2026 will reward manufacturers who connect the dots: modernize OT and data foundations, deploy agentic AI with strong governance frameworks, electrify strategically, and measure progress with capital and carbon efficiency in mind, writes Neil Smith, CPG President at Schneider Electric. Next year will be about freeing trapped value from legacy manufacturing constraints, compressing time-to-market, and reducing the cost of competitiveness.
1. CFOs will retire OEE to tackle multi-million legacy manufacturing costs
In 2026, profitability and efficiency will dominate manufacturing agendas and CFOs will work smarter on reducing operational expenses, imperative to maximising long-term growth and investment. A recent Omdia study uncovered that mid-sized manufacturers lose an average of $11 million (£8.2 million) every year (or 7.5% of revenue) to a ‘lock-in penalty’: inefficiencies, downtime, and compliance retrofits linked to closed, vendor-locked-in industrial ecosystems.
These costs are hard to spot, measure or manage unless we retire OEE (Overall Equipment Effectiveness). OEE can be misleading, as it only measures actual vs. planned utilisation. A 100% OEE for a production line that only runs once a week on a Monday doesn’t not mean you are running a capital efficient plant. Far from it. To make our industry more resilient and competitive, it’s time to introduce a Capital and Carbon Efficiency (CEE) metric that bridges operational, financial and sustainability goals.
Next year, CFOs will start to successfully tackle the productivity challenge by measuring what truly matters and pushing for more capital- and carbon-efficient industrial systems.
2. Agentic AI will redefine industrial intelligence, as human-in-the-loop push intensifies
In 2026, agentic AI will become a cornerstone of industrial innovation, transforming operations in both Life Sciences and Food & Beverage manufacturing. These systems, trained on sector-specific data, will proactively recommend actions such as cleaning-cycle optimisation to plant operators. They will test and correct code, helping engineers improve control, safety and batch logic during design and maintenance. Agentic AI will drive predictive maintenance, reducing downtime and improving efficiency. It has already started optimising production environments by regulating temperature and humidity, to name just a few, to support facility managers and ensure consistent product quality.
In F&B, solutions like ‘Golden Clean-in-Place’ can optimise cleaning cycles, reduce waste, cut chemical and water use – shortening cleaning cycles in the process. In Life Sciences, AI will continue accelerating drug development, while human oversight will remain essential to managing risk, bias, and explainability. As governance frameworks around ‘black box’ AI mature, with the EU AI Act coming into force on 2 August 2026, the push for transparent agentic AI will intensify to ensure AI remains a strategic enabler of resilience and growth.
3. Proprietary industrial data will take centre stage
In 2026, F&B manufacturers will harness real-time production data at the edge to deliver value, reduce waste, and optimise supply chains amid inflation and shifting consumer behaviour. Data control and access permissions can be designed to allow suppliers to analyse and provide inputs, delivering valued insights and action recommendations.
In Life Sciences, data integrity and traceability will become even more critical, as AI adoption moves from drug discovery to manufacturing. AI-driven digital twins and predictive modelling will be highly relevant for streamlining tech transfer from a manual, intensive process into a precision-driven workflow. The objective: compress time-to-market to maximise patent exclusivity windows for production, while preserving data integrity. With 95% of Life Sciences projects overrunning their target cost and schedule , and a six-month delay potentially eroding more than $750 million in net present value (NPV) , the opportunity presented by technology has never been more tangible. As a result, demand for vendor-neutral industrial platforms and software that accelerate technical data transfers from R&D to full-scale manufacturing will intensify.
4. Players will deploy intelligent industrial electrification strategies to protect margins
In 2026, intelligent process electrification and energy technologies will become a strategic priority for manufacturers seeking to cut emissions and control energy costs. With growing adoption of on-site renewable power generation and microgrids managed by intelligent systems, industrial players will be able to schedule production based on expected consumer demand patterns as well as forecasted energy price, availability or carbon mix. As energy volatility persists, companies will adopt phased and strategically planned electrification roadmaps. Those that allow them to ramp up production when low-carbon electricity is abundant, pause or export surplus energy when energy prices spike, turning energy agility into industrial resilience and margin protection.
5. Industrial hardware refresh cycles will accelerate to meet IIoT and AI demands
In 2026, we may enter a new investment cycle for industrial hardware replacement targeting business outcomes and the spotlighting the desire to modernize OT for embedded cybersecurity, sustainable efficiency, and readiness for autonomous operations. According to IDC’s 2024 Worldwide IT/OT Convergence Survey the average OT asset has been in service for 11 years, with 50% older than 11 years and 18% older than 16 years. These are likely to be replaced soon as they do not have key features of today’s modern hardware: embedded security and AI integration. Therefore, I believe next year, we’ll see industrial players prioritize modular, interoperable IIoT (Industrial Internet of Things) and production systems, as well as secure-by-design controllers. Upgrades will be most effective where legacy assets currently block real-time data, cybersecurity compliance, or closed-loop optimisation.
To conclude, 2026 will mark a turning point for industrial players who move beyond incremental fixes and embrace system-level change, measured through a Capital and Carbon Efficiency lens. Those who act now will not only protect margins but also secure a competitive edge in an increasingly volatile and complex global market.
Author biography:
Neil Smith leads Schneider Electric’s global team responsible for developing, marketing, and supporting its solutions portfolio for the Consumer Packaged Goods segment. He joined the group in 2014 following the acquisition of Invensys, where he later oversaw the business in Australia and New Zealand during its integration. He subsequently became Head of Process Automation for Schneider Electric’s Pacific Zone, expanded his remit to include the Industrial Software business, and was promoted to Senior Vice President of the Process Automation business in Asia Pacific.
