From automated fire strategy generation to predictive risk assessment, AI is poised to revolutionise fire engineering. We explore the opportunities, limitations, and ethical considerations.. AI Applications in Fire Engineering 1. Automated Code Compliance Checking AI tools can now scan building designs against Approved Document B requirements, flagging non compliance in minutes rather than days. 2. Predictive Fire Risk Assessment Machine learning models trained on historical fire data can predict building level fire risk scores, enabling targeted intervention. 3. CFD Acceleration AI assisted mesh generation and parameter optimisation can reduce CFD simulation times by 60 70% while maintaining accuracy. 4. Digital Twin Fire Simulation Real time digital twins integrating IoT sensor data with fire models can provide live fire risk monitoring and automated emergency response. 5. Evacuation Optimisation Agent based models using reinforcement learning can optimise evacuation strategies for complex buildings. Current Limitations Data quality — UK fire data is inconsistent and incomplete Regulatory acceptance — BSR has not yet accepted AI generated fire strategies Liability — Who is responsible when AI gets it wrong? Transparency — "Black box" models are unacceptable for safety critical decisions Our Approach At Magnus Opifex, we use AI as a tool to enhance — not replace — human expertise. Our engineers validate every AI assisted analysis. Interested in AI enhanced fire engineering? Contact us.