If traditional entry-level roles in supply chain are disappearing due to AI automation, what is one alternative pathway young professionals should pursue to enter the field?

Look at supply chain analytics or data management roles since automation is booming there. The folks on our team who could actually use Zoho or Tableau stood out immediately, even without much experience. I started in reporting and got up to speed by working alongside logistics. Learning these tools is a smart move that will help you find a solid place in the industry. If you have any questions, feel free to reach out to my personal email

Juniors used to do spreadsheets manually, however, now it's done by automation faster than people. The biggest change I see is companies trust these black boxes a lot and they don't check the source data. Young professionals must move to forensic system auditing to make themselves relevant. I saw how automated data masks tech debt while working in digital Merger & Acquisition (M&A). We recently looked at an asset in which the procurement logic had a recursive error, which cost the firm $400,000 in phantom stock. The AI created nonexistent inventory. That's why it's best for anyone entering this field in the wave of automation to check the integrity of this algorithm. You need to learn to identify where the logic has failed. In my work, we don't only look at the output, we look at the 'truth' in the raw data. That's because an automated supply chain is only as strong as the smallest step in its validation process. If you can do engineering-grade data audits you will see mistakes that are invisible to traditional managers. That is precisely how you will be indispensable in 2026.

Young workers should shift away from competing with automation and instead focus on managing the autonomous infrastructure directly. The duty of a traditional warehouse supervisor is no longer relevant; however, there is still a need for Robotics Operations Center (ROC) analysts to fill this position. Many of today's larger distribution facilities use numerous fleets of autonomous mobile robots (AMRs) and automated storage and retrieval systems (AS/RS) as part of their operation. Since these many automated systems work together as one large machine-like ecosystem, it is inevitable that they will run into things like physical bottlenecks, desynchronization of their software, or spatial routing issues that will cause them to freeze at some point before the end of their shift. Learning about how to manage a Human-Machine Interface (HMI) to control the movement of the automated robots and how to analyze fleet telemetry data (AMR) will position you well above the automated workers. The goal is to move from just physically moving the inventory to now being responsible for the complex algorithms that will control the movement of the mechanical workforce.

I tell young people to look at logistics or supplier roles since those jobs still need actual humans. When we worked on our jewelry shipping, the people who could use the software and handle vendor calls were the ones who made the difference. If you learn those specific tools and find an internship where you get your hands dirty, you will have skills that automation just cannot replace right now. If you have any questions, feel free to reach out to my personal email

Most of today's entry-level job positions, such as data clerk and inventory scheduler, have been replaced by AIs that do the bulk of the heavy lifting with regard to prediction and reporting functions. Therefore instead of trying to work with the algorithm, the best way for new professionals to engage with the algorithm would be to serve as its "exception handler." Management of the algorithm is what most new professionals will benefit from doing. This is what we are seeing in both our BPOs and supply chain management functions; basically all of the value is being transitioned from routine execution management processes to digital operational orchestration processes. For the most part, the best place for new professionals to focus on their careers will be in developing an understanding of system logic and edge case management. This includes being able to identify when the AI system is creating hallucinations and/or missing context in a supply chain workflow. The human in the loop will not disappear; rather, they will simply be moving up the food chain when working with this technology. If you can connect the dots with respect to providing context between the technical/system alerts and the on-the-ground business reality, you will become an extremely valuable resource in the overall business model. So stop being a data entry clerk or data skeleton, and start focusing on being a workflow architect. In summary, managing complexity, particularly in supply chains, is the major focus of any supply chain business, and the usage of AIs only adds a new level of complexity to that same task. So you should not worry about being replaced/replaced by machines; rather, you should concentrate your efforts on being able to fix AIs when they fail, which will be a normal occurrence; therefore, you will become an essential resource to your business as a whole.

An alternative option that is realistic is working in customer operations or dispatch coordination. As AI replaces more of the routine and basic entry-level responsibilities, there will continue to be a need for individuals who are able to resolve exceptions, communicate effectively, and keep things progressing when there are delays or changes in plans. Working through these types of experiences provides an opportunity for young professionals to learn about how supply chains operate in real-time. Positions that emphasize the coordination of updates, vendors, and schedules; as well as resolving issues or challenges usually provide better opportunities to enter this field because they create smoother transitions and faster turn-around times, which still represent significant operational challenges.

