BIFMA conference is set to deliver strategic insights for manufacturers facing a rapidly evolving landscape.
Manufacturing is undergoing a profound transformation driven by advanced technologies that demand a shift in how industry leaders approach their business models, workforce, and product development. Jim Carroll, a noted futurist with over two decades of experience covering the sector, encapsulates this imperative succinctly: “Shift your focus from managing the known to mastering the next.” His forthcoming keynote at the Business and Institutional Furniture Manufacturing Association (BIFMA) conference is set to deliver strategic insights for manufacturers facing a rapidly evolving landscape.
According to Carroll, the fast maturity of industrial autonomous technologies—ranging from robots and machine intelligence to digital twins, augmented reality, sensor networks, and drones—is reshaping manufacturing in profound ways. This technological tide is not just about incremental efficiency gains but instead signals sweeping business model disruptions, legal complexities, workforce skill shifts, and the rise of new competitors disrupting traditional value chains. The challenge for manufacturers is to accelerate the adoption of these technologies or risk falling behind as the gap widens between potential and actual performance.
Carroll offers a roadmap that aligns with trends observed across the manufacturing sector globally. A central theme is the move from conventional “make-to-stock” models to “make-to-order” processes, propelled by technologies such as 3D printing to enable mass customization at scale. Embracing digital twins—virtual replicas of products and factory processes—enables rapid iterative design cycles, dramatically shortening innovation timelines from months to mere weeks or days. These insights mirror broader industry data that show manufacturers increasingly invest in real-time data analytics and digital transformation to enhance agility and responsiveness.
The push towards smart factories embodying advanced robotics, AI, and the Industrial Internet of Things (IIoT) is also evident in worldwide industry developments. For example, Xiaomi’s fully automated “dark factory” near Beijing produces over 10 million phones annually, showcasing how autonomous robotics and IoT devices significantly boost operational efficiency and scalability. Industry forecasts anticipate that by 2027, such automated systems will constitute about a quarter of all capital spending in manufacturing, with global demand for industrial automation growing nearly 10% annually through 2030. This is intertwined with an increasing commitment by manufacturers to deploy AI, machine learning, and IIoT technologies at scale, with many investing a significant share of their operating budgets toward digital tools including cloud platforms and 5G connectivity.
Echoing Carroll’s emphasis on workforce evolution, the future manufacturing environment demands highly skilled employees fluent in robotics, digitization, and AI. The days of traditional manufacturing labour are passing, replaced by roles that require digital literacy and adaptability. AI itself is expanding beyond simple automations like chatbots, with investments focusing on advanced applications such as machine vision for quality control, predictive maintenance of equipment, and AI-driven supply chain optimisation, dramatically transforming factory floors.
The rise of smart factories is fueling a shift from reactive to proactive management grounded in real-time data. Manufacturers are adopting IIoT sensors to enable predictive maintenance, improve quality assurance, and streamline decision-making. This digital backbone supports demands for greater agility as product life cycles shorten and production complexity increases, requiring organisations to manage high-mix, low-volume manufacturing with flexibility across all stages from design to assembly.
Collaboration and open innovation also feature prominently in Carroll’s outlook, highlighting the need to look beyond in-house R&D. Embracing external partnerships, crowd-thinking, and cross-functional teams facilitates faster innovation and more effective problem-solving in an environment where speed-to-market is crucial. Additionally, business models themselves are evolving. The integration of connected device capabilities into physical products paves the way for “service-ification,” where products generate recurring revenue streams through uptime guarantees and product-as-a-service offerings.
Despite economic uncertainties and policy fluctuations, Carroll stresses the importance of long-term strategic technology investments. He encourages companies to adopt a mindset of continuous experimentation and learning rather than waiting for perfect clarity. This aligns with broader industry moves from isolated pilot projects to fully integrated smart factories employing comprehensive data-driven and automation systems.
The manufacturing sector’s future is thus defined by accelerated digitalization, autonomous system integration, and a workforce transformed by technology. From China’s leadership in robotics innovation to global adoption of IIoT and AI, the industry is embracing a new paradigm where agility, technology mastery, and innovation are prerequisites for competitive survival and growth.