Don’t Outsource Your Thinking: Why Judgment Matters More in the Age of AI
Introduction
This is the second in a 2 part article about how supply chain hiring is evolving as AI rapidly accelerates its influence.
In this article we’ll address the fact that hiring is still taking place. In fact, a lot of supply chain talent professionals are having big years. Recruiters are being asked to fill a lot of roles despite economic pressures being applied across the board. What does this mean in the age of ongoing global disruptions and AI advancements?
What this tells us is that employers need to hire differently. They are being more selective, placing a greater emphasis on leadership experience, critical thinking, business judgement, cross functional collaboration, and change management. This shift is being brought about in large part because of AI.
Analyses, modeling, research and the more routine execution tasks can be done by AI now or in the near future. Because of this, the entry level access points are being adjusted. Recent college grads are still finding their way, but the work they’re being hired to do is shifting. Furthermore, every company now has the potential to deploy the same tools which accelerate machine learning, analytics, etc. So what does this mean for competition?
The answer may be the thinking behind the work.
We’re not arguing against AI. We’re advocating for using it for what it’s built to do. It’s not built to think for you or be a substitute for your lived experiences. AI expedites the work that doesn’t require your unique strategic mind. Allowing AI to expedite the more routine and mundane tasks frees you up to do what only humans can do: create. A lot of employers – and professionals – struggle to determine where the line between human and AI should reside. That’s to be expected. Growing pains are normal as we come to grips with such powerful and influential technology. Just don’t lose sight of your lived experiences or what you and all of us can do better than the bots.
Efficiency is only helpful if it doesn’t come at the expense of understanding.
Research from Microsoft involving 319 knowledge workers illustrates the tension. The researchers found that greater confidence in generative AI was associated with less critical thinking, while greater confidence in one’s own ability was associated with more. AI didn’t eliminate the need for critical thinking, but it changed where it happened. Verification, interpretation, integration, and oversight became increasingly important.
That distinction matters. There’s a big difference between using AI to help you think and using AI so you don’t have to.
The Economics of Expertise Are Changing
Who do Fortune 100 companies hire when they need consulting help? Large consulting companies like Accenture and Cognizant. If AI can do the high level synthesis and analysis commonly entrusted to highly paid consultants, then what are people paying for when they engage these firms?
Judgment.
Things that AI can’t do.
A recent Reuters article details the money being lost by these consultants. According to this piece, Accenture and Cognizant reported a combined $100 billion loss in market value since 2024. Consultants have shifted to an outcome based model, rather than simple stacking hours on a balance sheet.
We said in Part 1 that AI implementation needs to be a business decision and not a tech decision. What we mean is that the decision makers all need to be on board with what is being done and how it’s being deployed.
It goes without saying that the implications of AI stretch far beyond the consultants. Supply chain professionals stare down this question on a daily basis. Fancy graphs and models can be effectively produced by AI. The presenter needs to grasp the why and the so what of the models. Spit shine and polish is surface level. Can the professional demonstrate the thinking behind it?
Anyone with even a modest level of AI proficiency has confronted this. We crunch numbers and model myriad analyses in real time with incredible ease. It’s super exciting. The world is our oyster! Then we start to write the email accompanying said report, and it happens: We realize that we just allowed AI to do all the thinking and we don’t have insight to offer.
That pause is very important now. Supply chain career acceleration depends on the ability to communicate the messages from the data in the report. When we built them ourselves, it was a cake walk. Now, we have to ensure that we can convey the thinking behind these fancy new presentations. Otherwise, the output may look better than ever while the thinking behind it is actually getting worse.
We see this issue a lot with the companies that Georgia Tech’s Supply Chain and Logistics Institute engage with.There is growing concern that professionals tasked with complex supply chain analysis are choosing the “EASY” button.
If your high paid analyst moves too quickly into optimization and network design without properly challenging assumptions or having a firm understanding of the recommendations impacting the business, then what are you paying them for? Technology is a tool. The person using the tech has to advance the tool’s operative capacity into one of synthesis and analysis and be able to defend their position. A sophisticated presentation can’t mask a lack of knowledge.
We recently explored this problem in a Georgia Tech article, The Blind Spot in Modern Supply Chain Analytics: Where Did Critical Thinking Go? The point is simple: most of the important work still occurs outside the model. Defining the actual business question, challenging assumptions, interpreting the output in operational terms, and determining whether the answer makes sense remain human responsibilities.
A technically correct answer can still be a terrible business decision.
Your Secret Sauce Still Has to Come From You
We’re also seeing this in the academic world. An anecdote from one of the companies we engage with sheds light on how AI has reversed the way in which interns operate. AI was to assist with some of the lighter cosmetic and administrative work while the students would churn the heavier stuff. However, the reverse happened. Rather than the intellectual heft being carried through research and questioning their own analysis, AI did the work. When challenged to interpret their reports, the students failed to understand their own findings.
