2026 Logistics tech trends

One of the most important logistics technology trends for 2026 will be the growing role of AI tools and agents in day-to-day operations, says Brian Smith, CEO, Banyan Technology. Rather than simply serving as standalone assistants, these technologies are becoming embedded in execution workflows to help teams interpret signals, prioritize decisions, uncover cost-saving opportunities and act faster.

“Artificial intelligence is already reshaping logistics, but 2026 will be defined by the rise of more autonomous, decision-capable systems built on a foundation of operational rigor and standardization,” adds Val Marchevsky, CTO, Uber Freight. “The biggest opportunities won’t come from layering AI onto broken processes, but from using it to redesign processes for efficiency, eliminate waste, streamline execution, and help teams move faster and smarter. As these systems evolve, they’ll increasingly identify disruptions, recommend actions, and support real-time decision-making across the supply chain.”

Leading the way for AI-powered advancements in the supply chain, the vendors on AJOT’s 2026 Top Logistics Tech Providers list are driving a range of tech trends this year, including

Agentic AI

Last year AJOT reported: the experts expect agentic AI to be the next phase of the AI revolution. In 2026, the logistics industry is rapidly adopting agentic AI, moving beyond basic automation to systems capable of autonomous reasoning, according to Nimesh Akhauri, CEO of The DDC Group. In fact, analyst firm Gartner expects spending on supply chain management (SCM) software with agentic AI to grow from less than $2 billion in 2025 to $53 billion by 2030.

Bill Driegert, EVP, Convoy Platform, DAT Freight & Analytics explains that while generative AI (GenAI) helps people work faster, agentic AI acts on its own: monitoring capacity, flagging coverage risks, and managing exceptions without waiting for a human to initiate.

“We’re seeing the rapid rise of systems run by AI agents where applications communicate and coordinate directly with each other,” observes Darrin Demchuk, SVP of Product - Fleet North America, Platform Science. “Instead of drivers and dispatchers navigating multiple tools, these intelligent agents will manage workflows in real time across vehicles, back-office systems, and external networks. This shifts transportation from a series of manual processes to a continuous, automated flow, resulting in reduced latency, improved decision-making, and a fundamental transformation in how commercial fleets create value.”

“This year, given the pressures to manage costs and be more efficient, it’s worth asking your providers directly how they’re using agentic AI tools and what results they’re seeing,” Driegert advises.

AI-Supported Decision-Making

“AI is becoming part of everyday supply chain decision-making,” says Dr. Madhav Durbha, Group VP of Manufacturing Industry Strategy, RELEX Solutions. “As volatility persists, companies are investing in AI-driven forecasting, optimization, and decision support to respond faster and operate with greater confidence, even when conditions change quickly.”

“AI is starting to reshape decision-making in logistics, not by replacing people, but by supporting them,” Matthew Fotouhi, Chief Innovation Officer, Magaya elaborates. “In areas like customs compliance, where accuracy matters and ultimate accountability rests with the broker or importer submitting the filing, human judgment remains paramount. The big change is how quickly teams can access and interpret information. AI can surface relevant regulations, flag risks, and digitize data in seconds. What we’re seeing is better, faster decisions, with humans still firmly in control.”

For example, AI can go beyond predictions to recommend operational actions for terminal operators — such as berth planning, crane sequencing, gate scheduling — while clearly showing why those recommendations are made, along with trade-offs and confidence levels, according to Subbu Bhat, Interim President, Head of Engineering, Tideworks Technology.

Load consolidation is another example. Smith from Banyan says AI can evaluate shipment patterns in real time and surface smarter ways to combine freight, reduce waste and improve transportation decisions at scale.

Integration

For years, fleets have managed safety and compliance, toll costs, and weigh station bypass as separate problems with separate vendors and systems — the data rarely connected, says Mike Precia, President and CSO, Fleetworthy. “That is starting to change in a meaningful way. The technology trend to watch in 2026 is integration. As these systems come together, fleets can finally connect data that has been scattered across their business.”

With connected technology and data in place, AI is starting to play a bigger role by identifying patterns, flagging issues, and automating decisions that used to require manual effort, Precia continues. That includes things like validating toll charges, predicting costs, and helping fleets stay prepared for DOT audits. The result is less time spent reacting to problems and more control over cost, risk, and day-to-day operations.

