Why AI freight tools still sit in pilot mode at most carriers

What's stopping carriers from moving AI past the pilot stage?

Two obstacles tied for first: workforce skills and an unclear return on investment. Each hit 33% of respondents in a new survey from the Association for Supply Chain Management (ASCM) and the Digital Supply Chain Institute (DSCI). Poor data quality followed at 25%. Executive skepticism didn't make the list.

The survey, released Oct. 14, found that 83% of supply chain professionals said their employees are unprepared to use AI effectively. The 17% who described their workforce as ready reported a 71% AI project success rate. Everyone else reported 28%, and about 64% of that group is still in the pilot or planning stage.

Freight technology vendors are selling AI agents that can benchmark rates and award freight under rules a customer sets. The survey found most supply chain organizations still limit AI to generating insights.

The report scored AI adoption across 13 core supply chain functions on a scale from 1 (no AI use) to 5 (autonomous execution without human review). The average was 1.94.

Planning functions scored highest. Demand planning led at 2.28, and supply and inventory planning hit 2.12. Execution-heavy functions trailed. Returns and reverse logistics ranked last at 1.59.

Why companies keep AI on a short leash

The report calls this keeping AI on a "short leash" and says companies doing it are using predictive tools as "little more than digital spreadsheets."

"I think we're using it much more on the analysis and on the predictions as opposed to the doing," Abe Eshkenazi, CEO of ASCM, told FreightWaves. He called it "more of a glorified spreadsheet."

He sees room for AI to take on "routine transactional decisions where AI can operate within parameters," with people keeping the higher-risk calls on customer commitments, sourcing, and major disruptions.

"We need to expand the AI authority, but we need to do so with confidence in the technology, and it's not there right now," he said.

Eshkenazi compared AI to enterprise resource planning (ERP) systems, which were also expected to revolutionize supply chains.

"The technology solution can't improve bad process and it can't improve bad data," he said.

Companies should use value stream mapping and data analysis to find and fix problem areas before an ERP project starts, he said.

What AI success actually looks like for a carrier

Headcount reduction is too simple a measure of AI's return, in Eshkenazi's view. The better one is response time: how quickly a company can recognize a disruption, weigh alternatives, and act.

"You can't point to a system and say it made the decision," Eshkenazi said. "Ultimately, somebody has to own that decision for the organization."

The survey found that 82% of C-suite respondents lead, implement, or scale AI initiatives. At the director level, 12% lead AI efforts directly, and half of directors said they are only aware of them. The aware-only share rises to 51% of managers and 70% of staff.

Those breakdowns rest on small samples. The survey collected 144 responses, and 107 met the criteria for analysis. Only 11 respondents were C-suite executives, and the report labels its results by job level as directional.

Only 7% of respondents predict AI will directly replace workers, while 51% expect it to move people toward higher-value decision-making.

The training gap AI creates for new dispatchers and planners

Eshkenazi said that shift carries a cost. Supply chain professionals used to build judgment by running the analysis, building the reports, and working the spreadsheets, which taught them to spot exceptions and ask whether the numbers looked right.

"A lot of those foundational activities and experiences are now being taken over by AI, and we're moving individuals into positions where they have to make decisions and manage without understanding the fundamentals," he said.

Technology more powerful than companies are using, paired with workers who can't critically think through what it produces, is "a very dangerous combination for organizations," he said.

Cybersecurity exposure through AI-connected partners

Of those surveyed, 92% expressed significant concern about cybersecurity exposure through AI-enabled suppliers and trade partners. According to the report, the average organization had adopted 2.3 of six standard cybersecurity practices.

Eshkenazi traced the exposure to the visibility push that followed the pandemic, when companies began connecting suppliers, carriers, and brokers on shared platforms.

"It's exposing them to significant ransomware and cybersecurity risks in their tier-three and their tier-four vendors, where predominantly they don't have a lot of resources," he said.

Food distributors on a conference panel in San Antonio described one way that plays out: a compromised carrier email that led to a fraudulent pickup of a cold-storage load.

Calling a tier-four vendor for inventory and delivery status isn't an option, he said. "Huge opportunity but also significant risk," he said.

Where to start if you're testing AI in dispatch or planning

Eshkenazi's first recommendation is to pick one high-value process, such as a key customer process, supplier, or route, and involve the people who run it.

"Then establish measurable outcomes," he said. "First, you have to identify where you're starting from."

That work has to reach below the leadership level, he said, so employees see AI as a path to more valuable work.

"Just because it's a technology solution doesn't make it autonomous and doesn't make it better if you don't have qualified processes, if you don't have knowledgeable workers, and if you don't have clean data," Eshkenazi said.

If you're running a small fleet and looking at a head-to-head look at TMS platforms with AI features, the survey suggests you start with one route or one customer and measure response time, not headcount savings. Train the dispatcher or planner who will actually use the tool before you flip it on.