Most of the advice I hear directs young people to certifications, graduate programs or internships at large corporations. I'd push back on all that as a starting point. The path I'd recommend is burying yourself inside a small e-commerce brand even unpaid or part-time and owning a real slice of the operation. Not shadowing. Not filing reports. But managing purchase order from the moment it gets raised to the moment stock lands in a warehouse. Here at Desky, for example, it is not unusual for one team member to touch freight quoting, supplier communication, lead time tracking and inventory reconciliation sometimes in the same day. That breadth doesn't exist at large companies where each task is the responsibility of a different role. The reason why this is important is that AI doesn't automate judgement, it automates tasks. And judgment only comes from doing the messy, end-to-end work yourself first.

A great way for up-and-coming professionals to consider creating a sustainable and meaningful career is to focus on reverse logistics and the circular economy. AI performs well in the linear, forward approach by predicting product demand as well as fulfilling product orders automatically on standard delivery routes. Conversely, the autoreverse (reverse logistics) generates large amounts of chaos that cannot be quantified. The process of receiving products back from customers, refurbishing defective inventory, or reclaiming reusable raw material out of products at the end of their useful lifecycle each consists of infinite physical variables that today's robotic automation and predictive analytics cannot effectively identify. By developing expertise in secondary market routing, warranty triage, and sustainable materials reclamation, an individual will remain relevant for many years. Also, this area of expertise requires humans to employ a high-level triage process to determine if a returned asset is liquidated, cannibalized for parts, or recycled, thus creating a very quick-to-market and profitable niche impervious to future technological displacement.

With over 30 years in commercial real estate, including tenant rep at Grubb & Ellis and flex/tech leasing at Highwoods Properties in Research Triangle Park, I've guided supply chain firms through site selection amid tech shifts--positioning me to spot entry paths AI can't touch. One alternative pathway: Start in industrial/flex real estate brokerage, targeting distribution and logistics tenants needing warehouse-office hybrids. At Highwoods, I handled leases for class A flex spaces where young pros learned supply chain ops like inventory flow and site efficiency first-hand, landing internal roles after 2-3 deals. My firm, Donahue Real Estate Advisors, exclusively reps tenants with zero conflicts--young advisors here have transitioned to supply chain ops at client firms after mastering market-driven decisions AI overlooks.

I run Doma Shipping & Travel (30+ years moving parcels, containers, cars and full relocations USA-Poland/EU), so I've watched "entry-level" work like data entry, basic quoting, and simple tracking get swallowed by automation while the messy, document-heavy edge cases keep growing. One alternative pathway: become a **customs + compliance operator** (not a "supply chain analyst"). Get very good at HS codes, declared value logic, CBP/EU paperwork, and exception handling for personal effects/relocation shipments and vehicles--because AI can suggest fields, but when a shipment is held, a human who can fix docs fast is the difference between a 2-day delay and a 2-week nightmare. Concrete example from my world: on USA-Poland moves (mienie przesiedlencze) and car/motorcycle shipments, the winning skill isn't "route optimization," it's assembling the right document set and sequencing steps so port agent fees, VAT/duty and release timing don't spiral; we publish costs up front (e.g., motorcycle ocean shipping often starts around $350 + port fees), but compliance errors can cost more than the freight. How to break in: start in a brokerage, freight forwarder, or relocation/vehicle-import shop and volunteer for the "held shipment" queue; build a personal playbook of the top 20 failure modes (missing POA, mismatched consignee, wrong valuation, incomplete packing list) and measure yourself on time-to-release, not spreadsheets.

As the owner of The Break Downtown, I've built my career on high-stakes operational logistics where hospitality meets real-time demand. Managing a sports grill directly across from the Delta Center requires a level of supply chain agility that AI can't replicate during a sudden surge of fans. Young professionals should pursue **perishable inventory and vendor relations roles within the high-volume hospitality sector**. AI cannot yet handle the physical coordination of 16 different wing flavors or the sudden procurement shifts needed for large-scale private event catering. For example, our Mac N' Cheese Sampler involves managing the "just-in-time" logistics of four distinct cheeses and volatile proteins like North Atlantic lobster. Mastering the procurement of these specific, high-cost ingredients provides a hands-on logistics education that translates to any industry. Focus on the "last mile" where local events drive demand. Understanding how a gameday schedule affects your $17.95 Burnt Ends Tacos inventory creates a specialized expertise that algorithms can't touch.

