What I Wish Every Non-Tech Supply Chain Leader Knew About AI Implementation

What I learned about the gap between AI pressure and operational reality (with Guest Writer Joel Salinas)

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Last week I had a call with a client—just our ordinary weekly ops review call. Normally inventory is a sensitive topic but for this client, I now look forward to the last bullet on the agenda, entitled ‘Inventory’. Why? Because, (knock-on-wood) we gotten our inventory levels under control and kept them that way for a few months now.

Just when we think we’ve got our system where we need it, my client mentioned how his CEO had sent him a Slack message full of "AI-powered supply chain" headlines and asked: "When are we implementing something like this?"

That moment—feeling like you're suddenly expected to become a data scientist when you've mastered logistics—captures exactly what most supply chain leaders are facing right now.

This week,

Joel Salinas

from Leadership in Change tackles the question every non-tech supply chain leader is wrestling with: how do you drive AI adoption when your expertise is in operations, not algorithms? Joel's been helping leaders navigate this exact transition, and his framework might be exactly what you need to hear.

Here's Joel...

The strategic framework that lets you drive AI adoption while staying focused on what you do best

Picture this: You're standing in the middle of your distribution center at 6 AM, watching forklifts move with practiced precision. Every operator knows their route, every scanner beep has meaning, every process flows because someone, probably you, spent years perfecting it.

Then your CEO walks up with a tablet showing competitor headlines about "AI-powered supply chains" and asks: "When are we implementing this?"

That moment feels like being handed the keys to a Formula 1 race car when you've spent your career mastering logistics, not software and coding. You know what good operations look like, you understand customer needs, you can spot inefficiency from across a warehouse, but suddenly everyone expects you to become a data scientist too.

Here's what I wish every non-tech supply chain leader knew about AI implementation:

Your operational expertise isn't a limitation. It's exactly what successful AI projects need most.

Think of AI Like Fire or Electricity

I often tell leaders that AI is like fire or electricity. It can power entire cities and transform how we live and work. But without proper guardrails? It can burn everything down.

Fire gave us cooking, warmth, and industrial revolution. Electricity brought us light, communication, and modern life. Both required people who understood safety, application, and smart implementation, not just the science behind combustion or electrical current.

AI is heading toward the same place. It's going to be embedded in most industries, including supply chain. The question isn't whether you'll encounter it. The question is whether you'll lead its implementation or let it happen to you.

But here's the thing about transformative technologies: The winners aren't always the ones who understand the technical details. They're the ones who understand how to apply it safely and strategically to real problems.

You don't need to become a machine learning engineer any more than early factory owners needed to become electrical engineers. You need to become an intelligent user who knows where AI fits, where it doesn't, and how to keep it from burning down what you've built.

Start With Your Role, Not The Technology

Most supply chain leaders approach AI backwards. They start by asking, "What can this technology do?" when they should ask, "What problems am I trying to solve?"

Your expertise in demand planning, inventory optimization, supplier relationships, and operational efficiency, that's your competitive advantage. AI should amplify that expertise, not replace it.

Here's how I frame it: AI excels at pattern recognition, data processing, and repetitive analysis. You excel at strategic thinking, relationship building, and understanding the human elements that make supply chains actually work.

Perfect partnership? AI handles the data-heavy lifting while you focus on the decisions that require judgment, experience, and understanding of business context.

Real example: Instead of spending three hours every Monday morning analyzing weekend inventory reports, you could train AI to flag anomalies and present only the issues that need your attention. That gives you back time to work on supplier relationships or strategic planning, things only you can do.

The key is understanding AI specific to your role, not AI in general.

Use AI to Eliminate The Repetitive, Not The Strategic

I've watched too many leaders get overwhelmed trying to understand every AI capability. Stop doing that.

Start with this question: "What tasks eat up my time but don't require my expertise?"

For most supply chain leaders, that list includes:

• Generating routine reports and summaries

• Initial data analysis and pattern identification

• Route optimization calculations

• Inventory status updates

These tasks are important but they're not where your value lies. Your value is interpreting that data, making strategic decisions, managing relationships, and solving complex problems that require human judgment.

