Generative artificial intelligence has rapidly become a mainstream tool among private fleets. But weak data infrastructure and limited measurement capabilities are keeping many organizations from realizing deeper operational benefits.

That assessment is according to a new Fleet Advantage survey released during the National Private Truck Council’s 2026 Annual Conference and Exhibition.

The survey, conducted in April among more than 2,500 transportation and private fleet executives, found that 87.1% of respondents are now using generative AI large language models. Applications include back-office tasks, driver feedback, and extracting information from fleet documents, including maintenance manuals, compliance guides, and standard operating procedures.

Fleet Advantage said the findings reveal both significant progress in AI adoption and growing concern over the quality of the data supporting those systems.

GenAI Adoption Surges Across Fleet Operations

Fleet Advantage said generative AI’s rapid rise represented one of the largest year-over-year shifts the company has recorded in its annual survey. The technology category did not appear in the company’s 2025 survey at all.

Meanwhile, fleets also reported sharp increases in operational AI use cases between 2025 and 2026, including:

• Route optimization growing from 42.9% to 71%
• Maintenance scheduling increasing from 33.3% to 64.5%
• Fuel type analysis rising from 0% to 61.3%
• Asset lifecycle management climbing from 9.5% to 38.7%

Predictive analytics and machine learning adoption also increased, though at lower rates than generative AI applications.

The survey found that 61.3% of fleets now use AI-powered tools for driver monitoring, coaching, and safety management.

Still, Fleet Advantage noted that 6.5% of respondents reported having no formal driver safety monitoring program at all, highlighting what the company described as a concerning gap in baseline safety practices.

Data Integration Emerges as the Biggest Obstacle

While fleets are deploying AI more aggressively, the survey found that implementation challenges intensified significantly year over year.

Respondents citing data integration issues jumped from 38.1% in 2025 to 71% in 2026, while concerns about inaccurate data rose from 23.8% to 64.5%. Lack of AI expertise also increased from 19% to 45.2%.

Fleet Advantage said the results suggest many fleets are struggling to build the foundational data systems needed to scale AI initiatives effectively.

Fleets Pull Back on Agentic AI Expectations

The survey also found a decline in active use and enthusiasm surrounding agentic AI technologies.

Respondents reporting no use of agentic AI nearly doubled year over year, increasing from 19% in 2025 to 38.7% in 2026. Interest in using agentic AI for procurement fell sharply from 57.1% to 9.7%, while interest in asset lifecycle management dropped from 57.1% to 6.5%.

Fleet Advantage said the findings indicate that earlier survey responses may have reflected aspirational goals rather than actual deployment activity.

ROI Tracking and TCO Modeling Remain Weak Spots

Despite increasing investment in AI tools, few fleets appear to have formal systems for measuring returns.

Only 9.7% of respondents reported having a formal AI ROI tracking framework, while 51.6% said they track metrics informally and 19.4% rely on anecdotal assessments.

The survey also identified major gaps in total cost of ownership modeling for Class 8 equipment. About 32% of respondents said they still conduct TCO modeling manually, while 29% reported not performing TCO analysis at all. Adoption of AI-driven TCO modeling averaged just 12.1%.

Telematics and Lease-End AI Opportunities Remain Untapped

Fleet Advantage identified telematics integration and lease-end processes as two major areas where fleets have yet to fully apply AI technologies.

More than half of respondents said they collect telematics and ELD data but have not integrated it into AI systems. While only 9.7% are using those data streams for real-time AI insights. Additionally, 64.5% reported no use or evaluation of AI for lease-end processes such as damage scoring, remarketing, or excess mileage assessment.

“The data tells a story we see playing out across the industry every day,” Mac Hudson, senior off-lease manager at Fleet Advantage, said. “Private fleets are embracing AI faster than anyone anticipated, particularly GenAI, but enthusiasm alone does not create results.”