Nick Piette, Senior Director, Product Management. TrueCommerce, adds that a key trend for 2026 is the growing expectation that APIs — the interfaces that allow applications to communicate — must seamlessly fit into increasingly complex, multi-application environments. Users expect APIs to be flexible, interoperable, and easy to integrate across a wide range of tools and workflows.

Zubin Appoo, CEO of WiseTech Global, envisions that disparate point systems will actually be replaced by integrated intelligence platforms that bring all facts of logistics and trade, across the entire supply chain, together for powerful decision making.

“The companies that will outperform are the ones using connected insights to remove cost, improve agility, anticipate market changes, and make smarter decisions across every layer of the transportation network,” concludes Bob Daymon, Head of Client Services, Uber Freight.

AI-Enabled Data Extraction

In 2026, the transportation industry is demanding unified intelligence and AI-enabled data extraction to streamline complex workflows, according to Akhauri from DDC. Carriers are deploying machine learning to instantly transform fragmented, unstructured documents into highly accurate, actionable data. This technology serves as a critical bridge, seamlessly integrating data across networks to eliminate manual work and costly operational blind spots. By empowering faster decisions and reducing waste, this approach allows modern fleets to adapt to market shifts, lower costs, and drive exceptional business outcomes.

AI-Driven Fleet Operations

“Fleet operations are where planning meets reality, and that’s where small inefficiencies add up quickly,” advises James Wee, GM, Fleet Management, Descartes. “AI is starting to close that gap by learning from how routes perform in the field — factoring in real service times, variability and conditions that static plans miss. Over time, that leads to increased route density and more reliable execution, delivering meaningful efficiency gains without adding vehicles, drivers or operational layers.”

AI-Powered Carrier Selection

“For a long time, if you wanted intelligent carrier selection and rate optimization, you had to buy a full TMS and spend months implementing it,” says Jimmy Sebastian, VP of AI Products, FourKites. “AI can now pull real-time rates, factor in historical carrier performance across millions of shipments, and recommend the best option for a specific lane and service requirement on the fly.”

Driegert from DAT adds that AI agents can monitor accepted/rejected tenders, reroute loads to backup carriers, and update tracking, all without manual intervention by the shipper’s TMS team.

Direct Carrier Connectivity

Brian Thompson, Chief Commercial Officer, SMC3 explains that AI agents must operate on reliable, high-fidelity data. Direct carrier connectivity that supports continuous data exchange is preferable to web crawling and static file transfers because it enables AI to scale with higher performance and lower maintenance costs.

Ship-To-Shelf Cargo Orchestration

Supply chain operations are being transformed by innovations that bridge the gap between terminal, yard and last-mile delivery, according to Brian Taylor, VP of Transportation Solutions, Kaleris. Ship-to-shelf or port-to-door orchestration platforms enable real-time operational visibility and data synchronization across every cargo handoff from port arrival to rail ramp to yard operations to store or home delivery. This integrated approach eliminates operational blind spots, streamlines asset tracking, and empowers teams with precise, actionable insights for dispatch and dwell-time management.

AI-Enabled DPS

“AI-enabled denied party screening is changing how organizations manage compliance at scale,” says Brian Hodgson, GM, Trade Compliance, Descartes. “Traditional screening tools tend to generate large volumes of potential matches, many of which require manual review but pose little real risk. By applying machine learning to better distinguish between low-risk and high-risk results, these solutions help reduce false positives while maintaining oversight — freeing compliance teams to focus on genuine risk, improving efficiency and consistency across increasingly dynamic global trade environments.”

AI-Empowered Risk Mitigation

“We are entering a new era of intelligent logistics,” Appoo from WiseTech concludes. “The closure of the Strait of Hormuz and other geopolitical events have escalated the need to not only better predict the impact of major disruptions but also be able to execute pre-planned risk mitigation actions immediately. Vast amounts of intelligence and data related to changing regulations, policies, tariffs, sanctions, embargoes, restricted parties and other industry data create an environment where logistics operators need to have the ability to make safe and compliant decisions in an increasingly complex and rapidly changing world. Leveraging these rich datasets through AI in an integrated way in logistics systems will help identify which shipments may be at risk and put risk mitigation plans into action — immediately.”

John Lash, Group VP of Product Strategy at e2open, adds, “Twelve long months of trade wars – defined by on-again, off-again tariffs – have taught us that the only certainty in trade policy is uncertainty. As we enter this new era of permanent trade volatility, look for tariffs to become increasingly embedded in the core SCM tools used for planning, sourcing, and logistics — it’s simply too disruptive to do in siloes anymore.”