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Source | Getty Images

Workforce development is a perennial challenge for manufacturing . Finding skilled workers is always a concern, especially as companies look to succession planning and carrying business forward. But today’s workforce concerns are influenced by more recent trends such as increased adoption of automation solutions and the advent of AI.

In this installment of CW Talks, we explore the evolving role of AI in workforce development — both in terms of challenges as well as opportunities for those looking for careers in manufacturing, particularly involving advanced materials. In this interview, Michael Novak, president of AIJ Search (Orlando, Fla., U.S.), a recruiting firm devoted to helping clients build teams, offers his insights into how AI is shaping the search for talented and skilled workers.

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Michael Novak, president, AIJ Search. Source | CW

ÂÌñÏ×ÆÞ (CW): Can you talk about how a new generation of workers is interacting with AI, and what kind of opportunities the use of AI might open up for job seekers?

Michael Novak (MN): It opens up a ton of opportunities. And I like that you called it “interacting with AI,” because that’s the exact view that we [AIJ Search] feel that top performers are taking.

There’s an article that Indeed.com published recently that showed that around only 1% of jobs could be fully transformed by AI, and around 40% are not going to see a whole lot of transformation from AI at all. The remaining 59% of jobs is where we are seeing opportunity to “interact with AI” [i.e., impacted by AI but not completely replaced by it]. Indeed further broke that 59% down into two categories: 40% are what they call the hybrid transformation category, where generative AI [GenAI] handles the bulk of execution, but the human oversees and evaluates and intervenes as needed; and 19% fall into what they call the assisted transformation category, where the human worker remains the lead actor, with GenAI offering support.

It is through this interaction with AI where AIJ Search sees the most opportunity for this new generation of workers. People who are engaging in those 59% of jobs that may be impacted by AI are going to be able to manage complexity. They’re going to be able to steer the system. They’ll be focusing on solving the edge cases that GenAI can’t solve. I feel that there’s huge opportunity for employees in those fields , as successful employees are going to become really well versed in those AI tools that they’re implementing. Ultimately, they’ll use those tools to eliminate repetitive tasks and increase their efficiency — and they’ll shift their focus to become an expert in the human skills that best complement this automation.

CW: Can you talk about what this might mean for the composites and advanced materials industries? Obviously when we talk about advanced materials, we’re thinking about a lot of high-performance applications, R&D, prototyping and innovation. Can you talk about challenges and opportunities you see within this area?

MN: We know that demand for high-performance advanced materials is only going to increase, and that AI is fundamentally transforming advanced materials and composites in industry, R&D and academia settings. AI is generally accelerating discovery, revolutionizing research methods, reorienting education and training. Instead of relying solely on time-consuming trial-and-error experimentation, we’ve now got these AI-driven approaches that enable researchers to screen millions of potential material candidates and predict their properties at unprecedented speed and scale. This provides ample opportunity to discover new materials and applications, creating opportunity for academics to write great papers, and land new funding and new grants for their continued research.

In terms of challenges associated with embracing AI, you’ve got implementation and training costs to contend with. There’s going to be a lot of upskilling of people. How are we going to better use their skills and train them, and in some cases, completely re-skill certain employees in the workforce? Recruiting and retaining top talent is going to be huge, because that human element is still essential as AI works side-by-side with humans moving forward.

CW: What advice do you have for students or individuals looking for careers in advanced manufacturing?

MN: Right now is a bit of a scary time for students that are just looking to get their first job. There is concern because the job market has cooled for entry-level jobs — in large part because companies are trying to figure out how implementing AI is going to impact what they call an entry-level position. But, I think that the good news for these students — and history suggests — that the early career workforce is often the best prepared to adapt to new technologies.

There are a few recommendations that that I can offer for those students who are in engineering science-related fields and preparing to enter the field of advanced materials. The first is to learn how to use — not just understand — AI as a tool for your productivity. Really research what AI tools are being used for in the field that you want to specialize in. Gain those skills now. See if you can land internships or co-ops, where you can develop and apply these skills and add them to your resume.

My second bit of advice is to gain exposure to robotics and automation. The high cost of manufacturing in the U.S. will continue to push more robotics and automation into an increasing number of operations. Understanding how to work alongside robots and automated systems will help students that are entering the workforce land a job for sure.

The third bit of advice is to develop skills with data analytics. This is because AI systems generate huge data sets and humans are needed to interpret the insights and use them to make strategic decisions. So, if it’s not part of your core curriculum, take some electives that allow you work with data analytics. 

Finally, seek out a way to develop soft skills — a lot of programs, especially in material and science and engineering, don’t require a whole lot of soft skill courses. However, it’s important because partnering with AI requires humans who have critical thinking and problem-solving skills, and the ability to communicate and collaborate within a team is essential.