The COVID-19 pandemic exposed an uncomfortable paradox. The world had unprecedented volumes of data, increasingly sophisticated epidemiological models, and rapidly evolving artificial intelligence (AI) capabilities. Yet many countries responded with fragmented information systems, siloed departments, and weak linkages between surveillance, clinical services, and political decision-making. The result was not merely technical inefficiency, but a response that proved uneven, delayed, and extraordinarily costly in human, social, and economic terms. In this context, epidemic intelligence (EI) has emerged not simply as a technical specialty but as a core function of modern health systems and global health security. AI, far from being an end in itself, can become the thread that stitches together data, institutions, and decisions. As in haute couture, the durability of the fabric does not depend on each individual piece of cloth, but on the quality of the invisible stitch that binds them. Today, AI-enabled epidemic intelligence must be understood as a global public good. When it fails, the consequences do not respect borders. This reframes the role of states, multilateral development banks, and major funders when investing in health systems and digital transformation.

This article highlights the urgency of moving from strategy to action in digital health, showing how interoperability, responsible AI, and governance can generate real and sustainable impact. With insights from the World Health Organization, MERCOSUR, and Uruguay, it emphasizes the role of ecosystems and partners such as Seniors International Consulting in turning vision into outcomes. Read the full article to explore how resilient, equitable, and future-ready health systems are being built today.

The green and digital transition will not be defined by the speed of technological advancement, but by the human and institutional capacity to govern it effectively.

Artificial intelligence (AI) is positioning itself as a key tool to accelerate the transition towards sustainable, resilient, and inclusive development models, particularly in strategic sectors such as banking, healthcare, and development financing. However, its positive impact is not automatic: it depends on robust governance frameworks capable of integrating ethics, transparency, accountability, and, centrally, a prepared human capital(1). International evidence shows that green and digital investments fail when talent governance lags behind. In this context, green governance driven by AI emerges not only as a technological innovation but as a political, labor, and strategic decision that conditions corporate sustainability performance and the real impact of green finance (2).

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