Why AI, and why trucking companies are implementing it now

Artificial intelligence (AI) is no longer a futuristic concept or a trendy buzzword in logistics; it’s fast becoming a survival tool for the modern trucking industry. Faced with shrinking margins, evolving customer expectations, and massive operational complexity, carriers are leaning into AI not as a luxury but as a necessity.

Below, we break down four major forces driving this transformation and why waiting is not an option.

1. An avalanche of data and not enough insight

The trucking industry is experiencing an explosion of data inputs—more than it can handle manually. Telematics systems, transportation management systems (TMS), electronic logging devices (ELDs), onboard cameras, IoT sensors, freight markets, and driver apps are constantly generating data.

A typical long-haul truck generates massive amounts of data per day, yet most of this information remains siloed or underutilized.

Without intelligent automation, operations teams are left drowning in dashboards and spreadsheets, struggling to separate signals from noise. AI, especially machine learning and decision intelligence, can process this data in real time to uncover hidden inefficiencies, flag anomalies, and boost utilization, productivity, and profitability across your organization.

Example: Dispatch management

Dispatch decisions should be based on data and facts, not assumptions and feelings. For example, two planners sitting beside each other make very different load planning decisions. With AI-backed decision intelligence, driver-to-load matches are optimized holistically across the whole network, meeting both short-term needs and long-term objectives, including driver satisfaction, utilization, and profitability. Advanced AI technologies maximize asset utilization, allowing you to shift valuable resources away from routine planning tasks.

2. Sky-high customer expectations

Shippers and end-customers alike have come to expect what was once impossible: hyper-accurate ETAs, real-time tracking, responsive communication, and zero delays. Amazon, Uber Freight, and digital-first brokerages have redefined the baseline experience, leaving traditional fleets scrambling to keep up.

In a 2023 survey by Gartner, 84% of supply chain leaders cited customer demands for faster, more transparent shipping as their top challenge. The problem? Humans can’t meet those expectations alone—not at scale and not without error.

Decision automation fills this gap by enabling automation in dispatching, load management, bid analysis, and network simulation via optimized digital twins. With a more unified approach, carriers can experience compounding improvements across all decision layers by streamlining both long-term planning and real-time execution decisions, ensuring every decision is aligned with overall goals and evolving needs.

Example: Load management

Every mile a truck runs empty or partially full is lost revenue. In fact, according to the U.S. Department of Transportation, trucks run empty 20–30% of the time, resulting in billions of dollars in lost revenue and increased emissions. Smart load management helps meet strict delivery windows, avoid late fees, and enhance on-time performance—all critical for maintaining strong shipper relationships. Decision intelligence enables carriers to identify the most valuable load options for their fleets and strike the right balance between their assets and brokerage, thereby improving asset utilization and profitability.

See also: Practical AI tools in transportation management systems

3. Pressure on the bottom line

The freight market has cooled since the post-pandemic boom. Spot rates have fallen significantly from their 2022 highs, and operating costs remain elevated due to insurance, equipment, and labor costs. Fleets are asked to do more with less—and do it flawlessly.

That economic squeeze is prompting carriers to reassess their existing processes. A combination of low rates and legacy tech is spurring a digital transformation. Today’s fleets can’t continue to operate with outdated systems; they need tools that enable them to work smarter, not just harder. AI offers that edge. By automating repetitive tasks, predicting maintenance needs, reducing detention, and enhancing driver retention strategies, AI helps carriers extract more value from their existing assets.

Example: Maximizing revenue

The trucking industry faced a harsh wake-up call in the post-pandemic market. In the highly competitive trucking industry, profitability hinges on operational efficiency, resource optimization, and smart decision-making. Automation is the key to driving profitability, enabling carriers to reduce costs, maximize resource utilization, and improve overall margins without adding head count.

By automating complex processes, carriers can reduce operational costs by eliminating inefficiencies and streamlining operations, maximize revenue per truck, and handle higher freight volumes with existing resources, ensuring profitability scales along with business growth. Automation drives efficiency and supports revenue growth, enabling carriers to do more with less, turning cost centers into profit drivers.

4. The competitive mandate

It’s not just about keeping pace; it’s about staying in the game. Trucking peers, partners, and customers are investing heavily in AI-powered tools, and the gap between adopters and laggards is widening fast. According to Penske’s newly released 2025 Transportation Leaders Survey: A Road to AI Adoption, fleet leaders are steadily embracing artificial intelligence, with 70% of companies now adopting AI solutions—up 17% from 2024.”

Major fleets are already using AI for freight forecasting, pricing optimization, and even driver safety coaching. As these tools become more affordable and widespread, the industry standard is rising, and the risk of being left behind is real.

Example: Implementing a decision layer

Modern technology is essential for streamlining operations and staying ahead in today’s competitive trucking industry. While implementing a strong TMS or telematics platform is important (and often required), building an ecosystem of integrated technologies that automate and optimize the decision-making process is what will drive long-term success and profitability.

Adding a layer of decision intelligence can help fleets automate the day-to-day load planning and dispatching decisions that can be time-consuming and difficult for team members to make with confidence. Using an extensive array of data supplied through seamless integrations with TMS and ELD systems results in quick implementations and fast results, even for the largest and most complex fleets.

The bottom line: The time for AI is now

The trucking industry is at an inflection point. The companies that adopt AI today are building the foundation for long-term agility, resilience, and profitability. Those who hesitate risk being buried under complexity, outpaced by innovation, and sidelined in the race for freight. Now is the time to rethink operations from planning and dispatch to network design with AI-driven automation at the core.

AI isn’t just a trend—it’s the next competitive differentiator.