Executive Summary
The industrial automation landscape is undergoing a fundamental transformation as two powerful technological currents converge: Edge Artificial Intelligence (AI) and integrated functional safety. This convergence is redefining how manufacturing systems are designed, operated, and maintained, enabling unprecedented levels of productivity, reliability, and operator protection. Recent announcements from leading automation providers—including ABB’s Automation Extended program and Festo’s latest servo drive—demonstrate how these technologies are moving from experimental concepts to mainstream industrial solutions.
ABB Automation Extended: Modernization Without Disruption
On February 2, 2026, ABB announced its Automation Extended program, a strategic evolution of its distributed control systems (DCS) designed to help industries modernize critical infrastructure without operational disruption. Building on ABB’s extensive installed base and process automation expertise, the program outlines how future automation capabilities can be introduced progressively while preserving system integrity.
Key Technical Features
The Automation Extended architecture employs a separation-of-concerns principle, creating two distinct yet securely interconnected environments:
- Control Environment: A software-defined domain ensuring robust, reliable, and deterministic control for critical processes
- Digital Environment: Securely connected to the control layer, enabling advanced applications, edge intelligence, and real-time analytics
This approach enables industries to leverage AI and machine learning for decision support without compromising established control structures. The system supports integration with existing ABB platforms including ABB Ability™ System 800xA®, ABB Ability™ Symphony® Plus, and ABB Freelance systems, providing a structured, low-risk path to modernization.
Peter Terwiesch, President of ABB’s Automation business area, emphasized the practical value: “In industries we serve—many operating large and complex infrastructures that deliver essential resources—our customers rely on modernization without disruption. Automation Extended delivers exactly that: bringing future-ready capabilities into the systems they know and trust, with security and interoperability at the core.”
Festo’s Safety-Integrated Servo Drive: Compact Protection
Festo has expanded its electric automation portfolio with the CMMT-AS-MP-S3 servo drive, introduced on January 29, 2026. This solution integrates high-performance motion control with extended functional safety features in a single compact device, addressing the growing demand for safety-critical automation applications.
Safety Capabilities and Compliance
The CMMT-AS-MP-S3 supports safety levels up to Performance Level e (PL e), SIL 3, and Categories 3 and 4—aligning with the highest requirements for machinery safety. Integrated safety functions include:
- Safe Torque Off (STO)
- Safe Brake Control (SBC)
- Safe Stop 1 and 2 (SS1, SS2)
- Safe Operating Stop (SOS)
- Safe Maximum Speed (SMS)
- Safely Limited Speed (SLS)
By combining motion control and safety functions in one unit, the drive eliminates the need for external safety modules or additional wiring, reducing system complexity, cabinet space requirements, and overall integration effort. The drive covers a power range from 300 W to 12 kW, supporting diverse machine sizes and duty profiles across assembly systems, packaging machinery, and electronics manufacturing equipment.
Engineering Efficiency
Safety parameters can be configured directly on the device without software for basic applications, while complex setups can leverage the Festo Automation Suite (FAS). This graphical interface provides guided workflows for safety setup, validation, commissioning, diagnostics, and firmware updates, with preset parameter values and validation routines designed to reduce commissioning time and configuration errors.
Ben Lloyd, Product Manager for Electric Automation at Festo, explained the design philosophy: “We’ve packaged everything into a compact servo drive that requires no additional wiring or modules, delivering space and cost savings while meeting the highest standards of functional safety.”
Edge AI in PLCs: From Logic Execution to Intelligent Decision-Making
The traditional Programmable Logic Controller (PLC) is evolving from a dedicated logic executor to a sophisticated edge computing hub. This transformation addresses what industry analysts term the “Latency Problem”—the critical delays that occur when data must travel to remote cloud servers for processing before returning to the factory floor.
Technical Evolution
Modern PLCs now feature multi-core processors and support for high-level programming languages like Python and C++ alongside standard IEC 61131-3 languages. This enables engineers to run lightweight Machine Learning (ML) models directly on controllers, allowing simultaneous execution of deterministic control tasks and probabilistic analytical functions.
