Vehicle Management Solutions (formerly EVAI) released survey results in June 2025 that highlight the challenges and opportunities facing fleet management with GPT interfaces.
The survey examined the use of generative AI and GPT interfaces across commercial vehicle fleets. Presented to more than 2,000 fleet professionals in May, the data from the online survey highlights a growing appetite for GPT-powered tools in operations, despite usage remaining in its infancy.
The results point to an early stage but accelerating interest in GPT interfaces for fleet. Familiarity is building, yet current usage remains limited. The adoption pipeline is meaningful: 38.8% aren’t using GPT today but are considering it, and 61.2% say they’d definitely or possibly adopt within 12 months.
Regarding perceived value, respondents see opportunity in TCO analysis, trip/route optimization, general data analysis, and vehicle health monitoring. A majority believes GPT outperforms traditional dashboards for analyzing and interpreting fleet data.
At the same time, the top barriers cluster around integration complexity, lack of awareness, data security, and accuracy/hallucinations, with smaller shares citing ROI uncertainty and satisfaction with current tools.
Among current users, reported efficiency gains skew positive: 30.1% cite 8% to 10% improvements, and 9.7% report 15%+ gains, while non-users anticipate a 10% to 12% gain once deployed. However, only about 40% feel “somewhat comfortable” using GPT for operations analysis, with a similar percentage reporting “trust with reservations” for routing.
The survey results indicate that the fleet industry is exploring the potential of GPT-based tools but remains cautious. Interest is increasing, but significant concerns remain regarding system compatibility, user trust, hallucinations, and oversight.
Top Concerns Hindering Adoption of AI
Main blockers are integration, awareness, security, and accuracy.
Source: Vehicle Management Services
KEY FINDINGS:
1. Growing Familiarity and Limited Adoption:
- 40.8% of respondents report being moderately familiar with GPT-style interfaces, while 10.7% say they are very familiar and 9.7% identify as experts.
- GPT solutions are currently used in a limited way by 40.8%, and extensively by just 10.7%.
- Still, 38.8% are not currently using GPT interfaces but are actively considering them.
- 30.1% would definitely consider adopting such interfaces within 12 months, and 31.1% possibly would.
2. Perceived Benefits and Use Cases:
- Key use cases include:
- Total Cost of Ownership (TCO) analysis (21.4%)
- Trip and route optimization (20.4%)
- Data analysis (17.5%)
- Vehicle health monitoring (15.5%)
- 51.5% believe GPT interfaces perform better than traditional dashboards for analyzing and interpreting fleet data.
3. Operational Efficiency Impact:
- For those already using GPT interfaces:
- 30.1% report 8–10% efficiency increases
- 9.7% report improvements of 15% or more
- Among potential adopters:
- 29.1% anticipate a 10–12% efficiency gain if implemented.
4. Comfort and Trust Levels
- 39.8% feel somewhat comfortable using GPT for operational analysis; 10.7% are very comfortable.
- For trip and route optimization:
- 39.8% trust GPT with some reservations
- 10.7% trust it completely
5. AI Delegation and Human Oversight:
- Preferred oversight methods:
- Periodic checks and audits (31.1%)
- Exception-based oversight (29.1%)
- Full-time human oversight (20.4%)
6. Specific Applications and Concerns:
- High perceived value in:
- Automated driver safety alerts and compliance monitoring (59.2% rate as very or extremely valuable)
- Major concerns in vehicle health monitoring:
- Data accuracy (31.1%)
- Integration with existing systems (29.1%)
- Privacy/security (20.4%) ■
