Actual causality in fault trees

In critical systems engineering, fault trees have been the preferred tool for decades to model risks and answer the question 'what can go wrong?' through minimal cut set analysis. However, a novel approach based on Halpern & Pearl's actual causality theory allows going one step further: precisely determining 'why did it actually fail?', transforming fault diagnosis into a logical and reproducible process. This paradigm shift is especially relevant in environments where multiple variables and dependencies converge, such as automated industrial facilities or cloud infrastructures. The complete classification of the different notions of actual causality based on the graph structure and the logic of the fault tree not only provides mathematical rigor but also lays the foundation for implementing automatic diagnostic systems capable of identifying the root cause of an incident in real time. In this context, companies that develop custom applications can integrate these causal models into monitoring platforms, connecting them with AWS and Azure cloud services to process large volumes of operational data. Furthermore, the incorporation of artificial intelligence and AI agents allows those same fault trees to evolve dynamically, learning from previous incidents and improving diagnostic accuracy. At Q2BSTUDIO we offer AI solutions for businesses that, combined with business intelligence services and Power BI, facilitate the visualization of causal relationships and evidence-based decision-making. Cybersecurity also benefits from this approach: by applying actual causality analysis to a system's fault trees, it is possible to trace the origin of a breach or anomaly with greater accuracy, reducing response time. Ultimately, the fusion of causal theory with reliability engineering opens a new dimension for custom software aimed at predictive maintenance and operational resilience. The challenge now lies in translating these academic concepts into practical solutions that organizations can adopt seamlessly, and that is where software development expertise and the ability to integrate technologies such as intelligent agents make the difference.