Earlier this year, Christina Parker, senior vice president for Randstad USA, appeared on Food Processing’s “Food For Thought” podcast to discuss the sentiment on artificial intelligence in the manufacturing space, highlighting a disconnect between what employers and employees expect the impact to be over the next few years.

Building off that conversation, Parker offered her insights into how the food & beverage processing industry stacks up against other manufacturing sectors when it comes to implementation of AI and machine learning. She also details some of the hurdles companies are facing and where the opportunities for success sit for food and beverage companies seeking improved operational efficiency and quality through AI.

What follows is a portion of her conversation with Senior Editor Andy Hanacek.

Andy Hanacek: If you had to categorize AI and machine learning adoption in food & beverage processing, would you say it’s still in its infancy, adolescence or some other level?

Christina Parker: I’d say we’re in the toddler stage. A lot of manufacturers are implementing AI, but many haven’t fully integrated it into their workforce yet. Food & beverage manufacturing is a bit of a mixed bag, because companies don’t want the downtime associated with implementing new technology. If I had to quantify it, about 65% of all manufacturers (beyond just food & beverage processors) have invested in AI within the past 12 months. That’s not an overwhelming majority, but it’s certainly a significant portion.

AH: The amount of data and infrastructure needed to support AI can be staggering. Is building and organizing that data one of the biggest hurdles, or are most manufacturers already in a position to share that data?

CP: Most of them have the ability to share the data. Where we see the real disconnect is workforce readiness. We’ve done quite a bit of research through our Workmonitor report to understand where those gaps exist. The issue isn’t necessarily the companies or their data — they generally have the ability to feed information into AI systems and robotics. The challenge is whether employees are prepared to work alongside the technology.

Manufacturing, especially food & beverage, is still facing a skilled labor shortage. On top of that, employees don’t always feel confident using AI. They don’t believe they have the skills needed to work with these tools, and that’s preventing many companies from moving further with implementation.

In our latest Workmonitor, 64% of workers said they feel they can use AI, compared to 78% last year. As AI continues to evolve — from ChatGPT to Claude and countless other platforms — employees feel like they’re constantly trying to catch up. At the same time, manufacturers often don’t have the luxury of dedicating production time to training because they’re focused on meeting production goals.

AH: Let’s talk about where AI is succeeding today. At this “toddler stage,” where are food and beverage companies seeing the greatest benefits?

CP: One of the biggest success stories is predictive maintenance. Instead of waiting for equipment to fail, AI analyzes machine vibration, temperature, motor current, sound and pressure to predict failures before they happen.

I recently visited a food manufacturer that’s using this on its packaging line. The system detected an abnormal vibration on one of the conveyor motors. Rather than experiencing an unexpected breakdown during peak production, the maintenance team replaced a $400 bearing during scheduled maintenance. That prevented eight hours of downtime, avoided losing thousands of pounds of product and eliminated overtime labor costs. In food manufacturing, you can’t simply make up lost production because products are perishable and time-sensitive.

Another area where we’re seeing tremendous success is quality inspection. AI-powered vision systems inspect products faster and more consistently than people can. They’re identifying missing labels, incorrect fill levels, damaged products, foreign materials, color inconsistencies — even baked goods that are too light or too dark for consumer expectations.

I work with a snack manufacturer producing tens of thousands of potato chips every minute. Their AI system identifies burnt chips, broken chips and chips that fall outside size specifications, all without slowing the production line.

AH: Recently, there have been a couple examples in other industries where companies have pulled back from AI. Are you seeing situations in food & beverage where AI simply isn’t the right solution?

CP: I haven’t really seen situations where AI isn’t effective. What I see more often is companies that simply aren’t ready to adopt it. Some manufacturers are concerned about how AI will affect production or their workforce. Others just don’t know where to begin, which is understandable because it’s still relatively new technology and we don’t yet know all of the long-term implications. Some companies are easing into AI by using it for production scheduling or administrative functions instead of incorporating it directly into manufacturing operations.

AH: Aside from workforce readiness, what other barriers to implementation are companies facing?

CP: AI adoption isn’t effortless. One challenge is integrating AI with older equipment. If companies need newer machinery to support AI, that’s a significant capital investment, and many aren’t in a position to make those investments in today’s economy.

Cybersecurity is another concern. Companies need confidence that their data will remain secure. Data quality also matters because AI is only as good as the information it’s given.

Finally, there’s employee training and change management. Companies need to build trust so employees see AI as a tool rather than a threat. A disengaged workforce is the last thing manufacturers need when they’re trying to meet production goals.

AH: On the workforce side, are companies hiring AI specialists or are they retraining existing employees?

CP: It’s really both. We’re still facing workforce shortages, and employees are asking for more training. In our Workmonitor research, 60% of workers said they need additional AI training. The question is whether manufacturers are willing to make that investment. Ironically, AI itself can even help train employees.

At the end of the day, technology alone doesn’t create competitive advantage — people do. People will always be at the heart of manufacturing. AI simply helps them make decisions faster, identify patterns humans might miss and automate repetitive tasks. Manufacturers need to invest in both the technology and the people if they want to improve operations.

AH: That seems to me to be one of the biggest shifts in thinking. Early on, AI was viewed as something that would eliminate jobs. Instead, it appears to be changing jobs and helping people become more effective.

CP: Exactly. That’s one of the biggest misconceptions. AI isn’t taking jobs — it’s changing the skills people need. The future of manufacturing isn’t people versus AI. It’s people empowered by AI to do their jobs better.

AH: Speaking of the future, what opportunities do you see over the next several years that food & beverage manufacturers may not be taking advantage of today?

CP: I think within five years AI will be just as commonplace as PLCs, automation and robotics are today. Those technologies once seemed futuristic too. The question won’t be whether manufacturers implement AI — it will be how they implement it.

The companies that succeed will integrate AI into their people, processes and operations, so it becomes a tool that supports employees rather than replacing them. Manufacturers that invest in both technology and workforce development will be the ones that thrive.