As a mid career supply chain professional who suddenly has these amazing tools at their disposal, what are you going to do?
We advise you to keep doing what you were doing. It’s akin to the smart phones. We all have them now. But we don’t have to have them with us ALL the time. Same with AI. You got hired and promoted based on your own merit. You developed experiential knowledge and understanding on your own. Learn how to augment what you do best using AI. But don’t use it as a crutch.
And remember that AI can’t talk to your boss who found the fly in the ointment on your latest report. AI can’t develop relationships with vendors or help you learn how to be a leader. You have to do the work and trust me when I tell you that your work is good enough.
The supply chain workforce needs people. Be the people we need and use AI as a tutor, not as a shortcut.
Leaders Need to Check the Thinking, Not Just the Work
The new challenge AI places on leaders:be accountable for your team’s thinking, not merely their production. Leaders also need to be proactive about developing AI guardrails. What tools should be used when, and how said usage should be disclosed. The goal is to ensure that you’re developing people, not prompts.
Polished reports and presentations no longer tell you much about the thinking that went into them. AI can produce impressive work in minutes. Managers have to dig deeper. Does the person understand the analysis? Can they explain the assumptions, defend the recommendation, and recognize when another approach might be better? The finished product matters, but so does the intellectual work behind it.
It’s one thing to make a good hire. Retention and long-term success depend heavily on how well you develop that person. Company culture plays a big role at this stage of the game. Notice how we’ve barely mentioned AI in the development process. That’s intentional. Technology can help. But people still need to train, mentor, challenge, and develop people.
Build a Fireproof Building
AI gives supply chain organizations a chance to rethink why today’s work exists the way it does.
Many supply chains were designed around constraints that technology is beginning to remove. Analysis took time. Information moved slowly. Scenario planning was difficult. Replenishment operated in batches. Using AI only to remove these constraints may leave much of AI’s value on the table.
The replenishment process is a great example of this. Predetermined delivery cycles were the way to go. But a more fluid and responsive network can evaluate demand in real time, along with inventory and transportation capacity. Now you have a totally new framework that can determine when a product should actually move. One approach asks how technology can make the existing process more efficient. The other asks, “does the process still need to operate in this way?”
We give firefighters all sorts of tools to help fight fires when maybe we should be asking for better ways in which to prevent fire. AI can highlight issues in a supply chain processes earlier and inform root cause analysis but the redesign still requires your knowledge, experience and creativity.
That distinction gets to the heart of what AI should ultimately enable in supply chain. Instead of giving the firefighters increasingly sophisticated equipment, maybe the better question is how to build a more fireproof building.
Curiosity, creativity, operational experience and business judgement develop these new ways of doing things. AI can provide the analytical horsepower to help get it done faster. But only if it’s guided by the people you put in place to operate it.
Conclusion
Supply chain has always rewarded people who can solve problems. AI just gives problem solvers an incredibly powerful set of new tools for earlier detection and more robust analysis. These tools are also reshaping how teams need to be managed and developed. Leaders need to evolve and change how they hire, challenge, and ultimately evaluate their people. Each of these cohorts should still prioritize experience and skills that allow you to recognize a pattern, challenge an assumption, ask a better question or envision an entirely new way of doing things.
Knowing what to do with the work that was much more efficiently produced will become key differentiators. Retaining and deploying soft skills in a new way while enhancing relationship building can set you apart and accelerate your career. Furthermore, having the judgment to know when something AI produced doesn’t make sense is more important than ever. Challenge the bots!!! Use AI to help accelerate and challenge your thinking.
Just don’t outsource your thinking.
About The Author
Chris Gaffney is an Edenfield Executive-in-Residence and a Professor of the Practice in the H. Milton Stewart School of Industrial and Systems Engineering. He also serves a dual role as Managing Director of the Supply Chain and Logistics Institute (SCL) and Academic Program Director for Georgia Tech Professional Education (GTPE) . He was most recently VP of Global Strategic Supply Chain at The Coca-Cola Company. During his 25-year tenure with Coca-Cola, Chris held multiple leadership roles including President of Coca-Cola Supply, SVP Product Supply System Strategy, VP of System Transformation, and VP of Logistics for North America. Chris also served as President of the National Product Supply Group; a governing body responsible for 95% of volume produced in North America. Following his retirement from Coca-Cola in 2020, he assumed the role of Principal at ECG and partner at EDGE Supply Chain, providing advice and consulting in the Supply Chain space. Gaffney has extensive experience in Consumer Products Supply Chain, Supply Chain Strategy & Transformation, Footprint Design & Network Optimization, Supply Chain Operating Model and Capability Building and Logistics and Supply Chain Planning.
