More than 70% of supply chain executives believe artificial intelligence will be the most disruptive technology over the next decade, while roughly a quarter expect disruptions caused by AI to be transformative for the logistics sector. MHI CEO John Paxton stated during his opening remarks at MODEX 2026 in Atlanta, Georgia on April 15: "Supply chains can no longer be optimized at the edges. Only connected, intelligent and automated real-time networks will withstand the volatility and meet the future customer demands for speed and efficiency." From a supply chain perspective, the concept of connected and real-time network requires warehouse management system (WMS), transportation management system (TMS), and yard management layers to operate with API-based integrated data flows. MODEX, held biannually, is the largest gathering point for the material handling sector.
In a chaotic geopolitical environment, planning for the future has become more difficult than ever, and artificial intelligence is viewed by supply chain leaders as a fundamental tool to mitigate these effects. According to a survey of 500 supply chain professionals conducted by MHI and Deloitte, 41% of participants report already adopting AI technology in some form, while another 47% expect to adopt AI within the next five years. From a supply chain perspective, the 88% total adoption intent demonstrates the maturity curve is compressing rapidly; the laggard group may face competitive disadvantages within the next two to three years. Talent gaps in change management, data engineering, and MLOps represent the most significant barriers to this trend.
The survey also reveals AI usage priorities. Within the next two years, 33% of participants plan to use the technology for inventory optimization; 30% aim to improve equipment predictive maintenance; and 27% plan to automate operational decision-making. Despite the urgency of AI adoption, ensuring that actual investments in technology are targeted and strategic is equally important. Carvana's regional logistics director Camille Blake, speaking on a panel following Paxton's presentation of the MHI report, stated: "All of the data suggests that the companies that are going to win are the ones that are being very thoughtful and intentional about how they add technology to their business." From a supply chain perspective, predictive maintenance becomes possible by evaluating sensor streams—vibration, temperature, and current—from equipment such as conveyors, AS/RS, and AGV/AMR systems using machine learning models.
Blake notes this means ensuring an organization has a strong operational foundation. Leaders must fully understand what problems they want AI to solve and how current processes can adapt to those objectives. Blake cautions that without the right fundamentals in place, any adoption initiative may fail to gain traction. Blake further adds: "Where we are struggling or getting it wrong is by trying to do the technology before we do everything else right. If you have a level of instability in your operations, you're not ready, and you have to be honest about that." From a supply chain perspective, process maturity is assessed using the SCOR (Supply Chain Operations Reference) model, and before adding an AI layer, systematic data flows and standardized workflows must exist at level 3. In conclusion, the MHI-Deloitte survey demonstrates that AI is entering the mainstream as a disruptive force in the logistics sector, though successful implementations are closely tied to operational maturity.
Key Takeaways:
1. More than 70% of executives view AI as the most disruptive technology over the next decade.
2. The MHI-Deloitte survey shows 41% already adopting; 47% plan adoption within five years.
3. Next two years: 33% inventory optimization; 30% predictive maintenance; 27% decision automation.
4. Paxton sees connected, intelligent, and automated real-time networks as essential.
5. Blake emphasizes that deploying AI amid operational instability carries high failure risk.