A practical example illustrates this capability: a PLC can now control a servo motor (deterministic task) while simultaneously analyzing the motor’s torque curve for anomalies (probabilistic task) without requiring external hardware. This dual functionality enables true predictive maintenance, where embedded ML algorithms can detect specific frequency signatures of developing equipment failures weeks before catastrophic failure occurs.
Implementation Strategies
Organizations are adopting several approaches to integrate Edge AI:
- Gateway Approach: Installing Edge Gateway devices between legacy PLCs and the network, allowing AI processing without complete hardware replacement
- Edge Controllers: High-end devices combining traditional PLC functionality with general-purpose computing power, often running Linux for data analysis and cloud connectivity
- Hybrid Architectures: Combining cloud analytics for long-term trend analysis with edge processing for real-time decision-making
The transition requires bridging the traditional divide between Information Technology (IT) and Operational Technology (OT). Data scientists typically work with Python and cloud environments, while control engineers specialize in Ladder Logic and proprietary systems. Successful organizations are increasingly adopting “No-Code” or “Low-Code” AI platforms that allow OT engineers to deploy pre-trained models onto PLCs without extensive data science expertise.
Market Outlook and Growth Projections
The convergence of Edge AI and safety integration is driving substantial market growth across industrial automation sectors. Recent research provides quantitative insights into this expansion:
PLC Market Expansion
According to a January 27, 2026 report from GlobeNewswire, the Global Programmable Logic Controller (PLC) Market is projected to expand from USD 14.74 billion in 2025 to USD 19.89 billion by 2031, achieving a compound annual growth rate (CAGR) of 5.12%. This growth is primarily fueled by:
- Rising demand for industrial automation in energy and automotive sectors
- Critical drive for operational efficiency to reduce manufacturing costs
- Increasing requirements for interconnected industrial ecosystems
Regional Dynamics
The Asia-Pacific region leads in both scale and momentum, with China and India’s subsidized capacity enhancements boosting demand for compact control units. Europe shows increasing demand for efficient energy management solutions, while North America prioritizes secure supply chains through infrastructural investments.
Investment Patterns
Rockwell Automation’s ’10th Annual State of Smart Manufacturing Report’ from June 2025 indicates that manufacturing organizations investing in generative and causal AI technologies increased by 12 percent year-over-year, reflecting a decisive move toward autonomous control strategies. Meanwhile, a 2025 Deloitte survey of 600 manufacturing executives found that 80% plan to invest 20% or more of their improvement budgets in smart manufacturing initiatives.
Technical Considerations and Implementation Challenges
While the benefits are substantial, organizations must navigate several technical and organizational challenges:
Hardware Requirements
Implementing Edge AI capabilities often requires hardware upgrades, as legacy controllers may lack the processing power, memory, or open protocols (such as MQTT or OPC UA) needed to run AI models and communicate with broader networks. Facilities frequently need to replace aging infrastructure with industrial automation components designed for high-speed data acquisition and connectivity.
Supply Chain Considerations
The global semiconductor shortage has made securing specific control modules challenging for many plants. Procurement teams increasingly rely on specialized distributors to navigate supply chain disruptions and source essential automation hardware efficiently.
Cybersecurity Implications
While Edge AI is generally considered more secure than cloud alternatives for operational data (since raw data never leaves the facility), endpoint security becomes critical once devices are connected to networks. Organizations must implement firewalls, disable unused ports, and ensure regular firmware updates to maintain security posture.
Application Scenarios and Industry Impact
The integration of Edge AI and safety functions is creating tangible value across multiple industrial sectors:
Automotive Manufacturing
Electric vehicle production lines leverage high-performance modular controllers to manage battery assembly and electric drivetrain production with extreme precision and speed. The International Energy Agency’s ‘Global EV Outlook 2024’ reported electric car sales reaching approximately 17 million in 2024, creating substantial demand for automated infrastructure capable of supporting this scale.
Electronics and Semiconductor Production
High-speed packaging lines and semiconductor fabrication processes benefit from millisecond-level latency enabled by Edge AI, preventing product damage and safety hazards that could result from cloud-based round-trip delays.
