AI in supply chain Archives - Logistics Viewpoints

AI-Ready Supply Chains and Workflow Management: Key Insights from the 2025 FourKites Summit

Logistics Trends | By Gaven Simon • 09/17/2025

From Fragmentation to Orchestration: Building An Intelligent Supply Chain That Elevates Business Performance

On August 28th in Chicago, Illinois, FourKites invited its customers, industry peers, and partners to join a full day of educational sessions, customer stories, and executive breakout sessions.

The morning began with a keynote address from Mathew Elenjikal, the CEO and founder of FourKites Inc. He outlined FourKites’ cloud-native, multimodal global network of data, emphasizing the company’s evolution from real-time supply chain visibility to AI-enabled orchestration and automation.

“Now that you can digitally see your operations, how can you optimize your processes and make your data work for you?”

The path to peak performance involves three steps:

Connecting fragmented systems
Automating routine tasks with AI
Orchestrating dynamic optimization

Mathew also shared some key metrics reflecting enterprises with disconnected systems. 33% churn of customers due to poor delivery experiences, 10-30% annual revenue loss from stockouts, and teams spending 70% of their time firefighting.

FourKites’ AI-driven digital twins for orders, shipments, inventory assets, and facilities provide real-time insights, reducing costs and improving efficiency. The company’s entire network tracks over $500 billion in freight annually, which FourKites is leveraging to enhance integration and automation through its network.

Keynote Presentation: The Age of Intelligent Agents: How AI is Revolutionizing Supply Chain Operations

This keynote session was led by Priya Rajagopalan, President of Product, Technology & Operations. The session dived into the strategic vision of integrating AI with supply chain operations to enhance efficiency and reliability. This session was focused mainly on FourKites’ deployment of AI Agents and their customers’ experiences.

She highlighted that most AI agents are built on generic models and lack contextual sophistication, emphasizing the importance of establishing data foundations and networks to make intelligence possible. Priya also spoke about the transformations needed to shift from reactive to reliable, from critics to champions, and from smart moves to expertise.

The most interesting part of this session was the live demonstration of Alan, a voice-enabled appointment scheduling and optimization agent. Priya called him live during the session and played the role of the warehouse manager who was scheduling appointments for product deliveries. Alan provided information, including the P.O. number, the delivery date, and the contents of the delivery. He spoke clearly, with a human-like tone and cadence. The two of them scheduled the appointment using historical data to help them decide the optimal time to arrive. Priya even threw in an ice-cream joke to make the phone call feel even more realistic. The entire phone call lasted approximately two to three minutes.

Breakout Sessions:

From Visibility to Orchestration: Building AI-Ready Supply Chains

Tyson Foods shared insights into its evolving supply chain strategy during its breakout session. Jeff Lyle, head of logistics and procurement, discussed the company’s shift from a poultry-focused business to a global protein leader, now shipping products to over 140 countries. This session covered the foundational visibility work required before AI implementation, the journey from “seeing problems” to “preventing problems,” and practical strategies for building systems that accelerate decision-making and enable autonomous interventions to fix issues before they become failures. Tyson has invested heavily in technology, implementing advanced visibility tools for truckload and yard management, and is now expanding into ocean freight tracking. The company faces challenges integrating data from multiple systems, but remains committed to process discipline and data governance. Looking ahead, Tyson aims to leverage AI and agent-based orchestration to further automate and optimize its supply chain, freeing team members for higher-value work and ensuring smooth customer experiences worldwide.

Geopolitical Risk Management and Supply Network Reconfiguration

The panelists for this discussion included LeAnne Coulter, former VP of Freight Management at Penske Logistics, and Gustavo Lopez Ghory, former Chief Supply Chain Officer at Kimberly-Clark. This session explored how escalating global uncertainties—from natural disasters and infrastructure disruptions to policy shifts and regional conflicts—are fundamentally reshaping supply networks. Rather than attempting to predict or plan for every possible disruption, leading organizations are building agile supply chains capable of rapid adaptation. The conversation emphasized the importance of designing supply chains with a clear purpose, building strong relationships with partners, and moving beyond transactional interactions. Gustavo highlighted that supply chains are designed for stability and often fail during periods of instability. He suggested that we need to start rethinking how we design supply chains and incorporate the possibility of failure into the process. Both panelists stressed that resilience comes from strategic planning, careful partner selection, and a mindset focused on delivering value and fostering prosperity, rather than simply optimizing for normal operations.

