Fleets test AI as ageing vehicles drive up costs

Fleetio has published new benchmark findings indicating that fleet operators are testing artificial intelligence tools but remain cautious about deploying them widely. Meanwhile, maintenance backlogs and ageing vehicles continue to exert cost pressures and cause downtime.

The 2026 Fleet Benchmark Report & State of Fleet Management draws on aggregated, anonymised data from 1.2 million vehicles and 9 million work orders, covering 17.5 billion miles and USD $7 billion in service spend. Fleetio also surveyed more than 600 fleet professionals across multiple industries.

Cost pressures are central to fleet decision-making. Rising costs ranked as the top concern for 54.4% of respondents, followed by regulations and emissions mandates at 46.1%.

Respondents also highlighted longer-term structural issues. The transition to electric vehicles and charging infrastructure, technician shortages, and parts and vehicle availability were the primary concerns, accounting for 35.1%, 32.5%, and 28.9%, respectively.

AI Adoption

AI adoption remains in its early stages across much of the sector. More than half of respondents (53.3%) reported researching or piloting AI capabilities, whereas only 5.6% reported using AI broadly today.

Reliability concerns appear to be a major brake on faster uptake. Half of the respondents cited accuracy and reliability as their main hesitation.

Although the research does not disaggregate AI use cases by segment, it indicates a substantial gap between experimentation and large-scale deployment. That gap also points to procurement and governance hurdles as operators weigh the impact of new tools on safety, compliance, and cost control.

Ageing Vehicles

The benchmark data suggests older vehicles account for a disproportionate share of maintenance costs. Vehicles older than 10 years accounted for approximately 12.1% of miles travelled in the dataset, but approximately 33.5% of total service spend.

Service cost per mile also rises sharply with age. Vehicles aged 0 to 5 years recorded an estimated cost of USD $0.20 per mile, compared with USD $1.10 per mile for vehicles older than 10 years.

These figures highlight a central trade-off in fleet management. Keeping vehicles longer can reduce acquisition outlay and slow depreciation, but it can strain service budgets if maintenance planning and execution slip.

Maintenance Bottlenecks

Operational coordination emerged as a prominent barrier to maintaining the schedule. The most common reasons for maintenance falling behind were communication gaps (31.5%), followed by technician availability (27.4%) and unscheduled service volume (25.2%).

Fleet operations often span multiple sites, external repair partners, and asset types. The survey results suggest basic process execution remains a recurring challenge, even where organisations have defined maintenance policies.

Downtime Signals

Work-order timing data indicate a wide variation in the rate at which repairs begin. The dataset shows a median time to start work orders of 31 minutes and an average of 6.7 days, indicating that a substantial share of jobs face longer delays.

Delayed start times can translate into avoidable downtime and missed utilisation targets. Long waits can also drive knock-on costs such as rental replacements, overtime, and rescheduling.

On-Time Performance

Many fleets see room to improve maintenance execution. Some 44.3% of respondents said they perform maintenance on time "reasonably well," while only 9.7% said consistent on-time maintenance was a strength.

That split suggests fleets recognise the importance of planned maintenance but struggle to deliver it consistently. The results align with survey findings on coordination, technician capacity, and unpredictable demand.

Fleetio will host a webinar panel with survey respondents to discuss additional findings and practical next steps.