This year will not be straightforward for fleets or for the financial institutions that underpin them. We’re entering what I call a ‘dual-reality economy’ – a market that feels very much like a recession and a boom at the same time.
In this ‘dual-reality economy’, freight volumes remain essential, but margins are tight; operating costs are rising, yet the opportunity to unlock efficiency has never been greater. What will separate the winners from the laggards is simple: whether they treat AI and data as an operational engine or a bolt-on tool.
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At Geotab, we process more than 100 billion data points per day from over 5.6 million vehicles globally. That unique vantage point gives us a clear view of how fleets are being reshaped – and what the next 12 months will demand. Several trends stand out.
AI moves from conversations to operations
The first shift is that AI is finally becoming part of the operational backbone of fleet management worldwide – supporting planning, maintenance, routing and decision-making in ways that weren’t possible even a year ago.
Inside businesses, this shift is already happening. We are seeing developers work 50-100% faster using AI-assisted tools. We are watching back-office teams automate manual processes they previously assumed were immovable. And we are seeing fleet managers use conversational tools to query safety, fuel use, or risk factors in seconds rather than hours.
The financial implications of this seismic trend are significant: the fleets that build this operational muscle early will expand their efficiency gap quickly. Those that don’t will ultimately struggle to match pace.
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By GlobalDataThe ‘dual-reality’ economy creates pressure and opportunity
The year ahead will be defined by the tension between economic strain and technological potential. Growth will feel uneven. Some fleets will cut costs aggressively, while others will seize the moment to modernise. Both dynamics will create winners – but only for organisations with the right tools and with the right data.
Political and cost pressures alike will continue to weigh on haulage. Freight demand is softer, margins are pressured and, in the specific case of the UK as a prime example, the 2025 Budget adds further cost through EVED (Electric Vehicle Excise Duty) and the likelihood of fuel duty returning.
But these pressures also accelerate the shift towards automation, AI-enabled insights and optimisation. The fleets leaning on data will navigate tighter cycles with far more precision. Those that don’t will experience the negative side of the ‘K-shaped economy’, where the biggest and most technologically mature fleets pull away from smaller operators.
For lenders, leasing companies and asset managers the world over, this divergence is critical. Data maturity will become a stronger signal of risk and repayment stability than fleet size alone.
Data-rich companies will become the infrastructure behind enterprise AI
It’s imperative to state that AI does not work without strong, structured data. The next wave of value will come from organisations that sit on large volumes of clean, contextual and real-world information.
This is why data integrity – not just data volume – matters. Fleets need to know whether the data they are collecting is accurate, frequent enough, and suited to predictive modelling.
As I often explain: you cannot predict battery failure if you measure voltage once a second when the model requires 100 samples a second. Quality determines capability, there is no circumventing that equation.
Financial institutions will increasingly use data integrity as part of credit assessment and risk modelling. The fleets with strong data foundations will be far better positioned to secure financing, extend asset life or prove return on investment.
I have no doubt that 2026 will be a pivotal year. The fleets – and the financial institutions supporting them – that act now will not just survive a complex economic landscape; they will gain a structural advantage that compounds over time.
