Can Adaptive Production Revive Our Factories?

The manufacturing industry is currently faced with a perfect storm of challenges: supply chain disruptions, labor shortages, sustainability pressures and major policy challenges. In May 2025, Bloomberg reported that US manufacturing activity shrank by the most it has since November 2024.

Meanwhile, a significant number of manufacturing jobs remain unfilled, and the problem is only expected to grow. A 2024 study conducted by Deloitte and the Manufacturing Institute projects a shortfall of up to 3.8 million workers through 2030. With rising inflation, geopolitical instability and a rapidly shifting technology landscape added to the mix, the result is a sector struggling to keep up.

“You have to automate more effectively and aggressively to fill the gap,” says Chris Stevens, SVP and GM of US Automation Business at Siemens. ““If you lag on that, you will be disrupted by those who are already doing it.”

Most manufacturing operations continue to depend on aging infrastructure. According to the US Department of Commerce, the US manufacturing base sits on trillions of dollars in legacy equipment, machinery and facilities—a staggering footprint that’s difficult to replace and costly to modernize.

This is precisely where the opportunity lies.

The manufacturing sector has the potential to remake itself and become more resilient than ever before, thanks to adaptive production—a commitment to nimble operations that can accommodate rapidly changing production requirements with the help of advanced technology.

Technologies like industrial AI, industrial edge computing and digital twin simulations are allowing manufacturers to adapt spontaneously to optimize processes and address workforce challenges. 

“Adaptive production technology is really the backbone of the next generation of manufacturing,” says Stevens. His first question to manufacturers: “Are you ready to take advantage of this technology without disrupting your existing operations and without ripping and replacing your installed assets?”

Already, the benefits of adaptive production are tangible. According to research conducted by MIT Technology Review and Siemens, AI-driven predictive maintenance has been shown to cut downtime by up to 50%. Digital twins—virtual simulations of real-life processes—are reducing time to market and cutting carbon emissions. AI-enabled high-speed cameras are identifying quality defects production lines orders of magnitude faster and more accurately than previous approaches.

According to Stevens, one consumer goods manufacturer reduced control center staffing by 75% after implementing the Siemens Industrial Copilot, a generative AI assistant that is tuned to the manufacturing environment. Instead of employees sorting through cryptic machine alerts and error codes on their own, the AI copilot converts machine language to natural language and can prioritize events and suggest solutions “instantly at the speed of software”—freeing up workers to focus on higher-value tasks.

The biggest message for manufacturers, says Stevens, is that “they have the power to transform and retrofit their operations today—without ripping out their existing installed assets—to gain advantage or just to stay competitive.”

The process starts with recognizing a new paradigm introduced by today’s advanced operating technology: the emergence of a data layer on top of manufacturers’ existing operations. Rather than focusing solely on new technology, manufacturers are now empowered to harness the potential within their operational tech data. 

Each manufacturer must evaluate its own needs and determine which technologies will best support their goals. According to Stevens, this kind of transformation was more challenging just five years ago—but recent advancements in AI and platform-based approaches have completely changed the game.

“Meeting each manufacturer—small or large—where they are is what’s most important to Siemens,” Stevens says. “Each situation is unique. Every customer of ours deserves their own vision of a more adaptive production capability.”