Navigating the Bumpy Road from Data to Health: A Worthwhile Journey?
Abstract
Across both human health and livestock production systems, the last two decades have been marked by an unprecedented growth in data availability. Advances in genomics, phenomics, imaging, sensors, electronic records, and environmental monitoring have created the expectation that abundant data, coupled with artificial intelligence (AI), machine learning (ML), and advanced statistics, would naturally translate into improved outcomes. Experience suggests that while data-rich environments are necessary, they are far from sufficient. This paper emphasizes parallels between research and advances in human medicine and lifestyle sciences-where abundant data enable discovery, risk stratification, and tailored interventions-and the emerging data-rich realities of livestock systems. The central argument is that the dominant challenge has shifted from data generation and discovery to translation: converting scientific insight into sustained improvements in health, productivity, and efficiency. Drawing on experience from human healthcare, translational science, and health system operations, the paper examines how learning from data enables tailored treatments and lifestyle recommendations from populations to individuals, while simultaneously exposing new sources of complexity, cost, and risk. Initiatives such as Clinical and Translational Science Awards (CTSA), Learning Health Systems, and precision medicine/health have emerged to address the gap between discovery and outcomes. Similar dynamics are increasingly visible in livestock genetics and production, where multi-modal data and predictive models promise gains but demand new governance, infrastructure, and execution discipline. Navigating this bumpy road is worthwhile, provided expectations are realistic and translation is treated as a first-class scientific and operational problem.
Keywords: 2026
How to Cite:
Tachinardi, U., (2026) “Navigating the Bumpy Road from Data to Health: A Worthwhile Journey?”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2343055. doi: https://doi.org/10.31274/wcgalp.24482
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