A new Publicly Available Specification (PAS) sets a benchmark for validating AI-assisted CFD modelling. Implement this framework to ensure your AI-powered fire engineering analysis is robust and defensible.. A New Era for Fire Engineering: Standardising AI in CFD The landscape of fire engineering is undergoing a significant transformation with the advent of artificial intelligence (AI). As AI tools become increasingly sophisticated, their integration into computational fluid dynamics (CFD) for fire modelling presents both unprecedented opportunities and considerable challenges. Recognising this burgeoning trend, the British Standards Institution (BSI) is set to release a new Publicly Available Specification (PAS) in Q4 2026. This landmark document aims to provide a much needed framework for the validation and verification of AI enhanced CFD models, ensuring their reliability and defensibility within the fire safety industry. The PAS will address critical concerns around the transparency, accuracy, and ethical deployment of AI in fire safety critical applications, ultimately fostering greater confidence in these advanced simulation techniques. This initiative by the BSI reflects a proactive approach to steer the responsible adoption of AI, safeguarding lives and property in line with the overarching principles of fire safety legislation. The Rise of AI in Fire Modelling: Opportunities and Risks AI’s ability to process vast datasets, identify complex patterns, and make rapid predictions offers substantial benefits to fire engineers. It can refine CFD simulations, potentially leading to more accurate predictions of smoke movement, heat transfer, and occupant egress in buildings. This can, in turn, inform more effective fire safety designs. However, the 'black box' nature of some AI algorithms raises concerns about interpretability and reproducibility. Without a robust validation framework, there is a risk of AI models producing erroneous or non compliant results, potentially leading to designs that compromise safety. The new BSI PAS seeks to mitigate these risks by establishing clear criteria for demonstrating the veracity and robustness of AI driven CFD analyses. This is particularly pertinent given the stringent requirements for fire safety compliance outlined in regulations such as the Regulatory Reform (Fire Safety) Order 2005 (RRO 2005). Addressing Regulatory Demands: The Need for Defensible AI The introduction of the Building Safety Act 2022 (BSA 2022) has fundamentally reshaped the regulatory landscape for building safety in the UK. This legislation places heightened emphasis on accountability and competence throughout the life cycle of a building. For fire engineers utilising AI in their CFD analyses, the BSA 2022 necessitates an even greater degree of scrutiny and rigour in demonstrating the validity of their work. Similarly, the Fire Safety (England) Regulations 2022 (FS(E)R 2022) further delineate responsibilities for ensuring fire safety in occupied buildings. The new BSI PAS will serve as a crucial tool for fire engineers to uphold these statutory obligations, providing a clear pathway to demonstrate that their AI enhanced CFD models are both technically sound and legally defensible. This will be vital for Responsible Persons and Accountable Persons seeking assurances regarding the fire safety strategies implemented in their buildings. Key Principles of the New BSI PAS While the full details of the PAS will be revealed upon its release, it is anticipated to focus on several core principles for validating AI driven CFD. These will likely include: Data Quality and Integrity: Guidelines for the selection, pre processing, and validation of data used to train and test AI models. Model Transparency and Interpretability: Requirements for understanding how AI models arrive at their conclusions, moving beyond a simple 'black box' approach. Verification and Validation (V&V): Establishing robust methodologies for comparing AI model outputs against established benchmarks, experimental data, and traditional CFD simulations. Uncertainty Quantification: Addressing how the uncertainties inherent in AI models are identified, quantified, and communicated. Documentation and Reporting: Standardised formats for documenting the AI model's development, validation process, and limitations. These principles will ensure that AI applications in fire engineering adhere to the high standards expected by building control bodies and fire authorities. Interoperability with Existing Standards: BS 9991 and BS 9999 The new BSI PAS will not operate in isolation but will complement existing British Standards that govern fire safety design. Standards like BS 9991:2011, Fire safety in the design, management and use of residential buildings – Code of practice , and BS 9999:2017, Fire safety in the design, management and use of non residential buildings – Code of practice , already provide comprehensive guidance for fire safety engineeri