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What are the prospects of using Artificial Intelligence (AI) to automate steps of the evidence synthesis pipeline? Prof Malcolm Macleod explains why there is no easy way to make evidence synthesis easy.

Explore livestock sector priorities with our interactive Livestock Strategy Documents Dashboard. 

Over the last half-year, SEBI-Livestock has been working with partners across the University of Edinburgh to explore how data science and AI can help address persistent livestock data challenges.

SEBI-Livestock team members report back from the AI for Good Global Summit 2026.

An innovative machine learning approach spearheaded by SEBI-Livestock and partners could help advance research on antimicrobial resistance (AMR).

Good data on livestock disease and mortality is essential for making informed investments in animal health, and to improve productivity and incomes. But decision-makers face enormous challenges when it comes to grasping and making sense of the existing body of literature and evidence, which is scattered across multiple databases or even unpublished.

The systematic evidence map allows users to quickly take stock of evidence on livestock disease prevalence and mortality. The map reveals the distribution and quantity of available evidence, and highlights areas for further investment and research.

Innovative data-driven tool will accelerate collection of crucial evidence