In the Age of AI, Manufacturers Won’t Need Engineers. Or Will They?

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Feb. 26^th of this year was the day that AI’s impact on the workforce became real for me.

For 14 of the last 15 years (thanks, COVID), I have spent the better part of a week each winter skiing with a group of close friends. Beyond yours truly, the quintet comprises a former Fortune 500 CEO, a maxillofacial surgeon, a department chief for one of the nation’s largest pediatric hospitals and a well-known Midwest entrepreneur. On the IQ scale, I’m the straggler in the group, but I do my best to keep up with the deep intellectual conversations that fill the trip.

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In late February, during our 2026 excursion, Block Inc. (formerly Square) founder and CEO Jack Dorsey announced that Block was eliminating 40% of those working in its financial services and digital payments company, attributing the downsizing to productivity opportunities brought about by AI. Essentially, Dorsey said that a leaner group of AI-proficient team members using tools Block was building could “do more and do it better.”

I read that and announced to my friends, “We’ll look back on today as the day the transformation of the entire workforce began.”

Literally two days later, a headline in the Wall Street Journal referencing the layoffs at Block, exclaimed, “The Week the Dreaded AI Jobs Wipeout Got Real.” I was clairvoyant by two days! Indeed, the world of work is being transformed before our very eyes.

What does this mean for those employed in manufacturing — particularly the manufacturing engineers, industrial engineers, materials engineers, electrical engineers and those in similar positions that currently comprise the backbone of manufacturing operations and continuous improvement?

Would it surprise you to hear me say that the news is really good for them? A quote from another Wall Street Journal article, this one an op-ed, tells us why. The headline, “How I Choose Which Cloudflare Employees to Replace with AI” is eye-grabbing. You can read the entire article if you choose, or better yet listen to the recent TechEd Podcast monologue where I unpack it.

To summarize the article, Matthew Prince, co-founder and CEO of Cloudflare — the infrastructure and cybersecurity company who lays claim to powering 20% of the internet — makes the point that salespeople and “builders” in roles like the engineers referenced above stand the most to gain in the age of AI. Prince writes, “Contrary to what some analysts predict, builders aren’t going anywhere. If an engineer on my team can now be 10 times as productive, I’m going to hire as many as I can find.”

Great news for engineers, with the key conditional conjunction being “if,” as in if, by using AI, the engineer’s productivity can increase by 10 times.

To solve for “if,” the role of the builder/engineer must evolve significantly in the age of AI. Individuals in these positions will see their value to their employers rise by an order of magnitude if they learn how to leverage AI in their work.

To get our thinking right, consider how the discipline of engineering is already changing. Gone are the pencils, clipboards and stopwatches we once used to determine cycle time, productivity, efficiency and yield, long since replaced by smart sensors and data acquisition tools. Today, AI enables us to find patterns in, and derive inference from, layered data in ways we never would have been able to prior to AI, identifying novel and major continuous improvement opportunities. Our builders must know how and when to use these tools.

We are on the cusp of being able to “digital twin” not just our manufacturing processes and floors, but our entire enterprises, including supply chain, customer service and financial performance. Our builders must be proficient in digital twin technology.

Many engineers are already adept at uploading myriad data sources (part drawings, work instructions, equipment schematics and records of process variables) into secure versions of generative pretrained transformers like Claude, Perplexity, ChatGPT or MetaAI, and then asking the AI platform to perform useful analysis, identify pain points or prepare reports. This is a must-have skill for future builders.

Others are using vector databases with access to troubleshooting guides, operating manuals, bills of materials and machine schematics, in addition to Application Programming Interfaces (APIs) to dynamic data sources to create searchable databases and chatbots that expedite root cause identification, problem analysis and resolution.

Fascinating, all of it. And we’re just scratching the surface of how AI is transforming manufacturing.

Now and going forward, one of the greatest differentiators between world-class manufacturers and struggling ones will be how their engineering teams embrace and leverage AI to improve, troubleshoot, innovate and grow. In a sea of downsizings and layoffs of all those in the middle of the organization chart, engineers who know AI stand to not just fare well but thrive. AI is great news for builders.