What Logistics Function Will AI Have the Most Profound Impact On?
Expert insights on the functions and solutions most ripe for AI impact.
Risk management because artificial intelligence (AI) enables predictive analytics. Reactive plans and over-engineered remediation will turn into proactive strategies that catch breakage and capacity constraints in supply chains before they emerge.
–Mike Van Horn
AVP, AT&T Connected Solutions
AT&T
Supplier and carrier collaboration. AI agents will transform collaboration through automation and real-time recommendations. They can make faster and more accurate decisions than humans in many cases and are always on.
–Sriram Nagaswamy
Executive Vice President, Technology
FourKites
Task optimization is an area where we will see significant changes. Whether an operations manager distributes work for the next 24 hours or a transportation planner determines routes, AI applications will have a tremendous impact on leveling up the multi-variable calculation element of task management far beyond that which a human alone can execute.
–Jordan Lawrence
VP Commercial Strategy
AutoScheduler.AI
Transportation management systems. AI will be used in freight management to advance TMS software functions. This will allow processes to improve and help with decision-making, providing true operational benefits.
–Rick LaGore
Co-founder and CEO
InTek Freight & Logistics
Distribution center management. Continuously analyzing growing warehouse data sets will enable predictive AI to develop and deliver key recommendations to management during daily operations. Allocating staff and workload in real time to maximize service and efficiency will soon be more effectively performed by predictive AI engines.
–Sandy Stephens
Chief Strategy Officer
HyTek Intralogistics LLC
Route Optimization
AI-driven route optimization will redefine delivery efficiency. By analyzing traffic patterns and environmental factors, AI will minimize travel time and costs, enhancing the reliability and sustainability of last-mile logistics.
–Dennis Moon
COO
Roadie
AI has the potential to not only lower cost (both fuel and labor), but also improve delivery speed, increase volume, and lower CO2 impact. It also offers the opportunity to respond in real time, whether that’s weather-dependent or a larger-scale crisis.
–Raj Ramanan
CEO
Jitsu
Rate management, especially quoting. By utilizing AI-driven quoting, transportation teams can improve data quality, manage rates proactively as markets change, and mitigate risks more efficiently across all lanes.
–Edmund Zagorin
Founder & Chief Strategy Officer
Arkestro
Data integrations. AI will speed up data integrations between customers and their 3PL partners, giving them agility and visibility across the supply chain. But, 3PLs will need to move fast; AI-enabled data integrations also make it easier for customers to switch providers.
–Bart Bullard
VP of Information Technology
Source Logistics
Inventory management. AI will create the ability to automatically see stock levels and initiate stock replenishment based on demand. This will help product availability and minimize manual inventory tracking.
–Nick Shorthose
Vendor Manager
Communisis
Decision intelligence. Historically, logistics operations have been data rich but insight poor. AI will have a profound impact on our ability not only to quickly analyze and resolve situations by contextualizing data from disparate sources to drive intelligent decision-making, but to improve outcomes for the long term.
–Ilya Preston
CEO
PAXAFE
Customer service. AI-powered chatbots/platforms will boost customer service by streamlining inquiries, tracking, and issue resolution, improving overall experiences and reducing costs.
–Ari Widlansky
U.S. Managing Director and
Chief Operating Officer
Esker
Demand Forecasting
Pure-play AI is helping with better predictions. In the longer term, pure-play AI will start to replace algorithmic code. ChatGPT is not suited for supply chain functions that require sequential activities.
–Tom Moore
Founder & CEO
ProvisionAi
AI enhances demand forecasting by processing vast data sets, identifying patterns, and integrating external factors like climate and social trends. It simplifies complex forecasting as SKUs and market channels expand.
–Mike Gross
Chief Technology Officer
TrueCommerce
Process efficiency and information sharing in the near term since AI enables intuitive onboarding and guiding users through tasks. In the long term, AI has the potential to revolutionize supply chain logistics by synthesizing intelligence across risk mitigation and route optimization.
–Doug DeLuca
Product Marketing Manager
SAP Business Network
Productivity. AI’s greatest impact won’t be on one thing like route optimization or inventory management. Rather, it will help connect all these functions, breaking down silos and refocusing workers on more strategic initiatives. The ideal scenario is that AI becomes a productivity multiplier across the entire industry.
