Speaker
Description
Environmental sustainability assessment is increasingly part of the evidence infrastructure that underpins business decisions, regulatory preparedness and long-term strategy. Companies need models that represent products and supply chains with sufficient accuracy to identify hotspots, prioritise interventions, compare design alternatives and anticipate the implications of future technologies or portfolio shifts. At the same time, regulatory and disclosure requirements are evolving, creating demand for assessment workflows that are not only scientifically credible, but also efficient, reproducible and auditable.
This keynote will offer an industry perspective on the practical conditions that may influence whether open-source LCA data and tools can move from promising research outputs to trusted and scalable workflows. It will explore the implementation gap between what is possible in research or prototype settings and what is needed in complex organisational environments, where tools must connect with existing digital infrastructure, data must be traceable and well documented, and assessment methods must be reliable and adaptable over time. While emerging capabilities such as AI-assisted end-to-end modelling and synthetic data generation create further opportunities, they also raise significant questions about accuracy, verification, traceability, governance, assurance and decision risk.
The next generation of digital LCA workflows will need to be transparent enough to build trust, modular enough to adapt to evolving policy and methodological requirements, interoperable enough to scale, and governed well enough to support assurance and decision-grade evidence. Achieving this will require deeper collaboration between researchers, developers, industry practitioners and regulators, with shared attention not only to tools and data, but also to the standards and talent needed to connect them.
The keynote will invite discussion on the existing challenges and enablers for closing the implementation gap, and on how we can better connect tools, data and people so that open LCA developments support both scientific progress and trusted real-world decisions.