# Industrial AI Adoption Highlights Need for Responsible Governance and Standards > As industrial AI evolves, the stakes rise for responsible deployment. Arti Garg from AVEVA advocates for a framework that ensures safety and human oversight amidst the growing autonomy of these technologies. **Source**: technologyreview.com | **Published**: 2026-10-08 | **Type**: article ## Key Facts - Industrial AI adoption surged by 78% in 2 years, indicating rapid market evolution and urgency. - AVEVA emphasizes responsible AI governance, revealing potential competitive advantages in safety. - Autonomous systems could replace retiring workforce expertise, highlighting a strategic labor shift. - AI's role in managing renewable energy grids shows financial benefits in sustainability and efficiency. - Lack of standards for AI's environmental impact poses risks, indicating a vulnerability in regulatory compliance. ## Summary Industrial AI is poised for a transformative leap as it integrates more deeply into physical environments, driven by advancements in foundation models and agentic AI. This evolution is significant because it enables automation of complex tasks that directly interact with critical infrastructure, where errors can lead to safety and operational failures. Arti Garg, chief technologist at AVEVA, highlights the urgency of deploying these technologies responsibly, emphasizing the need for robust governance, human oversight, and a focus on safety. The industrial sector has seen a marked increase in AI adoption, with some estimates indicating a 78% rise in the past two years. This shift reflects a growing recognition of AI's potential to enhance operational efficiency, particularly in high-stakes environments where precision is paramount. However, the integration of AI into these settings introduces unique challenges. Unlike purely digital applications, industrial AI must navigate the complexities of physical systems, where unexpected decisions can have dire consequences. Data management is critical in this context. Industrial systems generate vast amounts of information from various sources, including telemetry and service logs. Leveraging advanced technologies to correlate and analyze this data in real-time can significantly enhance decision-making processes. For instance, AI-powered robots can operate in hazardous environments, gathering data without putting human workers at risk. This capability not only improves safety but also increases operational efficiency. Governance frameworks for AI deployment are evolving. AVEVA advocates for a model that emphasizes security, efficiency, and human oversight. Garg asserts that AI should augment human decision-making rather than replace it, ensuring that critical operations remain under human control. This approach is particularly vital as AI systems become more capable yet less predictable, necessitating clear guidelines on where automation can be applied safely. Sustainability is another key consideration in the deployment of industrial AI. As organizations increasingly rely on renewable energy sources, AI can play a crucial role in managing complex power systems. However, the environmental impact of AI itself also requires scrutiny. Garg is actively involved in developing standards for measuring the environmental footprint of AI technologies, addressing concerns about resource consumption and carbon emissions associated with AI operations. The future of industrial AI holds significant promise, with potential applications ranging from autonomous robots to AI-assisted development tools. However, realizing this potential will require a comprehensive reevaluation of business processes and governance structures. Organizations must ensure that experienced workers can leverage their expertise in conjunction with AI, fostering a collaborative environment that enhances both safety and productivity. As the industrial workforce faces a significant demographic shift, with nearly half expected to retire in the next five years, the urgency for knowledge transfer becomes paramount. AI can help capture and disseminate the expertise of seasoned workers, facilitating smoother transitions for newer employees. This capability not only preserves institutional knowledge but also enhances operational resilience as industries adapt to changing workforce dynamics. Looking ahead, the trajectory of industrial AI suggests a dual focus on enhancing operational efficiency and maintaining safety. Companies that prioritize responsible AI deployment will likely gain a competitive edge, as they navigate the complexities of integrating advanced technologies into their operations. The emphasis on sustainability and governance will shape industry standards, compelling organizations to adopt practices that ensure both technological advancement and environmental stewardship. As the market evolves, leaders must remain vigilant, adapting their strategies to harness the full potential of industrial AI while safeguarding human oversight and ethical considerations. ## Entities - **Companies**: AVEVA - **Technologies**: AI, foundation models, physical AI, agentic AI - **People**: Arti Garg, Megan Tatum - **Organizations**: IEEE ## Key Concepts responsible AI, autonomous systems, human oversight, data governance, sustainability, industrial automation, environmental impact of AI, operational efficiency ## Definitions - **responsible AI**: A framework emphasizing security, efficiency, and human safety in AI deployment, ensuring human oversight remains central. - **foundation models**: General purpose AI models that enable broader access to advanced AI technologies across various applications. - **physical AI**: AI systems that interact directly with physical environments, enhancing automation in industrial settings. - **agentic AI**: AI that allows for automation at the software level, enabling systems to operate more autonomously. - **sustainability in AI**: The consideration of AI's environmental footprint, including energy and resource consumption. ## Use Cases - AI-powered robots gathering data in hazardous environments - AI for managing complex power systems with renewable energy - AI-assisted coding for building new applications - real-time diagnostics using AI to correlate disparate data - enhancing operational efficiencies in industrial settings - developing standards for measuring AI's environmental impact ## Frequently Asked Questions **What is responsible AI?** Responsible AI refers to a framework that prioritizes security, efficiency, and human safety in AI applications. It ensures that human oversight is maintained, particularly in critical decision-making processes. **How does AVEVA approach AI governance?** AVEVA employs a multi-layered governance approach that encompasses both internal AI usage and the deployment of AI in products. This framework emphasizes human judgment and ethics as core principles. **What are the risks of deploying AI in industrial settings?** The primary risks involve the interaction with physical systems that can have significant safety implications. Unpredictable AI behavior in these environments necessitates careful consideration and governance. **How can AI contribute to sustainability in industrial processes?** AI can enhance the management of power systems, particularly with the integration of renewable energy sources. It also helps organizations understand and reduce their own environmental footprint. **What is the role of human oversight in autonomous systems?** Human oversight is crucial in autonomous systems to ensure accountability and safety. Organizations must establish guardrails to define the boundaries of automation and maintain human involvement in critical decision loops. ## Links - [Read on Welcome.AI](https://welcome.ai/content/industrial-ai-adoption-highlights-need-for-responsible-governance-and-standards) - [Original source](https://www.technologyreview.com/2026/10/08/1144020/building-a-safer-path-to-autonomous-industrial-ai/) - [AVEVA](https://welcome.ai/company/aveva): Featured company --- Source: Welcome.AI | https://welcome.ai/content/industrial-ai-adoption-highlights-need-for-responsible-governance-and-standards