–Maneet Singh
Chief Information Officer
Odyssey Logistics
Picking operations. With 60-70% of labor costs tied to picking, AI’s ability to optimize routes, reduce errors, and predict demand offers massive efficiency gains.
–Erhan Musaoglu
CEO & Founder
Logiwa
Exception management. For example, when extreme weather like a hurricane or a black swan event like the Baltimore bridge collapse disrupts port operations, AI can help supply chain teams predict how the disruption would impact ETAs and proactively mitigate the effects by rerouting containers.
–Chelsea Quint
Product Marketing Manager
project44
Decision support. By integrating AI with human analysts and data analytics, companies can enhance decision-making regarding asset acquisition and management, allowing for smarter capital expenditures.
–Brian Antonellis
CTP, SVP Fleet Operations
Fleet Advantage
The List Goes On and On
AI is optimizing entire supply chains through improved data analysis and efficiencies to match supply with demand. Manufacturing, distribution, inventory management, demand planning, and marketing functions will all be impacted.
–Barry Bradley
Head of Supply Chain, Crisp
With a large dataset, AI will significantly impact all aspects of supply chain and logistics. With significantly rising inventory carrying costs driven by real estate, insurance, and employee costs, organizations need to use AI to optimize demand planning.
–Tom Kieley
CEO
SourceDay
Where we see the biggest benefits right now are in risk analysis, supply chain simulation and optimization, and automating engagement across stakeholders. However, AI can and will drive much deeper transformation in our industry.
–Neil Wheeldon
Chief Digital & Innovation Officer
PSA BDP
Supply chain efficiency. When items can be tracked through the supply chain, AI can predict demand, flag potential shortages, and automate replenishment cycles, helping to streamline operations.
–Jeff Dossett
Chief Revenue Officer
Impinj
AI is already reshaping risk mitigation by predicting potential disruptions in supply chains. Through real-time data analysis of port conditions, weather patterns, and supplier risks, AI and machine learning have empowered logistics teams to proactively address issues so they can reduce costly delays and losses in transit.
–Lilian Bories
Director, Marketing
TradeBeyond
Reducing missed sales. AI can predict demand with greater accuracy, helping manufacturers, wholesalers and retailers avoid stockouts and lost sales. By analyzing historical data, promotional activities and external factors, AI can forecast which products will be in high demand and ensure they’re always available.
–Eugene Van Zyl
SAP Chief Architect
Syntax
Automation and forecasting. We’ve seen a glimpse of how it is optimizing routes, managing inventory and driving automation. In the future, as data and compute power will get democratized, more companies will be able to leverage AI to reduce empty miles, optimize demand and forecast accurately—and in the end, help both shippers and carriers become more efficient.
–Yoav Amiel
Chief Information Officer
RXO
Warehouse management. AIoT-powered warehouse management ingests substantially more historical and real-time data sets and leverages more sophisticated models to predict, identify, and avoid order management and fulfillment errors. This provides more accurate inventory, fewer delivery errors, increased customer satisfaction, lower holding costs, reduced labor costs, and lower cost of quality.
–Jim Gripp
Senior Director, Product Management
Powerfleet
AI will alter inventory management by making it seamless and invisible. What-if AI could predict demand in real-time, shifting inventory before it is needed? Everything would move where it’s needed, effortlessly balancing supply and demand, creating a perfectly optimized, behind-the-scenes system that keeps things running smoothly without disruption.
–Stephen Dombroski
Director, Consumer Markets
QAD
Prescriptive analytics. Moving from predictive to prescriptive analytics involves transitioning from forecasting future outcomes to recommending specific actions based on those predictions. This requires more comprehensive datasets, advanced algorithms and context awareness to provide actionable insights. These insights will continuously be refined as new data is introduced to the AI models.
–Kevvon Burdette
Chief Commercial Officer
Princeton TMX
Repeatable high-frequency tasks involving human to machine curation will benefit most from generative AI. Top early logistics use cases include applications in customer service, status inquiries, basic bidding and pricing inquiries, contextual data processing, image analysis, and natural language analytics.
–Ken Wood
Executive Vice President, Product Management
Descartes
Meeting customer expectations. Shifting customer expectations and the fickle nature of consumer demands puts an immense strain on the supply chain industry. We think AI can be leveraged to alleviate this burden and greatly benefit demand forecasting through predictive analytics. By using historical and real-time data, companies can proactively manage resources to meet consumer expectations head-on.
