Our panel of automation experts offer advice on automation trends, how manufacturers are scaling automation against economic uncertainty and what to watch in 2026.
Automation insights
- Artificial intelligence (AI) is helping manufacturers drive efficiency and prioritize preventive and predictive maintenance.
- Digital twin technology is rapidly evolving and becoming a must-have for manufacturers.
- Legacy systems are being integrated with new automation technologies to better streamline processes.
Q: What are the most significant automation trends shaping plants in 2025?
Heath Stephens: In many ways, automation trends in 2025 were shaped by two opposing forces: the constant drive to increase efficiency and profitability and companies’ hesitation to invest with an uncertain economic outlook. This year was certainly a year when more companies started to look at how generative artificial intelligence (AI), like ChatGPT and others, could be more directly used in industrial applications. While not replacing special-purpose industrial AI applications, Gen AI will give us new ways to interact with our processes and sort through data.
Sean McGowen: The most common trend that I have been involved with, across multiple industries, is automating customers’ machine monitoring. This allows maintenance and reliability departments to focus their most valuable resource — labor — on day-to-day operations instead of periodic checks that may not be needed at that time. It also brings valuable data that allows these teams to mold their preventive maintenance and inspection programs to fit their specific equipment and facility needs. These systems can be scalable to gather both equipment and atmospheric data on the plant floor, which is useful for converting from a run-until-failure thought process to a truly predictive mindset.
Geert van der Zalm: Implementation of high-speed conveyance moving from electronics manufacturing towards automotive, enabling significantly faster throughput time and integration of process steps into the conveyance motion.
Sean Saul: In 2025, it was the year that software-defined automation technologies for mission-critical workloads went mainstream. Beyond virtualization of workstations and servers, the introduction of virtualized controllers deployed on high-performance computer platforms represents a huge opportunity to deliver on the promise of flexible manufacturing. Edge technologies expanded on this theme as installations of platforms that support both real-time and optimization workloads demonstrate clear and measurable value.
Q: How are manufacturers balancing automation investments with economic uncertainty?
Cody Bann and John Oskin: Currently, industries are facing economic uncertainties and manufacturers are no exception. Our processing clients are challenged with increased costs for raw materials. To help offset these expenses and improve productivity, companies are implementing digital transformation initiatives, which can improve plant performance by as much as 10% to 20%.
Significant labor and skills gap issues, lingering supply chain challenges and the current economic uncertainty can be daunting. However, evaluating the strategic plan and shifting it with the business environment is critical to meeting goals. Two key questions leadership should ask: Did we keep up with technology? Did we invest in the right equipment?
We, along with our systems integrator partners, are reiterating to our manufacturing clients the tremendous benefits of how upgraded technology will increase efficiencies, improve quality control and that a better working environment with a more modern facility helps retain younger workers. A modernized plant also allows companies to tap into new business models, including customization and on-demand manufacturing.
Sean Saul: Automation continues to be one of the highest return-on-investment (ROI) levers for manufacturers to increase productivity. Amid growing economic uncertainty, there’s been an increased emphasis on how quickly automation investments pay back, driving demand for software solutions that deliver faster time to value.
Heath Stephens: Many manufacturers have postponed investments until they better understand future economic conditions. Obviously, this is a broad generalization. There are still thriving industries and businesses in more challenging sectors with well-defined market niche and a robust outlook. However, we have seen quite a few clients notice their market outlooks sour or become unclear, leading to postponed investments. This makes sense in some cases, but in others, clients are missing out on unrealized operational savings that could generate funds for them in 2026 and beyond. Companies should take a closer look at their automation investments. If they are unsure of the original plan, take a step back. Does it make sense to do a partial project with a decision on just the larger scope held back? Should the planned investment be shelved in favor of an alternative investment? For example, maybe the rate improvement effort isn’t needed yet, but improvements in first-pass quality and improved reliability are still beneficial.
Geert van der Zalm: Automating processes is essential to stay competitive in the market. It unlocks levels of efficiency and productivity that manual processes will never be able to reach. As consumer demands continue to rise, automation will be the key to increasing throughput with accuracy and consistency. Automation doesn’t have to be zero to 60 though. Companies can opt to adopt automation slower, perhaps moving from manual to semi-automated before taking the plunge to full automated processes. This slower shift provides the opportunity for companies to establish an ROI for the change and make the case to continue the automation journey.
Q: Which industries are currently leading in plant automation adoption?