Closing Thoughts:

FourKites is helping address its customers’ major challenges and take advantage of their strategic opportunities. Whether it’s increasing supplier collaboration, protecting margins, unlocking working capital, or boosting team productivity through new AI capabilities, FourKites can support its customers in the physical and digital realm.

They are creating pragmatic and useful AI-powered solutions, reducing effort on repetitive tasks such as appointment scheduling. FourKites customers receive support throughout their digitalization journey, providing solutions regardless of their progress. AI Agents are taking center stage in the coming year, and FourKites will begin to allow more and more of its customers to gain access to these specialized tools. Lastly, FourKites is helping its customers to achieve orchestrated decision-making made possible by total visibility into their internal systems.

Transformation Is Not Trivial: The Work Ahead for the Supply Chain Industry in 2025

Guest Commentary | By Mathew Elenjickal • 11/21/2024

At this time last year, economists and business leaders were cautiously optimistic about 2024, hoping the economy could stage a ‘soft landing’ — cooling off from a period of surging inflation and rising interest rates without tipping into a recession. While many remain cautiously optimistic, there’s a growing sense of relief that the economy sidestepped the worst-case scenario. As noted in a recent CNBC piece, “a gravity-defying jobs market …. a slowing pace of price increases and declining interest rates puts the macro picture in a pretty good place right now.”

Yet 2024 hasn’t been without its challenges for the global supply chain, which is still undergoing a long-term transformation amidst growing geopolitical, physical, and cyber disruptions. This year, the focus has been on belt-tightening, profitability, and cash management. Looking ahead to 2025, the industry will need to strike a balance between the often-competing priorities of efficiency, security, and innovation.

The bill comes due on cybersecurity. In early April of this year, a coordinated cyberattack targeted several maritime ports and vessels, causing widespread disruption.

The attackers reportedly used advanced ransomware and malicious software to disrupt port operations and tamper with the Automatic Identification Systems (AIS) on several ships, causing significant delays, misrouted cargo, and heightened risks of collisions and groundings. The total economic damage is estimated to reach as much as $500 million, as major shipping companies such as Maersk and CMA CGM were forced to reroute vessels and temporarily halt certain operations.

Incidents are growing in frequency and severity, substantially increasing risks of identity theft, espionage and severe safety incidents. The unfortunate truth in all of this is that the supply chain industry has historically underinvested in cyber security. The bill is now coming due.

Going forward, the industry will have to treat cyber security as a top priority, evaluating existing systems and processes and putting security at the forefront for any new deployments. And it must do so without unduly slowing down digital transformation efforts.

Tariff Turmoil. As I write this, the US election is a few days away. The candidates’ widely differing views on tariffs are sparking intense debate and speculation in regard to the potential impact on the supply chain industry, with one trade journal declaring: “New Proposed Trump Tariffs Could ‘Fundamentally Alter’ U.S. Supply Chains.”

My view is that regardless of which way the political winds blow, supply chain professionals should focus on what they can control, continuing the work that started in earnest post-pandemic of diversifying their supplier networks and implementing more nearshoring capabilities.

More disruptions (not least of all from new market entrants). Supply chain disruptions will remain a fact of life. What we will see more of in 2025 is disruption brought on by a surge of new startups.

Dave Clark, former CEO of Amazon’s worldwide consumer division, grabbed headlines earlier this year when he launched his new company, Auger, with lofty-but-bold promises of “a future where global supply chains operate with the simplicity of today’s most intuitive consumer technologies.”

Traditional supply chain companies would be wise to not underestimate the potential threat of a coming surge in new market entrants. VC funding is flowing back into startups, and investments in supply chain companies and tech represent an estimated 15%-20% of that funding.

The potential for these new entrants to upend the market order is unlike any we’ve experienced before. Why? AI. Because of AI, the pace of technology development is multiplying exponentially. These new companies, unburdened by legacy technologies, have a very real opportunity to leapfrog incumbents.

AI, automation AND upskilling. After a three-day walkout earlier this year, the International Longshoremen’s Association (ILA) and U.S. Maritime Alliance reached a tentative agreement on wages and extended their existing labor contract until Jan. 15. But the potential use of automation remains a major sticking point for the unions.

My personal view is that neither unions — nor anyone else — can stop the inexorable march of automation (despite a long, storied history of attempts to do so). In my experience, automation can and has displaced some jobs, but it has also changed existing jobs for the better and created entirely new ones.

My company recently worked with a client who embarked on a technology deployment with an expectation of eventually reducing headcount. In the end, when they saw how they could use an influx of high-quality, actionable supply chain data to improve operations AND their customer experiences, they added new positions.