–Kristen Fullam
Director of Strategic Programs
Advantive
Four main areas: (1) AI will improve productivity by automating functions or streamlining underlying processes with better decision support, (2) enhance user experience by making information easier to find, (3) support operations with robust and readily accessible insights, and (4) reduce software implementation time by accelerating configuration, extension development or both.
–Adam Kline
Senior Director, Project Management
Manhattan Associates
Inventory management—where AI’s impact is already tangible. As small- and medium-sized businesses face mounting pressures across supply chains, AI-powered solutions unlock intelligent expertise to make real-time strategic decisions and boost visibility.
–Barry Kukkuk
CTO
Netstock
Logistics and demand planning. For example, generative AI is enabling risk mitigation by rapidly assessing logistics scenarios and planning contingencies. Agentic AI is enabling real-time, autonomous decision making to optimize routes for carriers.
–Matthew Bunce
Decision Intelligence Engagement Principal
Aera Technology
Demand forecasting. Our clients pull in enormous amounts of data to make informed decisions on where to place inventory, how long, and in what quantities. AI can now synthesize data such as weather, social media, trends, and how these disparate sources can all influence demand, thus the supply chain.
–Steve Schlecht
Director, Strategic Initiatives
Buske Logistics
Integrating AI into the final mile logistics will have the most profound impact, allowing providers to offer a more personalized and reliable delivery experience. New features such as tailored delivery windows, preferred delivery services and seamless communication channels will further enhance overall customer satisfaction.
–Ori Anavim
Co-founder and COO
Grasshopper
Route optimization. By using real-time data for efficient paths, improving demand forecasting with predictive analytics, and supporting risk mitigation by identifying disruptions, the innovation to Route Optimization will be where technology and people work together to achieve Peak Performance Delivered.
–Mike Teresinski
VP of Managed Transportation
TA Services
Inventory management. The ability to automate mundane tasks, leading to less inefficiencies and more speed will put pressure on supply chains. With AI’s ability to predict demand, it can break the cycle of reactive purchasing and shipping, fundamentally shifting how businesses approach their supply chain strategies.
–Ben Hussey
Co-CEO
Katana Cloud Inventory
Logistics operations are vulnerable to risks like natural disasters or labor shortages. As such, AI’s predictive capability to process vast amounts of data, make intelligent decisions and predict outcomes makes it a critical tool in the logistics sector. With genAI, multiple scenarios based on trade-offs and formulation of business continuity plans can be run, enhancing overall resilience.
–Shipra Sharma
Head of AI & Analytics
Bristlecone
Today’s unpredictable business landscape demands real-time insights and proactive decision-making. Effective sales and operational planning processes require collaboration among internal systems such as forecasting and planning, as well as inventory management. Modern supply chain data analytics, built on real-time data pipelines and AI, eliminate data silos and drive informed decision-making.
–Mike Capone
CEO
Qlik
AI will massively impact every logistics function, from driverless trucks to warehouse robotics, automated planning, demand forecasting, and route optimization. One area to highlight would be risk management and quality of service. I predict substantial improvements here, with risk monitoring and mitigation occurring more frequently and timely than today.
–David Stanton
Founder
Reelables
By processing vast amounts of data, including market trends, weather conditions, and consumer behavior, AI can predict demand with unprecedented accuracy. This empowers companies to align supply with demand in a dynamic way, driving both efficiency and resilience. AI-powered technology helps optimize inventory management, refine route planning, and minimize risks.
–Vlad Kadurin
Chief Product and Operations Officer
Ship.Cars
Route optimization, also drayage most likely.
–Gino Fontana
Chief Operating Officer – Executive Vice President
Transervice Logistics Inc.
AI will automate some of the lower value tasks currently done, such as load / independent driver matching and route optimization. On a more advanced level, it will promote better inventory tracking through the creation of digital twins that will follow cargos and provide real-time data to shippers.
–Joe Adamski
Senior Director
ProcureAbility
AI will transform personnel and business operations by automating routine tasks, enabling employees to concentrate on higher-value work. This shift will not only streamline operations but also foster a more dynamic and skilled workforce. AI will enhance leadership development, personalize training, and optimize talent management, creating more capable and engaged teams.
