Supply chains have undergone an era of rapid investment. Over the past decade, logistics leaders have poured millions into robotics, AI, predictive analytics, and automated warehousing to drive efficiency and resilience. But as global trade realigns and cost pressures mount, the focus is shifting. The question is no longer whether to automate—it’s whether these investments are delivering the agility, cost control, and network flexibility required for the next phase of supply chain transformation.
EY’s Q1 2025 Supply Chain Update signals a critical shift in how logistics networks are evolving. Protectionist trade policies, rising trucking and freight costs, and a sharp increase in third-party logistics (3PL) leasing activity all point to a landscape where logistics teams must refine their approach. Investments in automation and AI must go beyond efficiency gains and actively contribute to broader business resilience, risk mitigation, and real-time adaptability.
The New Logistics Landscape: Where Technology Meets Trade Disruptions
The logistics sector is facing a new round of complexity, driven by a mix of trade disruptions, rising transportation costs, and changing warehousing strategies.
New tariffs on Canada, Mexico, and China—though temporarily paused in some cases—are already reshaping sourcing and distribution models. Companies that once relied on low-cost, centralized fulfillment centers are being forced to rethink inventory positioning and cross-border logistics strategies. While procurement teams shift sourcing patterns, logistics leaders must optimize transportation networks, assess regional distribution hubs, and determine whether their existing warehouse automation models are still fit for purpose.
Freight costs are another pressure point. EY’s report highlights a resurgence in trucking spot rates, signaling a tightening capacity market that could drive long-term contract rates higher. Logistics leaders must anticipate cost fluctuations and embed greater flexibility into carrier negotiations. The role of AI-powered dynamic routing, real-time rate benchmarking, and predictive capacity planning will become critical—not just for cost reduction but for maintaining service levels amid volatility.
Warehousing Strategies Are Shifting—And That Means Rethinking Automation
A 9% increase in 3PL warehouse leasing over the past year reflects a major structural shift in how companies manage inventory and fulfillment. The push for owned, fully automated mega-warehouses is evolving into a more distributed, flexible approach where outsourced fulfillment centers play a bigger role.
This raises a critical question for intralogistics leaders. How do you scale automation when warehousing is becoming more decentralized? Many organizations have made significant investments in automated picking systems, autonomous mobile robots, and AI-powered warehouse orchestration within fixed infrastructure. But as networks become more fragmented, leaders must assess whether these technologies remain effective when inventory is more fluid, fulfillment is shared across partners, and demand shifts more dynamically.
Logistics executives are increasingly deploying cloud-based, AI-driven warehouse management systems that can seamlessly integrate across internal and 3PL-run sites. The goal is to ensure that automation doesn’t just optimize individual facilities but enhances network-wide agility, allowing companies to scale operations up or down without heavy infrastructure dependencies.
From Efficiency to Resilience: The New Automation Playbook
Automation in logistics is no longer just about improving picking speeds or reducing labor costs. It must actively contribute to real-time supply chain resilience. Leading companies are now using AI and robotics not just for fulfillment, but for adapting to shifting conditions across global logistics networks.
The next frontier in logistics technology is predictive and prescriptive AI, which enables organizations to move from reactive problem-solving to proactive risk mitigation. Instead of simply tracking shipments and optimizing routes, AI is now being used to predict supply chain disruptions, dynamically reassign freight, and automate supplier shift decisions based on real-time trade and cost data.
As companies refine their approach, logistics leaders must focus on three key areas of optimization. Network fluidity determines how well automation integrates across owned and 3PL sites and whether fulfillment can be reallocated in real time. Cost predictability relies on AI-driven forecasting and contract models that hedge against freight volatility. The scalability of automation must be evaluated to determine whether robotics and AI investments are adaptable to evolving warehousing models or locked into rigid infrastructure.
What Comes Next for Logistics Leaders?
The logistics sector is entering a phase where previous investment cycles must now deliver more than incremental efficiency gains. Robotics, AI, and automation will remain central to logistics transformation, but their success will be measured differently. Flexibility, network-wide integration, and resilience will determine which companies truly capitalize on their technology investments.
EY’s Q1 2025 Supply Chain Update highlights how the logistics sector is evolving amid macroeconomic shifts, but the leaders who come out ahead will be those who don’t just react to cost pressures and trade disruptions but actively use technology to make their supply chains more adaptable, predictive, and responsive.
Read the full EY Quarterly Supply Chain Update (Q1 2025) here.
