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The report synthesizes insights from the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing, focusing on how AI and advanced computing are transforming scientific discovery. It identifies four strategic themes essential for enhancing scientific computing ecosystems: software ecosystems for AI, trust and validation, human-AI collaboration, and workforce development. The report outlines eight actionable priorities for community engagement aimed at fostering sustainable and resilient scientific computing practices in the face of evolving AI technologies.
Trust and traceability in AI-enabled scientific discovery are now recognized as critical pillars for future scientific computing ecosystems.
Scientific computing is undergoing rapid transformation as advances in artificial intelligence, heterogeneous computing, automation, and data-intensive research reshape not only computational tools but also the institutions, workforce models, and collaborative practices that support scientific discovery. This report synthesizes insights from the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing, the second in a three-year series focused on strengthening scientific computing ecosystems through socio-technical co-design. Workshop discussions identified four interdependent strategic themes: software ecosystems for AI-enabled scientific discovery; trust, validation, and traceability; human-AI teaming and paradigm shifts; and workforce, pedagogy, and governance. The report translates these themes into eight priorities for community action spanning shared research infrastructure, trust and traceability, user experience, human-AI teaming, workforce development, cross-sector coordination, stewardship and sustainability, and evaluation of scientific value. Together, these priorities outline directions for building scientific computing ecosystems that remain trustworthy, sustainable, innovative, and resilient as AI assumes a growing role in scientific work.
