Artificial intelligence and strategic foresight for sustainable territories: anticipating climate risks and guiding public decisions
DOI:
https://doi.org/10.71068/ec000101Keywords:
artificial intelligence, strategic foresight, climate risk, public decision-making, sustainable territoriesAbstract
Introduction: Evidence on artificial intelligence, strategic foresight, climate-risk anticipation and public decision-making has expanded during the last years, but differences in design, scale, indicators and territorial context still complicate direct comparison. A traceable synthesis is therefore needed to distinguish. Objective: To critically examine the evidence on artificial intelligence, strategic foresight, climate-risk anticipation and public decision-making, identifying recurrent mechanisms, context-dependent effects and gaps that matter for policy and territorial management. Method: A structured narrative review was conducted for the 2020–2025 publication window using the corrected evidence matrix supplied for this manuscript. The final corpus comprised 24 peer-reviewed journal studies, each with a real and traceable DOI. Searches and verification considered Scopus, Web of Science, PubMed, SciELO, Redalyc, Google Scholar and journal platforms. Eligibility required thematic relevance, explicit methods, recoverable results and bibliographic traceability. Study context, design, analytical dimensions, principal findings and limitations were. Results: The reviewed evidence supports AI for forecasting, scenario exploration and risk detection, but its public value depends on data quality, interpretability and institutional capacity. Predictive performance alone is insufficient when uncertainty, unequal data coverage or weak accountability can distort territorial priorities. Across the corpus, stronger inferences came from. Conclusions: The synthesis supports context-sensitive decisions rather than universal prescriptions. For inteligencia artificial, prospectiva estratégica y riesgo climático, future research should improve comparability of indicators, reporting transparency and longitudinal assessment, while explicitly documenting equity, governance and implementation conditions.
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