AI and automation aren’t the enemy. But for supply chain companies to fully benefit from these technologies, they need to invest more in upskilling their employees. For example, with GenAI it’s crucial to train workers in prompt engineering so they can access the right information quickly and streamline outdated processes, all while creating new value for customers. Likewise, automation offers a chance to shift dangerous tasks away from human workers, freeing them up to take on higher-value responsibilities

AI and automation will increase. New entrants will upend existing markets. The companies that survive and thrive in this future will be cleared-eyed about the pace of change and will balance innovation, security and the interplay between technology and our human workers.

Matt Elenjickal is the Founder and Chief Executive Officer of FourKites. He founded FourKites in 2014 after recognizing pain points in the logistics industry and designing elegant and effective systems to address them. Prior to founding FourKites, Matt spent 7 years in the enterprise software space working for market leaders such as Oracle Corp and i2 Technologies/JDA Software Group. Matt has led high-impact teams that implemented logistics strategies and systems at P&G, Nestle, Kraft, Anheuser-Busch Inbev, Tyco, Argos and Nokia across North America, Western Europe and Latin America. Matt is passionate about logistics and supply chain management and has a keen sense for how technology can disrupt traditional silo-based planning and execution. Matt holds a BS in Mechanical Engineering from College of Engineering, Guindy, an MS in Industrial Engineering and Management Science from Northwestern University, and an MBA from Northwestern’s Kellogg School of Management. He lives in Chicago.

Getting Started with AI in Supply Chain

Artificial Intelligence | By Polly Mitchell-Guthrie • 01/25/2024

Getting started with AI in supply chain might not start where you think. Some try delving into deep learning or a crash course in generative AI (GenAI), but I don’t recommend starting there. Instead start with the foundation of your AI strategy, which should be an understanding of your company’s supply chain and your data. Second, avoid islands of isolation and limited impact by integrated AI into your supply chain so the results are aligned end to end. And third, lead the change needed, which in most cases is for your team to use technology more effectively, not build it themselves.

One supply chain executive told me AI makes him feel a bit like a deer in the headlights, which is why it’s worth stating that you don’t have to embark on this journey alone. Find a solution provider you trust, who will help shine the light to start where you are and evolve. Work that takes a whole team of people deliver, for the production and deployment of AI at scale, can instead be accomplished by a planner right in your company’s supply chain workflow as part of an end-to-end supply chain solution, putting the power of AI at their fingertips. Since this advice on getting started with AI in supply chain may seem counterintuitive, let me explain.

Why AI in supply chain?

First, why get started with AI in supply chain? The unquenchable appetite for adoption is driven by many factors. IBM’s Institute for Business Value found that 75% of CEOs believe generative AI will be key to competitive advantage. MHI and others continue to report that talent is the number supply chain challenge. Workers from picking and packing to planning and procurement are in short supply, stimulating interest in increasing productivity of the existing workforce. Planners are buried in tedious tasks using legacy, fragmented technology, which 48% say doesn’t help them do their job effectively, according to a survey by the boom! Global Network.

What AI has been able to do for years is find patterns and make predictions at a scale far beyond our human cognitive capacity, such as forecasting for a retailer with billions of sales records and millions of items. AI can accomplish tasks humans couldn’t do before, and do them better and faster, saving time and money. It can predict lead times for thousands of parts and automatically update changes, flagging only those for attention that fall outside of parameters a planner sets. It can increase forecast accuracy and provide greater granularity by incorporating additional signals beyond sales history using demand sensing.

What about generative AI?

Generative AI (GenAI) has introduced remarkable possibilities for increasing productivity by enabling humans to asking their system for help in their own words. Consider a planner in Brazil working with the previous lead time prediction example, who has forgotten how to update the parameters. Instead of searching for and reading multiple help documents, the planner can simply ask for help in natural language and receive an answer that is a single, synthesized explanation of those sources in Portuguese (even if the documentation is in English).

No matter how fetching GenAI’s communication abilities seem, it is important to remember that it doesn’t actually understand. Behind the curtain of wonders like ChatGPT is a probabilistic sentence completion machine, not a sentient being. Sometimes hilarious examples of its “hallucinations” illustrate its failure to understand (My Dinners with GPT-4 by Justin Smith-Ruiu is one of my favorites). Because it doesn’t understand, we need humans at the helm.

