Lab notes

Stanford HAI's 2026 AI Index is a core research reference for AI capability, adoption, investment, policy, and governance trends.

Source: hai.stanford.edu ↗

AI Governance

MIT's AI Risk Repository helps governance teams sort AI risks into categories that work for registers, controls, and executive review.

Source: airisk.mit.edu ↗

AI Risk Management

CSET policy research helps enterprises understand AI governance, security, capability trends, and institutional readiness.

Source: cset.georgetown.edu ↗

AI Governance

RAND AI research helps executives assess AI through risk, security, policy, and operational consequence lenses.

Source: rand.org ↗

AI Risk Management

The Alan Turing Institute offers research and policy context for trustworthy AI, responsible innovation, and data science governance.

Source: turing.ac.uk ↗

AI Governance

Partnership on AI resources help teams turn responsible AI principles into deployment governance and accountability practices.

Source: partnershiponai.org ↗

AI Governance

MLCommons gives teams benchmark and evaluation context for structured, comparable AI performance evidence.

Source: mlcommons.org ↗

AI Evaluation

ACM resources give professional and technical context for responsible computing, AI accountability, and governance practice.

Source: acm.org ↗

AI Governance

IEEE AI and ethics resources link technical design, human oversight, transparency, and accountability.

Source: standards.ieee.org ↗

AI Governance

Nature's AI research coverage is useful for understanding reliability limits, scientific evaluation, and responsible AI deployment.

Source: nature.com ↗

AI Evaluation

Science offers authoritative research and policy context for AI evaluation, governance, and evidence-based adoption.

Source: science.org ↗

AI Evaluation

Brookings AI research helps executives understand governance, regulation, public impact, and institutional accountability.

Source: brookings.edu ↗

AI Governance