It feels today as if the whole world is consumed by a focus on AI. In media, in industry, and even in our day-to-day lives, AI tools have come front and center at an almost unheard-of pace.
In industrial manufacturing, the rise of AI is incredibly apparent. While it is true that AI has been embedded in industrial manufacturing technology for years—most commonly as machine learning algorithms—the rapid improvement in just the last two and a half years, based in natural language processing, data analytics, and generative AI, are proving to be a step change for the technology.
In their recent article in Plant Engineering magazine, Emerson’s Claudio Fayad and Steve Williams explore the rise of AI in the automation industry, noting that there are many options out there for bolt-on AI technology, but the most valuable, effective solutions will always be those delivered as part of a seamless, fit-for-purpose automation system.
“Ultimately, businesses will increasingly adopt new AI solutions to improve how they operate, whether those solutions are fit-for-purpose and standalone or embedded elements of existing automation solutions. However, in both cases, doing so effectively will mean finding ways to navigate an increasingly broad and complex landscape of solutions, each with its own unique capabilities and requirements. Therefore, it is worthwhile to consider how AI technologies can be implemented as part of a seamlessly integrated holistic solution across operations and the enterprise.”
Why now?
While it’s true that advancements in AI have been incredibly rapid in the last couple of years, the move to adopt AI is driven by more than the shiny bells and whistles the technology can offer. Cultural shifts in the industry have also created a perfect environment for the capabilities of AI to deliver value.
“Technology advances, increasing mobility and globalization, geopolitical shifts, and more have created a volatile, uncertain, complex, and ambiguous environment that has increased competitive pressures. As demand, supply chains, workforces, and other key enablers of efficient operations continue to evolve, manufacturing organizations are shifting their strategies to an approach focused on flexibility, monitoring demand and changing production as necessary to meet changing marketplace needs.”
AI can help close these gaps, especially the ones created by the recent shrinking of an available expert workforce. Industrial AI tools can help process manufacturing organizations increase agility, deliver in-context guidance, and enhance productivity, all while simultaneously upskilling employees faster than ever before.
The value of holistic solutions
The rise of AI is not without its pitfalls, however. Every day there are more companies offering a wide array of bolt-on AI solutions for the problems process manufacturers face in the new global marketplace. The best tools offer dramatic efficiency gains, and the worst are often vaporware. But in both cases, if AI technologies are not added thoughtfully, they can potentially cause more problems than they solve. Claudio and Steve explain,
“As teams start implementing a wide array of disparate AI tools from a variety of suppliers, they often quickly discover challenges to effective deployment.”
“AI-ready automation will require a rich OT data ecosystem that not only drives copious amounts of data to and from any automation technology across the enterprise, but does so while preserving rich context, broad and secure connectivity, and layered analytics. If data is trapped in various silos across the enterprise or is delivered without the rich context necessary to turn large data into smart data, AI tools will struggle to generate trustworthy, actionable insights.”
Claudio and Steve argue for a better strategy: one rooted in an enterprise operations platform designed as part of a boundless automation vision. In such an environment, context-rich data flows freely from the intelligent field, through the edge, and into the cloud—all places where AI technologies can be found. That free movement of data breaks down silos and fully supports AI solutions with a continuous stream of valuable data.
What’s more, focusing on delivering AI solutions as part of an enterprise operations platform helps ensure AI technologies are seamlessly integrated with the automation technologies they serve. That means they will function as expected—as they will be vetted by expert automation solution providers with deep industry expertise— and will continue to grow and improve over the lifecycle of the automation system. Moreover, because such tools will integrate seamlessly as part of an operator or technician’s standard workflow, they will be more universally adopted by personnel and far easier to teach.
It is not too early to start preparing for this integrated industrial AI future. As Claudio and Steve explain,
“The foundation for such a technological leap is already available today, and it will continue to improve and scale in the coming years. Now is the time to get on board and capture the innovation capabilities that will drive competitive advantage for years to come.”
Teams can begin building their readiness for a new AI foundation by modernizing their automation technologies to support these new solutions. It’s never too soon to start preparing for the future—when that preparation comes with planning and strategy.
