AI is everywhere—but is it doing the best it can do in the manufacturing field? The many possible uses of AI to eliminate repetitive tasks or speed up production lines are well-known and heavily implemented across many modern factory environments. And this has served industry players well thus far—71 percent have seen at least a five percent uptick in revenue with AI adoption. But a potential functional area for AI that is less tapped into is making manufacturing delivery more custom and personalized to end customers. With more quantity and greater quality of data in the right AI machinery, the people running the show can and should be equipped with everything they need to transform manufacturing delivery into something stunningly personal and specific to each and every consumer. 

But to make AI do more than just offload tedious tasks on the shop floor, manufacturers must pivot to a deeper, more strategic angle that makes space for AI personalization in product or service delivery. Here are three foundational principles that support this effort: 

Pair AI with people strategically

The crux of truly transformative AI implementation in manufacturing is not just adding another gadget to your factory floor—it’s using AI to enhance and augment our human skillsets for more powerful results. Some elements of manufacturing operations can and should remain very human-based in order to sell your brand as personal and understanding to your customers. But other operations can be replaced by AI to both increase speed and give our operators on the other end reading the output more insights. 

“Human and AI teams should also be structured in an integrated manner,” according to Nada R. Sanders and John D. Wood in the Harvard Business Review. “This allows humans to transcend their ordinary cognitive limitations, without placing unreasonable reliance on a robot to perform human tasks that require high degrees of care and skill.” AI can process and analyze with record speed and precision, but it will take uniquely human motivations to process that information, make careful decisions based on it, and push the action forward. True human care and concern—a commitment to the company’s mission and product—can not be outsourced to any type of AI bot. And it’s imperative that consumers still feel that authenticity regardless of how much AI is leveraged to get the job done. 

Leverage AI for more than just processes

As hinted at earlier, AI is much more powerful than simply a mere industrial “butler” assigned all the tedious, repetitive tasks your team would just rather not do. Rather, it’s a wide-open opportunity to not only execute those processes more efficiently but also learn from them more effectively and generate an actionable wealth of data that powers personalization for manufacturers. 

For example, Katia Walsh, the AI Chief at Levi’s, has elevated the use of AI to a whole new level, raising the bottom line through more personalized consumer experiences. AI uses data housed in a massive on-cloud repository to deliver dynamic insights regarding customers’ experiences with Levi’s—from firsthand pricing and marketing to external factors like climate changes, economic trends, and more. With AI taking the analytical grunt work off of leaders’ plates, there is more time for thoughtful data consideration and decision making rather than compiling spreadsheets day after day. Levi’s knows more about their customers, what they’re buying, what they’re looking for, and what external shifts forecasted in the future may impact these patterns. With that knowledge, Levi’s can intelligently step in to fill the gaps in customer needs and cater the experience to their unique geography, background, and more. AI isn’t just automating processes at Levi’s—it’s generating more dynamic wells of information that are actively used to reach customers more intimately. 

Continuously adapt infrastructure for AI demands

Finally, using AI for personalized manufacturing delivery will simply be unsustainable without foundational changes to business infrastructure and logistics to support it. Where many manufacturers previously had to hire narrow-scope experts with deep knowledge in a particular area, AI is now taking on a large portion of that need. The emphasis in this organizational hierarchy is no longer vertical but far more horizontal, full of many multi-talented, well-rounded skillsets that can proactively respond to the insights AI generates for more personable interactions with customers. 

Making these kinds of foundational changes, however, will take time as it shakes the very notion of how a business operates for many long-time traditional manufacturers. This lengthy transition time is in large part because AI success in personalization and customization is not a plug-and-play matter—it takes a thoughtful integration of human capital and AI machinery to unlock real benefits. “Shifting to mass customization requires manufacturers to make significant changes to well-engrained production processes,” according to Max Versace, founding director of the Neuromorphics Lab at Boston University. “They need to move away from mass production lines toward flexible production cells where new technologies will be coupled with the human operator, providing the necessary mix to propel factories to embrace this new standard.” The shop floor may start to look a little less like a repetitive assembly line in this new frontier, a scary prospect for some leaders. But for those who embrace the challenge and make the logistical changes necessary to support personalized delivery for their customers with AI support, the future is very bright indeed. 

AI is just one part of a vast and sometimes dizzying technical landscape underpinning a manufacturer’s operations. To find out how AI can seamlessly integrate with your existing platform, contact Simplus for a discussion about new innovative solutions tailored to your needs.