83% of supply chain leaders say their workforce can't use AI

Eighty-three percent of supply chain professionals say their employees are unprepared to use AI effectively, according to an ASCM and Digital Supply Chain Institute survey released Oct. 14 — and that workforce gap, not the technology, is what's keeping AI stuck in analysis mode while vendors sell tools that can award freight on their own.

The report, titled The People Paradox in Supply Chain AI Integration, draws a sharp line between the ready and the rest. The 17% who described their workforce as prepared reported a 71% AI project success rate. Everyone else reported 28%. Roughly 64% of that second group is still in pilot or planning.

Freight tech vendors are already marketing AI agents that benchmark rates and award freight under customer-set rules. Most supply chain organizations haven't come close to delegating that authority.

Where does AI actually get used?

The survey scored adoption across 13 core supply chain functions, from 1 (no AI use) to 5 (autonomous execution without human review). The average landed at 1.94 — below basic insight generation.

Planning functions scored highest:

• Demand planning: 2.28
• Supply and inventory planning: 2.12
• Returns and reverse logistics: lowest, at 1.59

The report calls this keeping AI on a "short leash," with predictive tools serving as "little more than digital spreadsheets." Abe Eshkenazi, CEO of ASCM, reached for the same image.

"I think we're using it much more on the analysis and on the predictions as opposed to the doing," he told FreightWaves, calling current use "more of a glorified spreadsheet."

Eshkenazi sees room to expand AI into "routine transactional decisions where AI can operate within parameters," with people retaining the higher-risk calls on customer commitments, sourcing and major disruptions. But the confidence isn't there yet. "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.

He noted most AI sessions at supply chain conferences follow the same arc — challenges, implementation, benefits — and end with a reminder not to forget about the people. "It's interesting because from our perspective that's where you ought to start the conversation," he said.

What's blocking adoption?

Two barriers tied for the top spot at 33% each: lack of workforce skills and resources, and an unclear business case or return on investment. Poor data quality followed at 25%. Executive skepticism didn't make the main list.

Eshkenazi compared AI to ERP systems, which were also billed as supply chain revolutionaries. "The technology solution can't improve bad process and it can't improve bad data," he said. Companies should map value streams and fix problem areas before the project starts.

Headcount reduction is too crude a measure of AI's return, in his view. The better metric is response time: how fast a company recognizes a disruption, weighs alternatives and acts.

"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."

Who's actually involved?

Engagement collapses below the C-suite. Some 82% of C-suite respondents lead, implement or scale AI initiatives. At director level, 12% lead AI efforts directly and half say they're merely aware of them. The aware-only share rises to 51% of managers and 70% of staff.

The caveats are real. The survey collected 144 responses, 107 of which met analysis criteria. Only 11 respondents were C-suite executives, and the report labels its job-level breakdowns as directional.

Will AI take jobs?

Only 7% of respondents predict AI will directly replace workers. Fifty-one percent expect it to shift people toward higher-value decision-making. Eshkenazi warned that shift carries a cost: professionals once built judgment by running the analysis, building the reports and working the spreadsheets.

"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. Powerful technology paired with workers who can't critically assess its output is "a very dangerous combination for organizations."

How serious is the cyber exposure?

Ninety-two percent expressed significant concern about cybersecurity exposure through AI-enabled suppliers and trade partners. Yet the average organization has adopted just 2.3 of six standard cybersecurity practices.

Eshkenazi traces the exposure to the post-pandemic visibility push, 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 San Antonio conference panel described one concrete failure: a compromised carrier email that led to a fraudulent pickup of a cold-storage load. Calling a tier-four vendor for status updates isn't an option, Eshkenazi noted. "Huge opportunity but also significant risk."

His starting advice: pick one high-value process — a key customer, supplier or route — involve the people who run it, and set measurable outcomes. "First, you have to identify where you're starting from," he said. "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."

With adoption averaging 1.94 on a five-point autonomy scale, that groundwork — not more capable software — looks set to govern how fast supply chain AI moves from pilot to production.