I use AI daily to handle routine analysis and communication tasks. It processes data, drafts routine emails, and creates first-pass reports. But I still make the strategic decisions, handle sensitive supplier conversations, and design the overall approach.

Not sure where to start? Try this prompt of ChatGPT or Claude:

I'm a supply chain leader working in [specific industry/company type]. I spend significant time on [describe routine tasks that consume your time]. Based on my role and responsibilities, help me identify:

1. Which of these tasks could be partially or fully automated using AI tools

2. Step-by-step approach to implement AI assistance for the top 3 time-consuming tasks

3. How to maintain quality control while using AI for these processes

4. What to focus my human attention on once AI handles the routine work

Format the output in clear sections with bullets and label each part. Use emotionally intelligent, strategic, and practical language focused on operational excellence.

Guardrails Aren't Optional—They're Essential

Here's where too many companies mess up. They treat AI implementation like installing new software. Deploy it, train people, and hope for the best.

But AI isn't just software. It's making decisions about your inventory, your suppliers, your routes, your customers. Those decisions need guardrails.

Think about your current quality control processes. You don't just trust every supplier to deliver perfect materials. You inspect, you verify, you have backup plans. AI needs the same approach.

Essential guardrails for supply chain AI:

Data integrity checks: AI is only as good as your data. Garbage in, garbage out isn't just a saying, it's a business risk.

Decision boundaries: Define what AI can decide automatically versus what requires human approval. Start conservative.

Audit trails: Know why AI made specific recommendations. Black box decisions in supply chain can create black swan events.

Performance monitoring: Track not just whether AI is working, but whether it's working better than your previous processes.

Human oversight: Someone needs to understand what the AI is doing well enough to spot when it's going wrong.

For leaders who want to get this right from the start, I've created an AI Policy Generator that helps organizations develop values-based AI guidelines specific to their industry and risk tolerance. It walks you through the key decisions every supply chain organization needs to make about AI implementation.

Click here to get my AI Policy Agent.

The Job Reality: Displacement and Creation

Let's talk honestly about jobs. Yes, AI will replace some supply chain roles. Data entry positions, basic analysis jobs, routine coordination tasks, these are at risk.

But here's what I've learned from 10 years in leadership: Every technological advance in supply chain has eliminated some jobs while creating others. Barcode scanners replaced manual inventory counting but created roles in system management and data analysis. GPS tracking eliminated route planning clerks but created logistics optimization specialists.

AI follows the same pattern, just faster.

The jobs being created require a combination of operational expertise and AI literacy. They need people who understand both supply chain fundamentals and how to work effectively with intelligent systems.

Examples of emerging roles:

• AI-human collaboration specialists who design workflows combining human judgment with AI capabilities

• Supply chain risk analysts who use AI tools to model complex scenario planning

• Customer experience managers who use AI insights to improve service delivery

• Sustainability optimization specialists who use AI to balance cost, speed, and environmental impact

The leaders who start learning AI now, not to replace their expertise but to amplify it, will be the ones positioned for these opportunities.

But you don't need to become a programmer. You need to become an intelligent user who understands how AI can solve supply chain problems and how to implement it safely.

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Your Next Step: Learn AI For Your Role

Don't try to master AI in general. Master AI for supply chain leadership specifically.

I've built tools to help leaders navigate this transition. The FutureProof Agent helps you design a 6-month AI growth plan tailored to your specific role and industry. It's free and takes about 15 minutes to complete.

The key is starting with your existing expertise and building from there, not trying to become someone you're not.

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If You Only Remember This:

• AI is like fire or electricity—transformative when properly managed, dangerous without guardrails

• Your operational expertise is your advantage, not your limitation in AI implementation

• Focus on using AI to eliminate repetitive tasks so you can spend more time on strategic work

• Guardrails aren't optional—they're essential for safe and effective AI deployment

• AI will change jobs, but leaders who understand it now will be positioned for the opportunities it creates

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What's one repetitive task in your supply chain operations that could benefit from AI assistance?

If this helped inspire you to get started on what you already knew you could do but hadn’t yet seen the path froward clearly, subscribe, and if you can, recommend Joel’s page, Leadership in Change.