AI isn’t just a buzzword - it’s already changing how we design and run food systems, from production lines and packaging systems. A recent article highlights how smarter automation is leading to self-optimising systems, machines that can adapt to different inputs and shifting production needs without constant human oversight. It’s a glimpse of what the future of our factories could look like…

An example of utilising this was with Mondelez, the company behind Oreos etc, they’ve been using AI to tweak snacks and launch products up to five times faster than before. One tool alone has played a role in over 70 product projects, including the Gluten-Free Golden Oreo, all whilst ensuring these still taste like the brand we all know and love.

It’s not just about speed; these tools can help you see options you might’ve missed. You set the rules, like space, energy, and hygiene standards, and the system plays around within those limits. It may suggest a conveyor layout that saves power without slowing things down, or a lighter packaging design that still ticks all the compliance boxes.

With these tools, mistakes get caught before anything is even built. AI can simulate real-world conditions, including temperature changes, humidity, and cleaning cycles, it can highlight potential failures ahead of time. That means less rework, fewer breakdowns, and more confidence in what gets built will actually work.

Still, AI isn’t magic. It sometimes misses the nuances of a food factory floor, so engineers need to mentally double-check its suggestions. It also brings the need to learn new tools and collaborate with machines in new ways, and while some worry AI will replace jobs, the current reality is more of a partnership: automation doesn’t replace the creative, problem-solving parts of engineering but can have a strong advantage to the process.

We can already see where this partnership is heading. A smart bakery in Queensland, Australia, built an AI-powered “smart factory” with robots and autonomous vehicles handling the heavy lifting, which doubled production whilst allowing engineers to focus on other tasks. It even integrated solar power and greener ovens to cut emissions, showing how AI and sustainability can go hand in hand.

Of course, AI in food engineering has its challenges. Data quality, system integration, and transparency still cause real hurdles. Building AI tools that are powerful, trustworthy and making sure regulatory frameworks keep pace, is still a big ask.

AI isn’t here to take creativity out of engineering. The engineers who thrive will be the ones who know how to utilise these smart tools, using their own knowledge and instincts alongside AI’s speed and insights to drive food engineering forward.

Engineers what do we think?