As the Inventory Control Manager at King of Floors, I manage global sourcing and container logistics, moving product directly from international factories to our BC warehouse. Young professionals should pivot toward **Specialized Sourcing and Quality Advocacy**, a pathway that focuses on the technical and environmental nuances of physical goods that AI cannot qualitatively verify. For instance, sourcing our **Swiss Krono Grand Selection** laminate requires auditing FloorScore certifications and sustainable wood fiber cores to ensure the product is safe for families. By mastering these specific quality standards and factory relationships, you become a high-value gatekeeper for inventory excellence rather than just a data processor.

It does feel like the traditional entry point into the industry is starting to shift in a pretty meaningful way. A lot of the classic first jobs, the ones that used to involve updating spreadsheets, tracking shipments, managing routine purchase orders, or doing basic forecasting support, are increasingly being handled by automation and AI tools. Now, those roles were never glamorous, but they were how people learned the mechanics of the industry. One thing I'd like to mention is: when those positions shrink, the ripple effects travel further than people expect. Fewer entry level analyst roles today means fewer mid level planners tomorrow, and eventually a smaller pipeline of experienced supply chain leaders ten or fifteen years down the road. It also changes how people develop judgment. Historically, you built intuition about inventory cycles, vendor behavior, or logistics bottlenecks by working close to the data early in your career. If that learning layer disappears, companies will eventually feel that gap. The automation also tends to move up the chain gradually. Once routine data entry and reporting are automated, the next layer that gets affected is planning support roles and junior analysts who primarily compile information rather than interpret it. Over time even some forecasting and procurement functions will be partially automated, which means the remaining human roles will skew more strategic and analytical much earlier in a career. Because of that, one pathway I often suggest to younger professionals is to start closer to operations rather than pure administrative supply chain work. Roles in logistics coordination, warehouse operations, vendor management, or field operations expose you to the real physical movement of goods and the human decision making behind it. Those environments are much harder to automate, and they build practical judgment that technology can't easily replicate. Ironically, that operational exposure may end up becoming the new entry point into the industry. Someone who understands how freight actually moves, how suppliers behave under pressure, and how distribution networks break down will still be incredibly valuable even as automation handles more of the routine data work. In the long run, the professionals who combine operational experience with an understanding of the new technology will likely be the ones shaping the future of supply chain leadership.

The study of process improvement methodologies is one of the most important ways that young professionals can establish themselves in the rapidly evolving world of supply chain management and prepare for an environment dominated by automation. Young professionals who develop knowledge and skills using methodologies such as Lean, Six Sigma, and Agile will be able to optimize supply chain operations. They would benefit from studying Lean fundamentals that focus on reducing waste and increasing efficiency. As they become proficient with tools like Value Stream Mapping, young professionals will be empowered to identify inefficiencies in current processes. They will also receive a structured approach to identifying sources of variation and making data-driven decisions as they learn Six Sigma. Becoming certified in these methodologies will further enhance a professional's resume and provide a competitive advantage. Certification as a Certified Six Sigma Green Belt provides evidence that a professional has developed an interest in process excellence and has mastered analytical tools that are becoming essential for companies implementing data-driven approaches. Studying Agile will also prepare professionals to operate in fast-paced environments where responding to changing market conditions is crucial. Those who understand how to collaborate across functions and develop plans iteratively will be better prepared to support companies that need to adapt quickly in their supply chains.

I run one of the largest online marine livestock operations in the U.S., which means I've watched AI quietly absorb the roles that used to handle routing, inventory forecasting, and fulfillment scheduling. I've lived through that transition at SaltwaterFish.com. The path I'd actually bet on: specialize in supply chains where the product itself is too unpredictable for algorithms to fully manage. Live animals, perishables, temperature-sensitive goods--these categories punish pure automation. When we improved our livestock quality scores by 20%+, it wasn't software that did it. It was humans making judgment calls at every handoff point. Find a niche vertical with biological or environmental variability and become the person who understands *why* the system breaks, not just that it broke. Aquatics, fresh produce, pharmaceuticals, exotic plants--AI can flag the anomaly, but it can't yet understand that a typhoon in the Philippines means your coral supplier just lost collection access for six weeks. That domain expertise is your moat. Get into a weird, complex, living supply chain early, even if the role is small. That context compounds fast and it's genuinely hard to replicate.

