The International Society of Automation (ISA) has released a comprehensive position paper examining how artificial intelligence is fundamentally reshaping industrial automation. Published in November 2025, the document highlights AI's dramatic evolution from early expert systems to today's sophisticated generative AI technologies that are accelerating advancements in robotics, predictive maintenance, and digital twin technology.

Key Finding

Industrial AI has transitioned from rule-based expert systems to data-driven generative models, enabling unprecedented automation capabilities across manufacturing facilities and industrial operations.

AI's Revolutionary Impact on Industrial Operations

According to the ISA position paper, modern industrial AI brings operational benefits that were unimaginable just five years ago. The technology is advancing inspection and quality control processes, transforming maintenance from reactive to predictive, and enabling sophisticated vision-language-action models for industrial robotics.

The paper specifically highlights developments in data capture and analysis that are creating safer, more efficient plants. These advances represent a fundamental shift from traditional automation approaches to intelligent systems capable of autonomous decision-making.

Robotics and Vision-Language-Action Models

One of the most significant developments outlined in the position paper is the emergence of vision-language-action (VLA) models in industrial robotics. These systems combine computer vision, natural language processing, and robotic control to create robots that can understand complex instructions, assess visual environments, and execute precise actions.

"AI is bringing operational benefits including advancements in inspection, quality control and maintenance, as well as vision-language-action models for robotics and developments in data capture and analysis for safer, more efficient plants."

Digital Twins and Real-Time Optimization

The ISA paper emphasizes how AI-powered digital twins are revolutionizing industrial operations. These virtual representations of physical systems use real-time data and machine learning algorithms to predict equipment behavior, optimize processes, and prevent costly downtime.

Real-time optimization capabilities enabled by AI are allowing manufacturing facilities to adjust operations dynamically based on changing conditions, demand fluctuations, and equipment performance. This represents a significant advance over traditional static automation systems.

Predictive Maintenance Revolution

Traditional maintenance schedules are being replaced by AI-driven predictive systems that can anticipate equipment failures before they occur. The position paper notes that these systems analyze vast amounts of sensor data, historical performance patterns, and environmental factors to optimize maintenance timing and reduce unexpected downtime.

Industry Standards and Implementation Challenges

As a leading automation standards organization, ISA's position paper also addresses the critical need for industry standards as AI technologies become more prevalent in industrial settings. The organization emphasizes the importance of establishing clear guidelines for AI implementation, safety protocols, and integration with existing industrial systems.

Implementation Focus Areas

  • Safety protocols for AI-driven industrial systems
  • Standardization of AI integration procedures
  • Data security and cybersecurity measures
  • Training and workforce development programs
  • Quality assurance and validation processes

Workforce Implications and Skills Development

The position paper acknowledges the significant workforce implications of advanced industrial AI. While these technologies are creating new opportunities for skilled technicians and engineers, they also require substantial retraining and upskilling initiatives.

ISA emphasizes that successful AI implementation in industrial settings requires a workforce capable of working alongside intelligent systems, understanding their capabilities and limitations, and maintaining oversight of automated processes.

Future Outlook

Looking ahead, the ISA position paper projects continued acceleration in industrial AI adoption. The organization expects to see more sophisticated AI systems capable of handling complex industrial processes with minimal human intervention, while maintaining the safety and reliability standards required in industrial environments.

The paper concludes that organizations that fail to adapt to AI-enhanced automation risk falling behind competitors who embrace these transformative technologies, making strategic AI adoption critical for industrial competitiveness in 2025 and beyond.

Read the original ISA position paper →