FourKites: Supply Chain Leaders Deploying AI in Wrong Place

FourKites and ABI Research have partnered in a research study to explore how AI is being used in the workplace.

The report, The Execution Gap: What Supply Chain Leaders Are Saying About Technology, used the insights of professionals within manufacturing, retail and logistics to examine why companies are not seeing the benefit of AI.

According to the report, there exists a disconnect between opinions on AI and how it is being implemented into business operations. 

Supply chain transformation

FourKites is a leader in AI-driven supply chain transformation, harnessing advanced real-time visibility to turn supply chain data into automated action, so professional can focus on value-adding activities. 

The firm helps more than 1,600 global brands prevent supply chain disruptions through its processing network of more than 3.2m supply chain events every day, covering everything from purchase orders to final delivery.

FourKites' latest research, undertaken alongside ABI, examines why professionals are failing to unlock AI's potential across their businesses. 

The report gathered insights from almost 500 professionals across manufacturing, retail and logistics, and found most companies are implementing AI strategies in the wrong area, resulting in less-than-optimal outcomes. 

"Executives want working capital improvements, yet they deploy AI for demand forecasting instead of disruption prevention. They're analysing problems instead of preventing them,” said Mathew Elenjickal, founder and CEO of FourKites.

“In contrast, the 27% of organisations willing to use AI for autonomous execution can prevent detention fees before they occur, eliminate expedited freight by managing exceptions proactively, and reduce safety stock by guaranteeing reliable operations.

"These are direct hits to the balance sheet, delivered through AI that acts, not just analyses."

The survey was specific to businesses based in Germany, the US, Mexico and Malyasia, and discovered some distinct regional differences. 

Overall, 27.6% of respondents said that working capital optimisation is the leading investment driver, ahead of competitive advantage (14.9%) sustainability (8.4%). However, only 37% are using AI for risk management in a situation where it actively prevents financial loss and disruption.

Broken down regionally, only 33% of respondents in Germany use AI for risk management, as opposed to 48% in the US. Less than a third (31%) of German firms are using AI for inventory management compared to 55% in the US.

German companies (20%) are also lagging behind US counterparts (31%) when it comes to using AI for autonomous execution. This has the potential to hamper their ability to respond to incidents in real time, resulting in extra costs and operational delays.

"The survey identified key factors that determine whether AI investments achieve strategic goals like working capital optimisation," said Ryan Wiggin, Senior Analyst at ABI Research.

"Success requires data interoperability across systems, defined processes for action, and organisational readiness – elements that many companies currently lack."

Barriers to efficiency

Despite companies wanting to integrate technology and AI into their systems, the disconnect continues. 

According to the research, data issues are often overshadowed by integration challenges, with 46% of respondents citing legacy integration and tool fit as the main barriers to successful workflow. 

This means companies are either struggling to combine AI tools with existing systems or simply don't know where to begin. 

It shows the success of data integration is reliant on the ability to connect the AI solution to existing systems, rather than requiring a complete overhaul. 

Of the 490 respondents, 156 "strongly agree" with AI being used for autonomous decision-making, acknowledging that optimal efficiency relies on the ability to prevent disruption, rather than merely reacting to it. 

Those companies are the ones beginning to see working capital optimisation through the end-to-end integration of AI.