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Organisations are increasingly assessing how artificial intelligence can enhance the value of their established environmental data assets. While AI offers significant potential, its effectiveness is shaped by strategic choices made well before any models are deployed. This presentation positions AI not as an entry point, but as a natural progression in a broader data maturity strategy. Across industry contexts, the differentiator is seldom data age or volume, but the extent to which information is structured, integrated, and accessible. Hard copy reports, PDFs, spreadsheets, and legacy systems all represent valuable sources of insight, each requiring targeted preparation to unlock their full potential. The presentation sets out a staged, pragmatic pathway within a coherent data model, and storage in platforms designed for advanced analytics and AI. With these foundations in place, organisations are better positioned to apply AI confidently across a broad range of use cases such as search, reporting, prediction, anomaly detection, and automation. Looking to the future, AI value can be enabled by focused investment in data capabilities that support reliable, scalable, and decision ready insights.
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