GOODQUESTION
RUSHED DEPLOYMENT and incomplete data. Shippers must understand where AI data comes from and whether it reflects today’s real-world operating conditions. AI won’t solve capacity or service challenges, but with strong data governance, it can improve predictions and real-time insight. –Mika Majapuro VP, Product Management, TransmetriQ NO COMPETITIVE EDGE. Anyone can add generic AI tools to their tech stack. Dierentiate by leveraging unique data, refining AI for specific needs, and aligning it with strategic goals from the ground up. Oer a solution that no one else has. –Kevin McMaster SVP, Customer Success & Operations, Flock Freight DATA GAPS. Assuming AI can compensate for gaps in operational data is one pitfall. Many supply chains still depend on periodic scans or checkpoint tracking, leaving gaps in visibility. If AI is fed fragmented signals, it can produce misleading outputs at scale. First, improve how data is captured. –Simon Ford Founder & CEO, Blecon MISSING INPUTS. Algorithms may not fully account for temperature, chain-of-custody, or compliance, and AI decisions can be opaque. Overreliance on historical data may miss sudden spikes in urgent shipments. Stakeholders should use AI to support, validate recommendations, train sta, and maintain oversight for high-priority or sensitive shipments. –Lorena Camargo President, Customized Logistics & Delivery Association (CLDA) AUTOPILOT MODE. If AI makes a mistake based on bad data, it can snowball before anyone notices. Stakeholders must keep humans in the loop to vet big decisions and ensure the “math” aligns with real- world common sense. –Bradley Barry Director & Partner, Supply Chain Services, St. Onge Company
Protect and Validate Your Data
Adoption is outpacing management. Two risks stand out. First, security: Sensitive data is moving across more systems, often without proper oversight. Start by auditing access and reviewing it regularly. Second, signal integrity: AI outputs depend on data quality and degrade over time. Monitor inputs and validate models. –Scott Stonys Head of Sales & Customer Success, Spotter AI AI in supply chains is creating new routes for cascading breaches. Poorly governed tools risk leaking data or linking systems in unintended ways; firms need tighter supplier oversight, clearer permissions, and human sign-o for critical automated actions. –Melissa Carmichael Head of U.S. Cyber, Beazley
LACK OF CUSTOMER SERVICE. Freight forwarders shouldn’t assume that deploying AI tools can replace the value of customer service excellence. An experienced operator can read a customer’s urgency, stress, and expectations in a way no algorithm can. The real advantage lies in combining human insight with AI for route optimization, shipment visibility, and pricing options. –Sean Yanok VP Regional Development, Gebrüder Weiss FRAGILITY. Optimizing just for cost strips out buers, creating fragility. Algorithms that human operators don’t understand lead to errors without accountability. Human intuition gets weaker over time like an unused muscle. Solutions: Train AI to value redundancy, not just eciency. Demand tools and workflows where AI oers recommendations and a human makes the final call.
map where humans need the most lift, pilot with clear guardrails, and measure outcomes for all parties, not just speed. –Carly Gunby VP Revenue, Transfix WRONG ANSWERS. AI amplifies everything—including inconsistent, outdated, or duplicated information from trading partners. The result: confident wrong answers at machine speed. Stakeholders should automate data validation at the point of ingestion, before feeding AI systems. Clean, governed data flows are the foundation for any AI initiative. –Michael Bevilacqua VP AI Product Management, Adeptia
–Nick Rakovsky CEO, DataDocks
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CHANGE MANAGEMENT WHIPLASH and job security fears, plus AI agents that negotiate without real transportation context, eroding trust. Fix it by leading with strategy:
May 2026 • Inbound Logistics 7
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