t to wrap our teams in layers of corporate padding, but to give them clear ownership over their local operations. We maintain accountability by keeping authority close to the frontline, ensuring the engineers and managers who know the UK network best still have the autonomy to make callouts and own the outcomes.