The manufacturing industry is at a crossroads: Geopolitical instability is fracturing supply chains from the Suez to Shenzhen, impacting the flow of materials. Businesses are battling rising costs and inflation, coupled with a shrinking labor force, with more than half a million unfilled manufacturing jobs in the U.S. alone. And climate change is further intensifying the pressure, with more frequent extreme weather events and tightening environmental regulations forcing companies to rethink how they operate. New solutions are imperative.

Meanwhile, advanced automation, powered by the convergence of emerging and established technologies, including industrial AI, digital twins, the internet of things (IoT), and advanced robotics, promises greater resilience, flexibility, sustainability, and efficiency for industry. Individual success stories have demonstrated the transformative power of these technologies, providing examples of AI-driven predictive maintenance reducing downtime by up to 50%. Digital twin simulations can significantly reduce time to market, and bring environment dividends, too: One survey found 77% of leaders expect digital twins to reduce carbon emissions by 15% on average.

Yet, broad adoption of this advanced automation has lagged. “That’s not necessarily or just a technology gap,” says John Hart, professor of mechanical engineering and director of the Center for Advanced Production Technologies at MIT. “It relates to workforce capabilities and financial commitments and risk required.” For small and medium enterprises, and those with brownfield sites—older facilities with legacy systems— the barriers to implementation are significant.