AI won’t replace factory workers - just how they work

I had a great conversation recently with Vaibhav Deshmukh, who leads supply chain at a major EV manufacturer in California. We got talking about AI in manufacturing - what’s hype, what’s real, and where it’s actually making an impact on the ground.

Vaibhav brings a rare combination of frontline experience and global perspective. With 11+ years in supply chain - spanning global sourcing for complex motor components to insulation materials - he’s seen firsthand how AI is shifting the way manufacturers plan, source, and operate.

In this guest piece, Vaibhav cuts through the noise. His message is clear: the future of manufacturing isn’t about replacing humans with algorithms. It’s about using AI to augment human decision-making - to help planners plan better, engineers focus on what matters, and buyers act faster.

If you’re in manufacturing or adjacent to it, this is a practical and well-argued perspective on how to work with AI - not fear it.

Here’s Vaibhav 👇

AI in Manufacturing: Augmenting Human Ingenuity, Not Replacing It

As someone deeply rooted in the intersection of advanced manufacturing and global supply chains, I’ve seen firsthand how artificial intelligence is becoming an integral part of the industrial fabric. From predictive maintenance to intelligent quality control, AI is no longer just a buzzword - it’s quietly redefining how factories operate, how decisions are made, and how supply chains respond.

Yet, I often encounter a recurring fear: “Will AI take over jobs?”

This question paints an overly simplistic picture of the situation on the ground. The goal of AI isn’t to replace people, but to empower them to do more. The most impactful implementations of AI I’ve seen are not about automation for automation’s sake. At the heart of these solutions is human augmentation - empowering experts to make faster, more accurate, and more strategic decisions.

Today’s manufacturing world is far more complex than it was a decade ago. Factories are expected to produce more variants, at higher quality, with tighter margins and shorter lead times - all while maintaining safety and sustainability targets. This level of complexity cannot be tackled with spreadsheets and gut instinct alone. That’s where AI brings its value - it brings clarity to complexity.

Production planning is a great example. Traditional scheduling relied heavily on experience, fixed rules, and reactive firefighting. But with AI, manufacturers can now simulate thousands of scheduling scenarios in real-time - accounting for machine downtime, labor availability, material delays, and even weather disruptions. These AI-generated insights don’t replace the planner. Instead, they help the planner focus on trade-offs, anticipate disruptions, and make more informed decisions.

On the shop floor, AI-powered computer vision is transforming quality control. Systems now detect surface defects, dimensional deviations, and assembly errors with a level of consistency and speed that humans simply cannot match. But again, it’s not about removing people - it’s about enabling operators and quality engineers to focus on root-cause analysis, corrective actions, and continuous improvement, rather than spending hours visually inspecting every part.

Now let’s talk supply chain - an area close to my heart. AI has opened up entirely new possibilities in how we manage sourcing, logistics, and supplier relationships. Imagine a system that tracks real-time supplier data, freight availability, commodity indices, and geopolitical events - and uses all of that to alert a buyer about a potential material shortage three weeks in advance. This is not science fiction. This is happening now, and I’ve seen it in action.

However, what AI cannot do is build trust with a supplier, understand local customs during a factory visit, or assess long-term strategic alignment during a negotiation. These are human tasks. These are relationship-driven decisions. AI might inform your choices, but it doesn’t replace the wisdom gained from experience.

The most underappreciated benefit of AI in manufacturing is the cognitive relief it provides. Let’s face it - many talented professionals in this industry spend too much time on repetitive, low-value tasks. Maintenance engineers fill out the same checklists. Buyers create the same RFQs. Planners adjust the same parameters day after day. AI can automate much of this grunt work, freeing up time and mental bandwidth for innovation, collaboration, and strategic thinking.

AI adoption succeeds not just through tools, but through enabling the people who use them. On the factory floor, success requires that operators, engineers, and buyers embrace data, adapt to change, and work alongside technology. This digital fluency will define the competitive edge in the next decade.

Ethics also matter.

As AI becomes more involved in critical decisions - from product quality to supplier selection - transparency and accountability must remain non-negotiable. Our systems must be transparent, accountable, and just. Human oversight is not just a safeguard; it’s a responsibility.

In this journey, I’ve learned that the best results come when we stop thinking of AI as a threat and start thinking of it as a teammate. A teammate that doesn’t get tired, that doesn’t miss patterns, that brings data to the table without bias. But still - it’s a teammate that needs human direction, context, and judgment to perform at its best.

The factories of the future will not run solely on machines. They’ll run on collaboration. Collaboration between people and algorithms. Between experience and innovation. Between the known and the predictive.

AI will give us speed, scale, and foresight. Humans will bring empathy, ethics, and adaptability.

Together, they’ll create a manufacturing ecosystem that is not only more productive—but also more human-centered.

So absolutely no - AI won’t replace us. It will redefine us. And in doing so, it will unlock a version of manufacturing we’ve only imagined - smarter, faster, and more resilient than ever before.