Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Henrik Hulgaard, co-founder and vice president of product management; Daniel Joseph Barry, vice president of product marketing; Laura Beckwith, director of product management; Sigrn varsdttir, product manager, Configit
It’s impossible these days to discuss what’s ahead without including AI. Its disruptive potential particularly applies to the manufacturing industry, yet that’s not the only factor bringing transformation. Data also plays a significant role, as do customer expectations and the reality of an aging workforce. Below are six predictions that address these factors and what’s possible in the new year.
AI will usher in greater manufacturing efficiency
Discrete manufacturers are already increasingly using AI to optimize configuration processes, and we expect to see this trend in hyperdrive in 2026. AI will enable faster translation of market insights into refined product offerings, simplify engineering through more efficient bill of materials (BOM) management, and accelerate the creation and validation of configuration models. These advances will not only enhance how products are defined and sold but also streamline collaboration across marketing, engineering and operations. As manufacturers continue shifting from engineer-to-order (ETO) to configure-to-order (CTO) models, AI-powered productivity tools will play a central role, reducing manual effort, shortening lead times and enabling smarter, data-driven customization. The result will be more agile, responsive manufacturing ecosystems designed to meet evolving customer needs at scale.
AI will reshape the configuration process
AI is rapidly transforming configuration processes in manufacturing, both in terms of how models are built and how configurations are executed. It is already having a significant impact on two processes: modeling, where product features and rules are defined, and configuration, where users select compatible options to meet customer requirements. In the coming year, these processes face more rapid change. We believe that the change that has the most impact but is also the most challenging is to use AI in modeling. Instead of having modeling experts who know how to write rules, AI can take unstructured data such as paragraphs of text or diagrams from documents and automatically translate this information into product models. This approach has the potential to dramatically reduce the time required to create the configuration models as well as making it possible for product managers to maintain the information themselves.
AI will also reshape the configuration process itself. Rather than navigating complex interfaces, users will describe what they need in natural language, and AI will assemble a valid configuration, potentially even coordinating with sub-suppliers’ systems via intelligent agent workflows. Together, these innovations promise faster, smarter and more collaborative configuration across the manufacturing value chain.
The competitive advantage goes to data interoperability
Data interoperability will become a real differentiator, as manufacturers realize that aligning systems across the product lifecycle is key to scaling AI effectively.
Synchronized data sources will drive efficiency
As generative AI captures the attention of C-level executives in the discrete manufacturing sector, there’s massive pressure to become more efficient. AI technologies provide a lot of capabilities that can help manufacturers to achieve their efficiency improvement goals. While this opens manufacturers to new approaches and technologies, it also forces them to look under the hood to understand how their operations, especially their IT systems, are operating today.
What they’re likely to see is a fragmented landscape of data sources that aren’t aligned and are difficult to synchronize, leading to errors and delays. As a result, these leaders will realize that the first step in achieving their efficiency goals through AI is to build a reliable data foundation with connected systems, connected data and connected logic.
Institutional knowledge capture will be crucial as workforce ages
With an aging workforce, manufacturers face a critical knowledge transfer challenge. Capturing and digitizing configuration and engineering knowledge will be essential in order for manufacturers to stay competitive. In 2026, we expect to see acceleration of efforts to digitize this tribal knowledge. AI can play a key in preserving and surfacing the expertise of veteran workers.
Customer expectations will necessitate cross-divisional alignment
A big shift will come from tighter integration between PLM and ERP/Sales, ensuring engineering, manufacturing, sales and service all work from a shared source of truth. This will be an important shift as customers continue to expect more personalization with shorter lead times, which puts more pressure on aligning what’s offered commercially with what can actually be built.
Changes for the better
Clearly, AI is poised to transform manufacturing. It stands to help companies address significant issues with knowledge transfer, data management, customers’ increasing demands for customization, and configuration itself. Manufacturers who embrace AI will see much higher efficiency and adaptability with fewer errors and less rework while retaining the internal information needed for ongoing success.
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ABOUT THE AUTHORS
Henrik Hulgaard is the vice president of product management and co-founder of Configit, the global leader in Configuration Lifecycle Management (CLM) solutions and a supplier of business-critical software for the configuration of complex products. He holds a doctorate in computer science from the University of Washington and is an associate professor of computer science. He has published more than 25 articles internationally.
Daniel Joseph Barry is vice president of product marketing at Configit. He has over 30 years of experience in the telecom and IT industry, working in various technical and commercial roles.
Laura Beckwith is director of product management at Configit, where she focuses on ensuring that it’s not just the most technically minded who will benefit from the software Configit develops and sells.
Sigrn varsdttir is a product manager at Configit, focusing on the company’s core technology and improving product performance through close collaboration with customers and engineers. She holds a master’s in engineering management from the Technical University of Denmark, where she wrote her thesis on configuration systems.
