As process industries hurtle toward an AI-driven future, four powerful trends are set to redefine automation strategies in 2026: hyper automation, AI-first automation, low code/no code platforms, and advanced process intelligence. From unified platforms that blend AI, machine learning and robotic process automation (RPA) for end-to-end optimisation, to AI-driven self-healing operations, citizen developer tools and predictive process intelligence, these trends provide a lens into what industry can expect from process automation in 2026.
Hyper automation: A new era of integration
Leading industrial organisations are increasingly incorporating hyper automation into their 2026 strategies. This integration of AI, machine learning and RPA into unified platforms provides end-to-end process optimisation, particularly in complex industrial environments. By implementing platforms like AVEVA Unified Operations Centre and UiPath Hyper automation, organisations are achieving greater visibility and control across their operational technology (OT), information technology (IT) and business workflows.
The trend towards agentic AI and autonomous operations is also gaining traction. AI agents embedded in industrial software can take over automated tasks such as dashboard creation, alarm management and predictive analytics. Cloud-native copilots, such as Microsoft Azure Copilot, facilitate lifecycle governance and optimisation of automation agents, creating an environment where real-time decision making and closed-loop optimisation are achievable.
Furthermore, improved process intelligence is enabling organisations to identify bottlenecks more effectively, generating automation-ready workflows through process mining and modelling tools. By integrating with manufacturing execution systems, computerised maintenance management systems and asset performance management systems, organisations can achieve real-time execution and create feedback loops that inform continuous improvement. The results are striking. Documented benefits include up to a 27% reduction in downtime, 10-30% cost savings, and significant gains from predictive maintenance and enterprise visibility.
Autonomous operations on the horizon
The shift towards AI-first automation marks a significant change in how organisations are approaching operational processes. In 2026, businesses will increasingly rely on AI systems to automate tasks and predict potential issues and respond automatically. Through predictive issue detection, AI-driven platforms will analyse real-time and historical data from IT systems, OT assets and IoT sensors, allowing organisations to anticipate failures and intervene proactively.
Automated responses and closed-loop control mechanisms enabled by AI will further facilitate operational continuity. Businesses will implement AI-driven platforms that ensure dynamic load balancing, auto-scaling and real-time parameter adjustments without human intervention, minimising mean time to repair.
The implementation of self-healing infrastructure will elevate AI-first automation to a new level. AIOps and agentic AI will empower IT and OT systems to self-repair, autonomously addressing issues such as restarting failing services, patching vulnerabilities and resolving configuration drift. For manufacturing operations, this means adopting technologies that can automatically recover and optimise processes, enhancing overall efficiency.
Low code/no code platforms: Empowering citizen developers
In the automation landscape of 2026, low-code/no-code (LCNC) platforms will play an essential role by empowering non-technical users to develop and deploy automations without deep coding knowledge. These tools are now positioned as fundamental components in digital transformation frameworks, particularly across industries like manufacturing, utilities and mining.
By providing visual drag-and-drop interfaces and pre-built templates, LCNC platforms will enable business users from diverse departments such as operations, HR, finance and marketing to automate repetitive tasks and prototype applications independently. The democratisation of development opens the door for citizen developers to innovate, bridging IT skill gaps, and reducing reliance on specialist developers.
Gartner forecasts that by 2026, over 80% of new digital initiatives will leverage LCNC platforms, with a substantial portion of automation drivers emerging from user departments rather than traditional IT settings. This shift not only accelerates digital transformation, but also fosters a culture of continuous improvement through rapid iteration and scaling.
Evolving to meet future demands
Process intelligence is evolving beyond traditional process mining and becoming integral to AI-driven strategies. In 2026, organisations will leverage real-time analytics from various operational and business systems, moving from historical data analysis to predictive insights. This evolution will enable businesses to not just ask “What happened?” but also “What will happen?” and “What should we do next?”
AI-powered analytics will allow leaders to anticipate equipment failures, detect process deviations and provide actionable recommendations. By leveraging digital twins, organisations can simulate what-if scenarios and optimise decision making. This proactive approach not only reduces waste and improves operational efficiency, but also aligns with sustainability goals, making process intelligence a strategic imperative for the future.
The road ahead
These four trends: hyper automation, AI-first automation, low-code/no-code platforms, and process intelligence will profoundly shape the broader landscape of process automation in 2026. Organisations that harness these innovations will not only improve operational efficiencies, but also enhance decision making and agility, ensuring they remain competitive in an increasingly dynamic market.
The convergence of these technologies will create a cohesive ecosystem where automation is not only faster, but also smarter and more responsive to real-time needs. By embracing these trends, businesses will empower their workforce, streamline processes and achieve sustainability goals while positioning themselves as leaders in their respective industries. The result will be a renaissance in process automation that drives significant value creation and sets new standards for operational excellence.
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