Many organisations are investing in AI to automate complex workflows, but often encounter the same challenges: systems that are difficult to trust, hard to explain, and risky to operate at scale. In this joint talk, Marketer.com and Oxford Semantic Technologies show how a knowledge graph–driven approach helped turn fragmented marketing operations into a reliable, scalable system for growth. By creating a shared semantic layer across data and integrations, Marketer was able to improve transparency, accelerate decision-making, and safely automate complex processes. At the core of this approach is RDFox®, which uses incremental reasoning to generate “action plans” - validated, explainable representations of what the system can do next. This allows AI components to operate over clearly defined and trusted states, rather than relying on opaque decision-making. While the use case comes from marketing, the approach is broadly applicable. Inspired by infrastructure-as-code practices such as Terraform, it treats operational complexity as something that can be modelled, validated, and continuously improved - whether in data engineering, compliance, or system orchestration. We will share both the business impact and the technical foundations, including modelling patterns, rule-based reasoning, and real-time data integration using Linked Data Event Streams. We will also compare this approach with state-of-the-art LLM-based agent frameworks, highlighting trade-offs in reliability, transparency, and control. This session is designed for anyone looking to understand how knowledge graphs can enable trustworthy, production-grade AI systems.