The new report, “The Execution Gap: What Supply Chain Leaders Are Saying About Technology,” published by ABI Research and FourKites, found that although 28% of companies cite working capital optimisation as their top investment driver, only 37% use AI for risk management, the area most directly linked to preventing costly delays, detention fees, and expedited freight.
According to the study, 28% of companies identified working capital optimisation as their top investment driver, ahead of competitive advantage (15%) and sustainability compliance (8%). Yet only 37% use AI for risk management, even though disruptions and delays are among the main causes of trapped cash in supply chain operations.
The authors argue that companies are deploying AI in the wrong places: focusing on demand forecasting or analytics instead of disruption prevention and real-time execution.
“Executives want working capital improvements, yet they deploy AI for demand forecasting instead of disruption prevention,” the report notes. “They’re analysing problems instead of preventing them.”
Europe lags the U.S. in AI adoption
The survey found notable regional differences. While 31% of North American companies said they use AI for autonomous decision-making, the figure was just 19.5% in Europe.
In Germany, only one in three respondents (33%) use AI for risk management, compared to 48% in the U.S.
When it comes to inventory management, North American adoption reached 48%, while Europe stood at 31%. This gap, according to ABI Research, indicates that European organisations remain more cautious about handing operational decisions to AI systems.
The “trust gap” in autonomous AI
Across all respondents, 52% use AI for decision support, where systems provide recommendations, but only 27% allow AI to take autonomous action. This “trust gap,” the report argues, limits the technology’s potential to deliver measurable savings.
Companies are willing to use AI for predictable, low-stakes tasks such as demand forecasting or customer service, but tend to avoid deploying it for risk management, precisely where it could prevent expedited freight, detention fees, and excess safety stock.
Organisational barriers, not data, hold companies back
The findings suggest that the biggest challenge is organisational rather than technological. Sixty-five percent of respondents said they lack clear Standard Operating Procedures (SOPs) for acting on real-time alerts generated by their visibility platforms. Another 53% reported insufficient authority for operational teams to act quickly, and 70% cited weak cross-functional coordination.
In practice, this means that even when companies have visibility into disruptions, they often cannot act on it without multiple approvals or departmental meetings, turning visibility into what the report calls “perfect paralysis.”
Integration, not data quality, is the top obstacle
While poor data quality often dominates discussions about digitalisation, respondents said the real barriers are legacy integration (46%), tool fit (46%), and skills availability (46%). These technical and organisational issues make it difficult to connect AI solutions with existing systems such as ERP, WMS, and TMS.
Ryan Wiggin, Senior Analyst at ABI Research, said:
“Success requires data interoperability across systems, defined processes for action, and organisational readiness, elements that many companies currently lack.”
Companies expect rapid ROI — not multi-year transformations
Working capital pressures are forcing companies to focus on measurable, short-term returns. Most supply chain investments now target four- to eight-month payback periods, not multi-year transformation projects.
The majority of control tower projects cited in the report cost between $50,000 and $250,000, with fewer than 7% exceeding $500,000. ABI Research notes that “a well-adopted $100,000 system beats an ignored $500,000 platform every time.”
Few companies ready for AI that acts, not just analyses
A smaller group of 156 respondents said they “strongly agree” with using AI for autonomous decision-making. These companies have already begun linking AI directly to operational systems, enabling automatic prevention of detention fees, expedited freight, and excessive inventory.
Their experiences suggest that financial benefits come when AI is embedded into daily operations, not treated as an analytical tool. The report concludes that companies using AI for autonomous action see the strongest results in working capital efficiency.
“Fix the organisation before buying more tech”
The report summarises its key recommendations in three points:
- Fix processes first – Create clear SOPs and empower teams to act on real-time alerts.
- Build trust in AI gradually – Start with decision support and evolve toward autonomy.
- Link every project to cash flow – Frame investments in terms of days of inventory saved, detention fees avoided, and expedited freight prevented.
ABI Research and FourKites conclude that the next stage of supply chain digitalisation will depend less on technology availability and more on organisational readiness.
“Visibility is table stakes. The gap is execution,” the report states. “The technology works. The ROI is there. Companies just need to let it run.”
