LLMs and Generative AI in the enterprise.
Inspire, develop, and guide a winning organization.
Understand the unique values and behaviors of a successful organization.
Create visible workflows to achieve well-architected software.
Understand and use meaningful data to measure success.
Integrate and automate quality, security, and compliance into daily work.
An on-demand learning experience from the people who brought you The Phoenix Project, Team Topologies, Accelerate, and more.
Learn how to enhance collaboration and performance in large-scale organizations through Flow Engineering
Learn how making work visible, value stream management, and flow metrics can affect change in your organization.
Clarify team interactions for fast flow using simple sense-making approaches and tools.
Multiple award-winning CTO, researcher, and bestselling author Gene Kim hosts enterprise technology and business leaders.
In the first part of this two-part episode of The Idealcast, Gene Kim speaks with Dr. Ron Westrum, Emeritus Professor of Sociology at Eastern Michigan University.
In the first episode of Season 2 of The Idealcast, Gene Kim speaks with Admiral John Richardson, who served as Chief of Naval Operations for four years.
Exploring the impact of GenAI in our organizations & creating business impact through technology leadership.
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Leaders can help their organizations move from the danger zone to the winning zone by changing how they wire their organization’s social circuitry.
The values and philosophies that frame the processes, procedures, and practices of DevOps.
This post presents the four key metrics to measure software delivery performance.
April 3, 2025
Organizations building complex cyber-physical systems face mounting pressure to innovate faster while maintaining reliability, safety, and efficiency. A new paper, “AI and Industrial DevOps for Teams” from IT Revolution’s Spring 2025 Enterprise Technology Leadership Journal, offers a compelling vision for how artificial intelligence can transform the way teams develop and operate these mission-critical systems.
Written by industry veterans Debbie Brey, Jennifer Fawcett, Dr. Suzette Johnson, and Robin Yeman, this paper provides a roadmap for technical leaders seeking to leverage AI as a force multiplier within their teams.
The paper’s central thesis is that AI, particularly large language models (LLMs), can significantly enhance the application of Industrial DevOps principles to the development of cyber-physical systems. These systems—which include everything from autonomous vehicles and spacecraft to smart infrastructure and medical devices—are increasingly complex, with sophisticated interactions between hardware, software, and human operators.
Industrial DevOps, an approach that applies Agile, Lean, and DevOps principles to cyber-physical systems, provides a framework for managing this complexity. The authors demonstrate how AI can strengthen each of the nine Industrial DevOps principles, from organizing around value flow to adopting a growth mindset.
One of the paper’s most striking insights is its reconceptualization of AI from passive tool to active collaborator. The authors present an AI-enabled operating model where AI serves as an intelligent partner that enhances human capabilities rather than replacing them.
“AI is more than a tool,” the authors argue. “It now acts as a collaborative entity, providing guidance and suggestions and augmenting human creativity across the value stream, but it still requires human oversight in critical decision-making areas.”
This human-AI collaboration is particularly evident in hypothesis-driven development, where AI can help generate and test hypotheses about system behavior, analyze vast datasets to identify patterns, and propose potential solutions—essentially functioning as a co-researcher alongside human teams.
The paper doesn’t just deal in theoretical constructs; it offers concrete examples of how teams across different disciplines can leverage AI to improve their workflows:
The paper grounds its arguments in real-world scenarios across various industries:
These examples illustrate how organizations are already realizing tangible benefits from AI integration, from improved operational efficiency to enhanced decision-making and innovation.
The authors emphasize that as AI becomes more integral to cyber-physical systems, responsible AI practices are essential. This means ensuring fairness, transparency, and accountability in AI systems—particularly in safety-critical applications.
For autonomous systems making high-stakes decisions, the paper stresses the importance of aligning AI decision-making with societal values and legal frameworks, maintaining human oversight, and implementing robust security measures to protect against tampering or malicious interference.
Looking ahead, the authors envision AI’s role in cyber-physical systems continuing to grow, with advancements ranging from enhanced real-time decision-making to the emergence of autonomous, self-healing systems that optimize industrial operations.
They predict expanded AI applications in healthcare, smart infrastructure, and autonomous systems, increased adoption in military defense, revolutionary advances in space technology, and the evolution of frameworks for ethical AI that balance innovation with societal responsibilities.
The paper concludes with a pragmatic call to action for leaders:
“The question is no longer whether AI should be a part of your journey,” the authors conclude, “but rather how prepared you are to make it a reality and what are your next steps.”
For technical leaders overseeing the development and delivery of cyber-physical systems, this paper offers a comprehensive blueprint for integrating AI into their teams’ workflows. It provides both the strategic vision and tactical guidance needed to leverage AI effectively, responsibly, and in alignment with broader organizational goals.
The authors—all with extensive experience in aerospace, defense, and complex systems development—bring credibility and practical wisdom to their recommendations. Their collective expertise shines through in the paper’s nuanced understanding of both AI’s potential and the challenges of implementing it within industrial contexts.
Whether you’re leading teams developing autonomous vehicles, smart infrastructure, medical devices, or other complex systems, “AI and Industrial DevOps Teams” offers valuable insights that can help you improve operational efficiency, accelerate innovation, and maintain your competitive edge in an increasingly AI-driven landscape.
As we move into an era where “the speed of relevance defines success,” as the authors put it, this paper equips leaders with the knowledge and frameworks they need to integrate AI with purpose and precision, setting new standards for what’s possible in cyber-physical system development.
The full paper, published in the Spring 2025 edition of the Enterprise Technology Leadership Journal, is available as a free download from IT Revolution. For leaders navigating the intersection of AI, DevOps, and complex systems development, it’s essential reading that will shape how they think about and implement AI within their organizations.
Managing Editor at IT Revolution working on publishing books and guidance papers for the modern business leader. I also oversee the production of the IT Revolution blog, combining the best of responsible, human-centered content with the assistance of AI tools.
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