How to Confidently Introduce & Leverage AI Copilots and Agents in Supply Chain

In This Article

How Are Copilot and Agents Different?

Copilot is interactive: your coach on the field, providing real-time guidance and insight. 

Agents are autonomous: trained players that execute your strategy independently in the background.

Together, they analyze, choose, act, and evolve for measurable outcomes. 

What is Microsoft Copilot?

Microsoft Copilot is your AI-powered personal productivity assistant for manufacturing. A partner that amplifies your productivity and takes the grunt work off your plate.

Copilot is similar to many generative AI models you may have seen before. Basically, you enter a prompt (using your keyboard or microphone) and the software responds with AI-generated information that you can then review, iterate, and finalize.

But Copilot is developed specifically for work tasks. So, AI can pull information from the internet as well as internal work content to build its responses… and you control what it has access to.

The result is higher efficiency, less admin and busy work on your plate, and more time to focus on the tasks that really matter.

What Are Agents?

Microsoft Agents are AI-powered specialists designed to take on entire processes or workflows inside your business. Think of them as focused team members you can assign specific responsibilities to, whether that’s reconciling accounts, monitoring inventory, or handling supplier queries.

Unlike Copilot, which works alongside you on tasks you initiate, Agents operate more independently. You define their role, give them access to the right data, and set guardrails. From there, they can run continuously in the background, executing instructions, monitoring for changes, and triggering actions without you having to prompt them every time.

This makes Agents especially valuable in manufacturing and distribution, where repetitive processes and cross-system tasks can drain time and attention. By handling these operational workflows, Agents free your team to focus on higher-level decisions while still keeping you in control.

The result is a stronger, more automated operation without adding headcount.

Copilot and Agents in the Supply Chain

As your AI-powered assistants for manufacturing and distribution, tools like Microsoft Copilot and purpose-built agents are revolutionizing the industry. Here are just a few of the relevant scenarios they can tackle:

• AI Copilots and agents work together to handle the tedious details, keep communication flowing, and optimize operations. Imagine this: while your copilot automatically takes notes during a sales call, flags action items, and even drafts the follow-up email, agents are already handling the next steps — confirming POs with suppliers, updating order status, or escalating issues without manual follow-up.
• The same teamwork shows up in communication. Copilot can coach you in real time, streamline complex email threads, and generate clear summaries of warranty claims or reports. Agents then act on those insights, implementing instructions for work orders, reconciliations, or supplier updates.
• And in operations, they’re just as complementary. Copilot helps teams make sense of sprawling data, while agents continuously improve inventory accuracy, optimize warehouse slotting, and free up capacity — all while cutting costs. Together, they transform day-to-day supply chain tasks into a seamlessly connected system that runs faster, smarter, and with less human drag.

So, imagine your field service tech tells Copilot about a problem with a machine, including what did or didn’t work to fix the issue. Copilot can capture the details in real time, updating the work order with symptoms, tasks performed, and recommendations for follow-up. From there, an agent can take over, automatically categorizing the incident (break-fix, preventive maintenance, or proactive maintenance), routing it appropriately, and even moving the work order along in D365 Field Services or a custom workflow. Together, Copilot and agents turn a manual process into a closed loop of instant documentation and automated action.

That same teamwork extends beyond service calls. For example, in hiring, resumes uploaded to a SharePoint folder can be analyzed by a custom agent built specifically to answer questions on that dataset, instantly surfacing who has stronger experience in X or the most years doing Y. Copilot supports by drafting outreach or summarizing interview notes, while the agent ensures your decisions are based on precise, structured insights.

Finance teams benefit from the same partnership. Copilot can help reconcile accounts across multiple ERPs, while agents continuously monitor transactions, flag anomalies, and automate repeat processes. The result: less time spent chasing numbers and more time making strategic decisions.

How Do I Adopt AI Without Risking Errors? Trust But Verify.

What’s the largest Copilot and agent-related struggle we see manufacturers and distributors grappling with? Letting go of control. We, as humans, have a hard time delegating tasks… even to other humans with whom we’ve already worked. This challenge is only amplified when trusting AI’s actions.

That’s because users often don’t fully understand what Copilot and agents are doing, or what it’s capable of until they’ve used it for a while. Like humans, AI can sometimes make mistakes.

But these aren’t reasons to write it off. Like a new (human) intern, a new AI solution is merely predicting the correct next word or action based on the data and training previously provided. The solution is more training and time to adjust.

If you were hiring a new employee, you would verify trust with that new hire, give them feedback, and watch to see how they do.

Use the same “trust but verify” approach with Copilot. This comes down to reviewing and approving AI’s suggestions initially to train it up while you build confidence in its capabilities.

User training sessions can also help with understanding, efficiency, and adoption among your team members.

Having a continuous improvement culture or having change management support can help ensure financial performance, the meeting or exceeding of goals, and even driving ROI.  

Misconceptions About AI in the Supply Chain

Is AI going to replace the people on my team… or one day replace me?

Generally, we’re not all losing our jobs. Work will certainly evolve, as AI technologies automate things like admin and busywork. But this means our jobs should only get better. Not disappear completely. Think of it as automating the more repetitive tasks that you would rather not do so you can focus on the more creative, insightful, and impactful work you were hired to accomplish.

Tips for Employing Chat and Autonomous AI

When it comes to implementation, every business is going to have a different approach, and no company’s process is “wrong.” But, in our experience, there are a few key considerations:

Build Your Team 

Form a group of enthusiasts who would like to try the latest in AI and build a cross-functional team to drive feedback and improvement. This group can discuss what out-of-the-box applications aren’t working well enough (and discuss solutions) and share what works well. 

Start Slow 

Turn Copilot or agents on in just one area – one agent for one supplier, perhaps. Then, slowly add more agents and more tasks as you get more comfortable. 

Prove it Out 

Prove the strategy before you scale it up. What’s working? What needs to be tweaked? Address any glaring issues now. 

Designate a Champion

Find a team member who is excited about offloading their more mundane tasks. This person will become your change agent (the human kind), a champion who cannot help but share how AI has saved him or her a lot of time and provided new insights. This champion will start to affect the culture and perspective of others around him/her, expanding Microsoft Copilot. 

For continuous improvement of the model, make sure there’s an appropriate level of AI supervision.  

Remember: just like a human employee, AI has the potential to get better. But it needs to be supervised in some way.  Even an AI agent needs an annual review! 

For example, let’s say you make a website chatbot. At some point, a user will hit that “thumbs down” button. This is where you need to investigate. 

What motivated this feedback? Was the answer incorrect? Was it correct, but not the answer the user wanted? Was there a better answer the bot could have provided? The answers to these questions can help you tweak your AI for continuous improvement.  And sometimes the user has asked the bot to accomplish a task you had not considered before. 

To further expand AI solutions, you might also want to revisit your data strategy. The output ultimately depends on the input, so Copilot needs quality and connectivity in data to function at its best.