Geert van der Zalm: We’re seeing a big push for automation in the automotive industry. Automotive, battery and medical manufacturers must increase throughput on key assembly processes to keep up with consumer demands. As we enter 2026, we expect other industries to follow suit as the need for greater efficiency is required to stay competitive in the market.
Q: How is AI being applied to plant-floor operations today?
Sean Saul: AI continues to evolve in the traditional areas of strength like advanced process control and equipment health. New advancements in models and supporting frameworks are increasing the accuracy and long-term sustainability of these techniques. The emerging segment for generative AI on the plant floor is the use of natural language advisors to upskill personnel in context and real-time, increasing situational awareness and delivering expert guidance where it matters most.
Q: What role does machine vision play in quality assurance and defect detection?
Steve Keeney: Our onsite machine vision system deployments have become the cornerstone of our customers’ modern quality assurance by bringing speed, accuracy and consistency to the inspection process. By using high-resolution cameras and intelligent software, these systems scan every product in real time to catch defects like scratches, misalignments or incorrect labels that human eyes might miss. Unlike manual inspection, machine vision applies the same objective criteria to every part, reducing variability and eliminating fatigue-related errors. One thing machine vision users learn quickly is that these systems provide instant feedback when issues arise and collect valuable data to improve processes over time. This combination of reliable detection, actionable insights and traceability helps manufacturers reduce waste, ensure compliance and deliver the quality level that today’s customers expect.
Heath Stephens: Machine vision is an incredibly powerful tool in quality assurance and defect detection. Modern systems can run at very high image processing rates, relying not just on visible wavelengths but also on UV, Infrared and X-ray images. Sonar and other synthetic imaging technologies can also be used. It’s also easier to integrate these technologies into cloud platforms for further analysis, record retention, etc.
Q: How is generative AI influencing engineering and automation design processes?
Sean Saul: Engineering functions are being transformed by the power of large language models as they have proven very adept at structured text translation, like control narratives to code and one code to another. When combined with process and domain expertise, this capability can dramatically boost engineering productivity.
Computer vision is also being used to directly digitize and create operator graphics from P&IDs and when combined with advanced operator display knowledge, this approach can automatically generate graphics in a fraction of the time compared to the traditional methods. Generative AI can also aid value engineering when integrated with 3D conceptual design tools, as an example by automatically optimizing piping layout based on economics and physical constraints.
Q: How are robotics being used beyond material handling and assembly in 2025?
Geert van der Zalm: Cobots are being used for a wider range of industrial applications than ever, especially with the introduction of 7-axis robots, which offers an extra degree of freedom from traditional 6-axis cobots. Through our subsidiary, Kassow Robots, we’re seeing cobots being used outside of more well-known applications like palletizing and pick and place and being implemented for welding, CNC machine tending and quality inspection applications.
Q: What progress has been made in predictive maintenance and condition monitoring?
Heath Stephens: Predictive maintenance and condition monitoring tools have been around for a while and the core mathematics behind the scenes is well-established. However, there continue to be new improvements in usability and pricing that make these tools more accessible and practical than ever before. Whether you need an edge computing solution, server-based system or a hybrid cloud platform, predictive maintenance tools can help you optimize the impact of your maintenance workforce. No one has unlimited maintenance budgets and a production line under maintenance isn’t usually functional for production. Predictive maintenance tools can help make sure maintenance is both timely and effective.
Sean McGowen: Advances in sensors are giving us more data points to measure in increasingly convenient packages. Manufacturers are adding extra axes of vibration analysis to sensors, combining multiple sensors into one housing for ease of installation and having all this recorded data in a user-friendly, customizable and easily translatable user interface. The easier a program is to use, the more likely it will be continued. This simplicity is encouraging more companies to invest in and utilize these technologies.
Q: How are plants using digital twins in daily operations?
Sean Saul: Digital twins are increasingly becoming the foundation of robust optimization programs. Traditionally used to emulate control system functions and validate changes to control schemes or logic, their integration with high-fidelity models and training software now enables a seamless, safe environment for deploying optimization techniques, measuring impact and smoothly embedding improvements into ongoing operations.
Cody Bann and John Oskin: Digital twin technology models production lines and combines with real-time data collection to monitor processes, detect downtime and predict performance, helping manufacturers identify root causes of problems and improve efficiency.