–Joe Galvin
Chief Research Officer
Vistage
Demand forecasting. By analyzing historical data and identifying trends, AI helps manufacturers anticipate consumer needs more accurately. However, AI isn’t a standalone solution; it must be aligned with a solid organizational strategy in order to effectively leverage insights, fostering innovation and adaptability in today’s complex supply chain landscape.
–Ryan McMartin
Product Marketing Manager
Parsec Automation Corp.
AI will significantly impact route optimization, helping companies mitigate rising fuel costs and inflation-driven operational challenges. Advanced AI-driven solutions improve real-time route planning and fleet efficiency by analyzing traffic, weather, and demand patterns, reducing delivery times, and enhancing last-mile performance.
–Shivalika Pandey
Director – Business Development
Trigent Software
Automation and resilience. Generative AI’s ability to summarize data and generate insights will enable pervasive and faster data-driven decisions. Moreover, its ability to autonomously execute tasks and collaborate with other agents will drive automation and resilience in the supply chain, analogous to algorithmic trading on Wall Street today.
–Sheikh Talat
Data Science Manager
IntelliTrans
Supply chain optimization. AI will radically enhance supply chain optimization, analyzing vast datasets to streamline operations and reduce inefficiencies. This will lead to improved performance and cost-effectiveness, making supply chains leaner, smarter, and more responsive to real-time challenges and opportunities.
–Fred Baumann
Senior Industry Principal
Kinaxis
Demand forecasting. By analyzing vast amounts of data in real-time, AI can predict customer demand with extremely high accuracy, reducing stockouts and overstocking. This improves inventory management, optimizes supply chain efficiency, and enhances overall decision-making in logistics operations. This will be a game changer for 3PLs.
–Alan Silberstein
Co-founder
ShipLab
Inventory management and determining ideal order quantities. AI could predict seasonality, consumption rates, optimal DC locations, and inventory needs based on data access.
–Miguel Perez
Director of Cross Border Operations
TA Services
AI/ML capabilities will continue to impact logistics functions like demand forecasting, such as including unstructured data like news articles in forecasts to boost accuracy. AI is also improving embodied intelligence, like creating autonomous robots for warehouse tasks that reduce manual labor, and strengthening supply chain management by increasing visibility and flagging anomalies in forecasts.
–Srinath goud Vanga
Architect, Machine Learning
o9 Solutions
Demand forecasting. AI will analyze vast data sets to predict shifts in consumer demand. With AI’s ability to track real-time trends and patterns, logistics can better manage stock levels, avoid shortages or excess inventory, and optimize overall supply chain performance.
–Kelly Sims
Owner, President, Chief Operating Officer
iJility, LLC
Demand forecasting and route optimization are the logistics functions most significantly impacted by AI. Demand forecasting benefits from AI’s ability to analyze vast amounts of data, improving accuracy in predicting demand shifts. Route optimization is transformed by AI through real-time analysis of traffic. Both functions help cost savings and improve service.
–George Maksimenko
CEO
Adexin
Transportation management, crucial for moving vehicles and parts across long distances, will be most impacted by AI’s route optimization capabilities. AI can analyze traffic, weather, fuel efficiency, and potential disruptions to optimize routes in real time. This will lead to faster deliveries, reduced costs, and lower fuel consumption.
–Mike Trudeau
Executive Vice President of Business Development
Montway Auto Transport
Forecasting. Initially, AI will have the greatest impact on things like forecasting since that has the longest track record of data to draw from. Only slowly will AI be used for risk management, as companies will need to internally align across groups (procurement, supply chain, logistics, IT) on how best to manage risk before applying AI to forecast it.
–Tony Pelli
Practice Director, Security and Resilience
BSI Consulting
AI will transform demand forecasting by analyzing shipping trends, customer behavior, and market data to predict volumes with greater accuracy. This enables better resource allocation, reduces shipping costs, and ensures organizations can meet changing global demands, driving more efficient, scalable, and tailored international delivery solutions.
–Thanneer Malai
Vice President of IT
ePost Global
AI will have the most short-term impact on demand planning, forecasting and customer service applications. With time, AI will likely increase its dominance in the robotics optimization space with a major impact on speed, accuracy and advanced decisioning.
–Bart Cera
President and CEO
VARGO®