Running operations across two storage facilities with 1,358 units means I live inside vendor coordination, logistics scheduling, and inventory management daily--supply chain at a local, human scale. That ground-level view taught me something the big-picture frameworks miss. The pathway I'd push young professionals toward: become the person who manages **supplier and vendor relationships** directly, not data. I onboard moving partners, packing supply vendors, and service providers constantly. The humans who negotiate terms, catch relationship friction early, and translate operational needs to outside partners? AI isn't replacing that. Concretely, I'd recommend approaching a small regional 3PL, storage operator, or local distributor and offering to own their vendor communication process for free for 90 days. Build a simple accountability tracker, run the check-in calls, document the gaps. That's a real portfolio. What gets hired isn't "I know supply chain theory"--it's "I reduced vendor response lag and caught a service gap before it cost us." That story closes interviews.

I've spent 25 years building musicians from scratch who had zero traditional credentials -- and what I learned translates directly to your question. The pathway I'd chase right now is **performance-based credentialing over degree-based entry**. In my Real Rock Band program, students who couldn't read a note landed gigs because they could *demonstrate* results in a room. Supply chain hiring managers are facing the same shift -- they need people who can show problem-solving in action, not just list coursework. Specifically, look at **operations roles inside mid-size manufacturers or 3PLs** where you're touching real inventory decisions daily. At Be Natural Music, my most growth-ready students weren't the ones who studied theory longest -- they were the ones who managed band logistics: booking, equipment, timelines, accountability. That's supply chain thinking with a different label. Get in a room where the problems are live and messy. That's where AI still hands the wheel back to humans.

One strong pathway for young professionals entering the supply chain field is building expertise in supply chain data analysis and automation oversight. As AI increasingly handles routine operational tasks, organizations are prioritizing professionals capable of interpreting operational data and improving automated workflows. Research from McKinsey & Company suggests that advanced analytics and digital tools could unlock significant value in supply chain operations, highlighting the growing importance of data-driven decision-making. Within modern supply chain environments, professionals who understand both operational processes and analytical tools often contribute earlier in strategic initiatives. Exposure to supply chain analytics platforms, process mapping, and automation monitoring roles can provide a practical entry point. This blend of operational awareness and digital capability helps early-career professionals remain relevant as AI reshapes traditional entry-level positions.

One strong pathway for young professionals entering the supply chain field is focusing on digital project coordination and process improvement roles that support technology-driven operations. As AI increasingly automates repetitive entry-level tasks, organizations are placing greater value on professionals who understand how technology, data, and cross-functional workflows connect within supply chain ecosystems. Research from the World Economic Forum highlights that analytical thinking, systems thinking, and technology literacy are among the fastest-growing skills in modern workplaces as automation reshapes operational roles. In learning and development environments supporting enterprise teams, individuals who combine supply chain fundamentals with project management and digital collaboration skills often gain early exposure to transformation initiatives. Participation in process improvement projects, digital operations programs, or certifications focused on project coordination can create a strong entry point. This blend of operational understanding and digital capability allows emerging professionals to contribute to supply chain innovation rather than routine administrative work.

One promising pathway for young professionals entering the supply chain field is developing cross-functional digital skills, particularly in data analytics and process optimization. As automation reduces repetitive operational roles, demand is shifting toward professionals who can interpret supply chain data and improve decision-making. Research from World Economic Forum highlights that analytical thinking and technology literacy are among the fastest-growing skill requirements across industries as organizations integrate automation and AI into operations. Within enterprise environments, early-career professionals who combine supply chain fundamentals with data analysis capabilities often contribute faster to strategic initiatives. Participation in project-based learning, internships focused on operational analytics, or training in tools used for supply chain planning and performance monitoring can provide a practical entry point. This blend of operational understanding and digital capability creates a strong foundation for navigating the evolving landscape of AI-driven supply chains.