New Survey From EVAI Illustrates Opportunities & Challenges With GPT Interfaces For Fleet Management Adoption Still In Early Stages

• 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.

• The most common barriers include:
  • Integration complexity (20.4%)
  • Lack of awareness (19.4%)
  • Data security concerns (19.4%)
  • Worries about hallucinations/answer accuracy (19.4%)
• Fewer cited uncertain ROI (9.7%) or satisfaction with current systems (11.6%).

• 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.

• 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.

• 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

• Delegation comfort levels:
  • 30.1% would delegate some tasks with human oversight
  • 30.1% would delegate moderate tasks with periodic reviews
  • Only 10.7% would allow high-level delegation; 9.7% would allow full autonomy
• Preferred oversight methods:
  • Periodic checks and audits (31.1%)
  • Exception-based oversight (29.1%)
  • Full-time human oversight (20.4%)

• 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%)
• Real-time location and geofencing:
  • 21.4% consider it very important
  • 29.1% moderately important
    

“The data reveals a clear desire to embrace generative AI in the fleet sector, but also underscores that we're still in the early phases,” said Ian Gardner, Founder and CEO of EVAI .“Fleet managers are asking smart questions about integration, trust, and ROI-and that's where EVAI is helping bridge the gap, providing real-time, actionable insights while keeping human oversight in focus.”

While GPT-style interfaces offer strong promise for improving decision-making, efficiency, and cost control, providers must address lingering concerns about hallucinations, system compatibility, and user trust. The research suggests that with the right deployment strategy and user training, GPT-based tools can become a momentous force in fleet operations-unlocking gains that were previously out of reach.

As the industry continues to modernize, EVAI's mission remains clear: to equip fleets with the intelligent tools they need to operate efficiently, predictively, and securely in a fast-changing environment.

About EVAI:

EVAI is a pioneering company specializing in advanced data analytics and AI-driven solutions for fleet management. Our mission is to empower fleet managers with the tools and insights they need to optimize their operations, reduce costs, and transition to sustainable electric vehicle (EV) fleets. By leveraging cutting-edge technology, predictive analytics, and real-time data, EVAI provides comprehensive solutions that address the challenges of Total Cost of Ownership (TCO) tracking and EV adoption. Our innovative platform enables fleet managers to make informed decisions, enhance efficiency, and achieve their sustainability goals. For more information, visit .

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