Artificial intelligence (AI) is gaining traction in transportation management, and although the industry is still in the early stages of AI adoption, motor carriers are already clear about the role they want AI to play in their operations.
Rather than pushing toward fully autonomous decision-making, most carriers are prioritizing AI tools that improve real-time efficiency across pricing and routing, ETA management, and dispatching, according to Trimble’s latest State of AI report. The survey is based on responses from more than 230 shippers, carriers, and logistics service providers (LSPs), as well as interviews with more than 20 executives across Europe and the United States.
Only 13% of carriers and LSPs said they support fully autonomous decision-making within a transportation management system (TMS). Most favor a human-in-the-loop model, where AI handles routine tasks, surfaces insights, and flags exceptions.
For fleets, AI’s value lies in helping them react faster and run tighter operations — not in replacing humans and their judgments, Trimble found.
Where carriers are using AI today
Among carriers and LSPs, the most common AI-enabled use cases are those affecting utilization and service reliability. These include pricing and lane optimization (42%) and real-time tracking and ETA management (39%). Driver scheduling and route planning (31%), load acceptance and dispatching (29%), and freight billing and audit (25%) also rank among the leading applications.
Meanwhile, nearly half of shippers (44%) reported using AI in transportation planning and optimization, while others cited freight procurement (37%) and real-time visibility (32%). Thirty-six percent of shippers reported having moderate or basic AI capabilities in their TMS, while about 25% said they’re not using AI at all, and about 18% said they do not even have a TMS.
The survey also found that just 8% of carriers and LSPs said they do not use a TMS, while 24% said their TMS has no AI capabilities. Thirty-nine percent said they operate a TMS with basic AI capabilities, while 13% described those as moderate.
When asked which AI capabilities would most improve route planning and fleet optimization, more than half of the carriers pointed to real-time rerouting based on conditions (54%) and predictive route and load planning (52%), followed by reducing fuel costs and empty miles (42%).
And over half of the surveyed shippers said that real-time scenario simulation and forecast-based planning aligned with demand variability would benefit their transportation planning processes the most.
AI integrations
Carriers also have certain preferences about how they want AI to be integrated into their daily workflows.
According to the survey, 63% of carriers and LSPs prefer dashboards with visual insights and alerts as their primary way of interacting with AI-enabled TMS platforms. Another 43% favor automated alerts or nudges, while 39% want AI suggestions embedded directly into dispatcher or driver workflows.
Surprisingly, interest drops when interaction becomes more hands-off. Only 31% support AI-powered automation with minimal manual input, and fewer than one-third favor chatbots or voice assistants and mobile app notifications.
The findings suggest carriers are most comfortable with AI that enhances situational awareness and fits naturally into existing tools and workflows, rather than systems that operate independently in the background, Trimble said in the report.
And while full autonomy remains off the table for most carriers, there is growing openness to task-level automation.
For example, when asked which logistics activities are most suitable for AI agents to manage autonomously or semi-autonomously, carriers most often cited ETA calculation and alerting (59%), route and fuel optimization (40%), and spot quote negotiation (36%). Load acceptance and dispatching (34%) and invoice matching and exception handling (31%) also ranked high, along with appointment scheduling with shippers.
But asset maintenance (8%) ranked lowest, signaling that carriers are reluctant to rely on AI when it comes to safety-critical decisions.
A look into the future
Looking ahead three to five years, carriers expect AI’s most significant impact to be in pricing and lane optimization. It was cited by 59% of respondents, while driver scheduling and route planning (41%) and real-time tracking and ETA management (40%) were cited closely behind.
Shippers echoed the focus on optimization, with 86% expecting AI to have a significant impact on transportation planning and optimization over the same period.
And when it comes to freight procurement specifically, shippers identified carrier performance scoring (60%), predictive rate trends (57%), and dynamic market benchmarking (53%) as the AI capabilities that would bring the most value in the future.
Data quality slows adoption
Despite the growing interest in AI, respondents reported that foundational challenges have hindered adoption. More than half of carriers and LSPs (57%) cited data quality and system gaps as the most significant barrier to successful AI deployment, followed by integration challenges with shipper or broker platforms (36%).
Shippers reported similar concerns, with nearly half citing data quality as their top obstacle, followed by cybersecurity and data privacy risks (38%).
Respondents emphasized that AI systems cannot deliver reliable insights when data is incomplete, inconsistent, or siloed across disconnected platforms.
At the same time, carriers and shippers are not rushing for collaborative planning across multiple organizations. Instead, they are focusing on stabilizing internal data and systems before extending AI-driven collaboration and widening networks.
Collaborative planning across multiple organizations ranked near the bottom of expected AI value, while enhanced load matching and prioritization (55%) and aggregating real-time freight opportunities (43%) ranked at the top. And shippers pointed to improved predictive capabilities such as ETA accuracy and disruption risk management (43%).
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