Understanding your supply chain is the bedrock, and people bring that understanding

For all its prowess, AI lacks the three c’s: context, collaboration and conscience, all uniquely human capabilities. It fails to understand because it cannot derive meaning from context, work together to solve problems, or hold us to a higher standard. Those traits are essential for business, along with understanding of your supply chain and its data. This knowledge is the bedrock upon which AI must be built, because as my favorite expert on the subject says, the three pillars of AI are data, data, and data.

A powerful advanced planning system can save planners time and provide insights, accelerating their intuition to make better decisions, as P&G has found. When a hurricane was bearing down, the instant transparency gained from their concurrent planning system allowed them to reposition inventory, solving all the expected disruptions, save for one gap in supplying bottles to a partner. Someone remembered they still had inventory of the old bottles, a eureka moment built on human expertise and institutional memory, features that a system doesn’t possess, even when enhanced with AI. It doesn’t understand.

Increase productivity by automating the obvious, those tedious tasks that require minimal thinking but much time, and save human understanding for where it counts. As one executive told me, his vision is 80% “touchless planning” – the solution does the planning, but it is guided by people, who use its outputs and insights, freeing up their human understanding for the 20% that can’t be automated, due to complexity, uncertainty, and sensitivity.

Connecting AI islands of isolation

Humans act on system-generated output to make decisions. But if those insights are isolated in functional areas not visible across the network, they will have limited impact. Even if AI provided a 100% accurate demand forecast, if you’re waiting on your production scheduler to return from vacation and correct errors in a spreadsheet or lack capacity to produce that demand, all you’ve done is create a highly-efficient silo. Concurrency combined with AI is the breakthrough, because it connects islands of isolation and aligns the nodes of your supply chain. That AI-enhanced demand forecast is truly powerful when it immediately informs supply, reducing the latency to keep them in concert.

Collaborative decisions are possible when everyone is on the same page at the same time, any time. If AI provides insights that require the supply chain professional to swivel between systems, open a tool to grab insights, download data into a spreadsheet, and then import it into the planning system, productivity goes down the drain, the risk of errors rises, and the likelihood of adoption shrinks. Only when AI is aligned and embedded across the supply chain, integrated right into the planner’s workflow, will the value of its insights truly be achieved. AI combined with concurrency is the true breakthrough in supply chain management.

Lead the change for people to use AI, not build it themselves

As Tom Davenport and Randy Bean report in MIT Sloan Management Review, their research finds that the groundswell to accelerate AI is shifting how it is done. One trend is AI moving from “artisanal to industrial,” as companies adopt platforms with the capabilities they need already built in. The second is the increase of techniques like automated machine learning and growth in “citizen data science,” which enables those with foundational understanding of their business and company data to leverage AI without a data science background.

For example, AI can improve demand forecasts by adding “signals” beyond sales history, but it takes understanding of your business and data to best guide the selection of signals. Asthma rates by region could be relevant for a life sciences company, whereas for a retailer festivals and events near stores might be more predictive. Human expertise grounded in an understanding your supply chain and data guides signal selection for demand sensing but does not depend on technical proficiency. These signals can be ingested and applied automatically and seamlessly, relying only on knowledge the planner already has, the ability to name columns on a spreadsheet.

AI brings a powerful set of techniques to bear on our supply chain problems, so exploiting that power will entail change for supply chain professionals. Upskill them with better awareness of how to leverage AI but based on a solid foundation of supply chain understanding, not an expectation of technical proficiency. Supply chains are never static, nor are the business models to run them, which means systems must be engineered for adaptability. The data feeding AI is dynamic, so data handling must be adaptive, to monitor changes automatically and orchestrate and adjust as needed. And the system itself must be adaptive, so your supply chain isn’t locked into a customized moment in time but can grow and evolve with the business.

AI can add horsepower to your engine, so don’t be afraid to get started with AI in supply chain. Start where you are, with expert knowledge of your business and data, connect your islands of isolation, and lead the change for your team to leverage AI.

Polly Mitchell-Guthrie is the VP of Industry Outreach and Thought Leadership at Kinaxis, the leader in empowering people to make confident supply chain decisions. Previously she served in roles as director of Analytical Consulting Services at the University of North Carolina Health Care System, senior manager of the Advanced Analytics Customer Liaison Group in SAS’ Research and Development Division, and Director of the SAS Global Academic Program.

Mitchell-Guthrie has an MBA from the Kenan-Flagler Business School of the University of North Carolina at Chapel Hill, where she also received her BA in political science as a Morehead Scholar. She has been active in many roles within INFORMS (the Institute for Operations Research and Management Sciences), including serving as the chair and vice chair of the Analytics Certification Board and secretary of the Analytics Society.

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