Digital twin technology provides a live visual representation of production lines, highlighting issues like machine failures or bottlenecks with machine state and process and linked process flow to show fault propagation. Digital twins deliver an up-to-date digital record of physical assets so engineers and plant managers can quickly identify key factors that foreshadow the need for preventative repairs or maintenance. This technology can be used to optimize tool calibration, load levels and even cycle times, allowing companies to increase their operational efficiency while significantly reducing costly downtime or equipment malfunctions.
What makes ABLE so powerful is its ability to integrate real-time IoT edge data into business systems such as manufacturing execution system (MES), supervisory control and data acquisition system (SCADA) and enterprise resource planning systems (ERPs). This integration helps speed up the process of Production Line Modeling by reducing the need for manual tagging by more than 80%.
By leveraging this digital twin technology, manufacturers have access to sophisticated analytics that can be visualized on shop floor HMIs. This helps provide insight into how processes are always working, making it easier to diagnose problems before they become major issues and identify process improvements that could lead to greater product line efficiency.
Digital twin technology supports data validation, accurate calculation of key performance indicators (KPIs) like mean-time-between-fail (MTBF) and mean-time-to-repair (MTTR) and provides insights from the plant floor to the executive level, driving them toward a smart factory and Industry 4.0 goals.
Geert van der Zalm: Process simulation software such as Visual Components enables manufacturers to test a design via simulation and adjust before implementing. When working in conjunction with robust design software, this helps simplify the automation process from initial design to simulation to final system and helps ensure daily operations run smoothly once a new system is implemented.
Q: How are manufacturers reskilling workers to work alongside automation?
Geert van der Zalm: With automation, manufacturers can focus on training their employees to optimize machine productivity and gain additional skills to keep machine uptime.
Q: Are manufacturers seeing measurable ROI from automation upgrades in 2025?
Sean McGowen: Manufacturers who have implemented sizable automation upgrades are seeing ROI in the form of labor savings. Multiple manufacturers we have worked with shared this same experience with us. Some simply look at this labor reduction as a cost savings, while others reallocate the labor saved to more important or crucial tasks. While each company utilizes this labor savings differently, there is a measurable return from these projects.
Cody Bann and John Oskin: The short answer is yes and here’s why. By deploying advanced technologies, manufacturing plants can accelerate and drive overall equipment effectiveness uplift, avoid problems before they occur and reduce engineering time by up 70%. We regularly benchmark performance using real-time data. Last year one of our studies revealed that for a $1 billion company, every one percent improvement in overall equipment effectiveness –– like integrating advanced software that reduces equipment downtime –– is worth approximately $7 million annually.
When manufacturers integrate a manufacturing execution system (MES) it provides real-time visibility across all levels of production. These systems monitor work steps ranging from equipment, materials, data collection and both automated and manual processes –– continuously making sure that people and equipment are operating according to policies. MES technology gives organizations the ability to take responsive action when it comes to data-driven events occurring on the production chain. Unfortunately, because it’s a steep hill to climb, not every manufacturing plant implements MES. High implementation and operational costs, complexity and inflexibility mean that some facilities are unable to take advantage of the powerful MES systems out there.
However, third-party MES accelerators support and complement this market by providing a solution that is fast to deploy, simple to configure, easy to use and cost-effective for all lines and sites. Organizations can realize quicker ROI as they work towards a complete MES solution. Manufacturing teams can bypass lengthy development efforts and get an intuitive solution running in days instead of months.
Q: How are automation vendors responding to the need for more flexible production lines?
Geert van der Zalm: Modular components that enable the greatest possible degrees of freedom when it comes to layout planning and use of space. An example of this in the industry is our conveyance line, which features a robust portfolio of components that can be adjusted to the requirements of a diverse range of industries. This flexibility is key to ensuring an efficient and economical conveyance solution for every application.
Steve Keeney: We work with many automation suppliers and see a shift from rigid, single-purpose systems to modular robotics, collaborative robots and adaptable control platforms that can be reconfigured quickly as production needs change. This is true especially for high-mix, lower-volume applications, which are becoming more prevalent today. Under the umbrella of artificial intelligence (AI), deep learning machine vision systems now let equipment recognize and adjust to different parts on the fly, which is important for those high-mix, lower-volume needs. We have deployed the use of digital twins and simulation tools that allow teams to model and test changes virtually before making them on the floor. Together, these technologies are helping manufacturers build production lines that adapt faster, reduce downtime and stay competitive in fast-changing markets.