Food and Beverage Processing
Integrated safety systems in packaging machinery ensure operator protection while maintaining production efficiency, with solutions like Festo’s CMMT-AS-MP-S3 servo drive providing both safety certification and motion control in compact form factors.
Renewable Energy Systems
Solar power installations and wind farms utilize predictive maintenance algorithms running on edge controllers to detect equipment anomalies before they cause downtime, optimizing energy production and reducing maintenance costs.
Future Directions and Strategic Implications
Looking beyond 2026, several trends will shape the industrial automation landscape:
Software-Defined Automation
The market is experiencing a fundamental shift toward Software-Defined and Virtual PLC architectures, decoupling control software from proprietary hardware constraints. This trend facilitates greater scalability and interoperability under standards such as IEC 61499, allowing manufacturers to update logic remotely and reduce supply chain dependency on specific hardware components.
Workforce Transformation
Contrary to the misconception that automation replaces jobs, modern automation systems often enhance workforce capabilities. By automating repetitive, high-risk, or ergonomically challenging tasks, manufacturers improve workplace safety and employee satisfaction. Companies that invest in employee training alongside automation adoption report significantly lower turnover rates, as workers transition from manual operations to supervisory and analytical responsibilities.
Sustainability Integration
Advanced automation systems contribute to sustainability goals through optimized energy consumption, reduced material waste, and extended equipment lifespan. Predictive maintenance algorithms minimize unplanned downtime and resource consumption, while digital twin technology enables virtual testing and optimization before physical implementation.
Conclusion
The convergence of Edge AI and integrated safety represents a paradigm shift in industrial automation, moving beyond incremental improvements to fundamentally reimagined manufacturing systems. As demonstrated by recent announcements from industry leaders, these technologies are transitioning from experimental concepts to practical, scalable solutions delivering measurable business value.
For manufacturers, the strategic imperative is clear: embrace this convergence not as a collection of discrete technologies, but as an integrated approach to building intelligent, resilient, and safe production environments. The organizations that successfully navigate this transition will establish sustainable competitive advantages through enhanced productivity, reduced operational risk, and improved workforce capabilities.
As industrial operations continue to evolve in complexity and scale, the integration of intelligent edge computing with robust safety systems will form the foundation of next-generation manufacturing excellence—enabling industries to achieve new levels of performance while protecting both people and assets in increasingly dynamic production environments.
References
- ABB Automation Extended Press Release (2026-02-02). ABB introduces Automation Extended: enabling industrial innovation with continuity. Retrieved from https://new.abb.com/news/detail/133078/abb-introduces-automation-extended-enabling-industrial-innovation-with-continuity
- Festo CMMT-AS-MP-S3 Servo Drive Announcement (2026-01-29). Servo Drive with Integrated Extended Functional Safety. Retrieved from https://www.automation-mag.com/news/105898-servo-drive-with-integrated-extended-functional-safety
- Edge AI and PLCs Technical Analysis (2026-01-21). Edge AI and PLCs: The Future of Real-Time Industrial Decisions. Analytics Insight. Retrieved from https://www.analyticsinsight.net/automation/edge-ai-and-plcs-the-future-of-real-time-industrial-decisions
- PLC Market Research Report (2026-01-27). Programmable Logic Controller Research Report 2026 – Global Market Size, Share, Trends, Opportunities, and Forecasts. GlobeNewswire. Retrieved from https://www.globenewswire.com/de/news-release/2026/01/27/3226813/28124/en/Programmable-Logic-Controller-Research-Report-2026-Global-Market-Size-Share-Trends-Opportunities-and-Forecasts-2021-2025-2026-2031.html
- Deloitte Manufacturing Survey (2025). Smart Manufacturing Investment Trends. Deloitte Insights.
- Rockwell Automation State of Smart Manufacturing Report (2025). 10th Annual State of Smart Manufacturing Report. Rockwell Automation.
- International Energy Agency EV Outlook (2024). Global EV Outlook 2024. International Energy Agency.
- VDMA Robotics and Automation Statistics (2024). German Robotics and Automation Sector Forecast. VDMA.