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01 September 2026

Focus September 2026

Technology & InnovationSustainability & EnvironmentSkills & EducationPolicy & GovernmentProjects & PeopleFocus MagazineActive TravelAviationBus & CoachFreight ForwardingLogistics & Supply ChainOperations ManagementPorts, Maritime & WaterwaysRailTransport Planning

Welcome to Focus's September 2026 issue, which spends real time with the question the profession can no longer defer: not whether AI belongs in transport and logistics, but where, and on whose terms.

The answer isn't uniform. In places, AI is already invisible in the good sense, forecasting failures, monitoring fleets, catching patterns no human team could hold in view at once. In others, it's the opposite problem: decisions are moving into systems nobody can fully explain, and the sector is having to build the vocabulary, explainable, verifiable, auditable, to keep pace with what its own tools are doing.

That tension runs through this issue's AI coverage. Adoption is accelerating faster than governance. Productivity gaps that have sat unmoved for three decades are, for the first time, being closed by something other than headcount. New job titles are appearing at the exact moment old certainties about accountability, who's liable, who's watching, who's actually deciding, are being rewritten. None of it is settled, and the features that follow don't pretend otherwise.

What they agree on, from a dozen different angles, is that the interesting question was never ‘how do we use AI’ but ‘what are we actually trying to solve, and does this get us there.’ Capability is not a strategy. A black box that works is not the same as one that can be trusted. And a profession that lets the technology set its own agenda has already given up the thing that made it a profession in the first place.

That's the spirit we found, unprompted, in this issue's interview with Lauren Sager Weinstein, Chief Data Officer at Transport for London. Nearly 24 years into a career that includes taking contactless payment from a three-person meeting room to a global standard, she's unsentimental about what AI actually is, mature in places, genuinely new in others, and clear that it's only ever as good as the data underneath it. Her closing point stays with you: trust is inherently human, and it's what should decide where the technology goes next.

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