Search: “governance”

LangGuard's agentic workflow governance engine represents one of the first production deployments of Lakebase, Databricks' platform for managing AI agents. The deployment demonstrates how organization

arXiv:2604.21090v1 Announce Type: cross Abstract: AI governance programmes increasingly rely on natural language prompts to constrain and direct AI agent behaviour. These prompts function as executabl

With AI capabilities rapidly increasing, humans appear close to developing AI systems that are better than human experts across all domains. This raises a series of questions about how the world will—

arXiv:2604.06018v2 Announce Type: replace-cross Abstract: This study examines the perception of legal professionals on the governance of AI in developing countries, using Nigeria as a case study. The

arXiv:2610.10957v1 Announce Type: cross Abstract: Production AI systems deployed in high-stakes domains accumulate a governance liability that existing monitoring frameworks fail to detect: the progre

arXiv:2608.18086v1 Announce Type: new Abstract: The growth of open-weight foundation models (OWFMs) has prompted the AI community to re-evaluate strategies for effective downstream governance. Althoug

arXiv:2608.15131v1 Announce Type: new Abstract: Digital platforms govern by changing rules: rankings, monetization thresholds, moderation standards, verification systems, disclosure requirements, appe

As AI agents move from experimental chatbots into production systems, enterprises must rethink agent governance as autonomous actors gain access to sensitive data, tools and business processes that tr

arXiv:2505.11579v3 Announce Type: replace-cross Abstract: As AI systems evolve from static tools to dynamic agents, traditional categorical governance frameworks -- based on fixed risk tiers, levels o

arXiv:2605.23981v1 Announce Type: cross Abstract: Generative AI research increasingly confronts a shared problem: systems must sustain yet govern their own generative activity when uncertainty is high

As artificial intelligence agents become more powerful, agentic AI governance becomes increasingly important – and yet, today’s governance solutions struggle to keep AI agents from going off the rails

The AI era demands a fundamental shift in security, and that includes identity and access management (IAM). Traditional controls simply aren’t built for autonomous AI agents that interact with sensiti

Agentic artificial intelligence misbehavior is reaching epidemic proportions. Today’s AI governance solutions aren’t stopping the madness. We need to rethink our entire approach to AI governance. Even

arXiv:2603.02259v2 Announce Type: replace-cross Abstract: Multi-agent systems provide mature methodologies for role decomposition, coordination, and normative governance, capabilities that remain esse

arXiv:2604.22789v1 Announce Type: cross Abstract: Organizations deploying AI-enabled Intelligent Transportation Systems face fragmented governance: ISO/IEC 42001 demands a certifiable management syste

arXiv:2604.11065v1 Announce Type: new Abstract: AI systems increasingly shape high-stakes decisions in healthcare, law, defense, and education, yet existing governance paradigms -- AI Ethics, AI Safet

Agent governance is an engineering problem. We’ve built safeguards into Perplexity’s infrastructure, harnesses, and tools, and put them to work across our products. Today we're sharing how we engineer

Artificial intelligence agents have become table stakes in enterprise software, but in financial reporting, audit and compliance, speed counts for little if the output cannot be defended. That gap bet

arXiv:2609.13734v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly deployed in real-world high-stakes applications, effective governance has become essential. Existing

arXiv:2609.00309v1 Announce Type: cross Abstract: AI compute verification is one of the first tangible and tractable points for international policy aimed at AI governance. Determining whether frontie

arXiv:2608.07070v1 Announce Type: cross Abstract: With the rapid diffusion of AI-generated content, AI-driven misinformation is becoming increasingly pervasive and difficult to govern, undermining inf

We stand at a critical crossroads in the debate over AI governance in the United States, and it feels like we are inching closer to a very serious battle over whether or not open source models will ev

arXiv:2607.05410v1 Announce Type: cross Abstract: We present CANONIC: governed intelligence that compiles digital artifacts into an evidence ledger at scale. Large language models generate prose faste

arXiv:2607.02116v1 Announce Type: new Abstract: Autonomous AI agents increasingly depend on external knowledge stores, yet most retrieval pipelines provide relevance without durable guarantees of prov

arXiv:2606.12320v1 Announce Type: new Abstract: Enterprise security was built to govern data boundaries: the protected surface was data at rest and in transit, and the controls -- access control, data

arXiv:2606.08806v1 Announce Type: cross Abstract: Artificial Intelligence (AI) and Large Language Models (LLMs) are increasingly used in autonomous software testing; however, AI-generated test artifac

arXiv:2605.20874v1 Announce Type: new Abstract: Enterprise agents are increasingly expected to operate autonomously across tools and interfaces, yet production deployments require governance by constr

Model risk governance and risk intelligence are distinct but complementary practices in machine learning operations. Model risk governance focuses on establishing policies, controls, and compliance fr

arXiv:2604.19751v1 Announce Type: new Abstract: Generative AI is entering research, education, and professional work faster than current governance frameworks can specify how AI-assisted outputs shoul

Enterprises are chasing AI models at a dizzying pace, yet the organizations pulling ahead are the ones that paused to build something less glamorous: a trusted, governed data foundation. Pressure is m

arXiv:2604.07833v1 Announce Type: new Abstract: Embodied agents are evolving from passive reasoning systems into active executors that interact with tools, robots, and physical environments. Once gran

Enterprise multi-agent AI systems produce thousands of inter-agent interactions per hour, yet existing observability tools capture these dependencies without enforcing anything. OpenTelemetry and Lang

arXiv:2610.12916v1 Announce Type: new Abstract: Existing governance approaches in decentralized financial networks rely on manual review processes conducted by human committees, which introduces subje

AWS invests in tools that help customers align with international standards for responsible AI governance. In this post, we explore the AI system impact assessment: what it is, how it improves enterpr

arXiv:2609.29465v1 Announce Type: new Abstract: Large language model based coding agents have made substantial progress on repository-level software engineering tasks. Existing repository benchmarks,

arXiv:2609.29345v1 Announce Type: new Abstract: Enterprise governance requires decisions, evidence, and accountable authority; it does not require every review task to retain its current human impleme

arXiv:2609.11391v1 Announce Type: cross Abstract: Environmental controversies in global supply chains pose significant risks for global buyers. This study examines whether overseas suppliers' exposure

arXiv:2606.23094v2 Announce Type: replace-cross Abstract: As AI systems become increasingly persistent and personalized, they make possible a class of technologies that we call cognitive digital twins

arXiv:2609.10489v1 Announce Type: new Abstract: AI literacy provides foundational competencies that support ethical, transparent, and sustainable technological development, although higher-order capab

arXiv:2609.01040v1 Announce Type: cross Abstract: Machine learning systems deployed for credit, hiring, and resource distribution are increasingly subject to regulatory oversight from policies such as

arXiv:2608.19278v1 Announce Type: cross Abstract: The most capable general-purpose AI (GPAI) models are mostly built in two jurisdictions, the United States and China, but the risks they carry land gl

arXiv:2608.14568v1 Announce Type: new Abstract: As Artificial Intelligence (AI) systems become deeply integrated into critical global infrastructure, the urgency for robust governance frameworks has i

arXiv:2607.22692v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for emotional support despite lacking mechanisms to safely govern evolving mental health risk. Existi

arXiv:2607.20065v1 Announce Type: new Abstract: Enterprise strategic decision support requires AI systems that are not only accurate, but also uncertainty-aware, risk-calibrated, explainable, and gove

arXiv:2607.13716v1 Announce Type: new Abstract: Agentic AI systems increasingly act through heterogeneous runtimes: local coding hooks, SDK tools, browser automation, managed-agent traces, API gateway

arXiv:2607.07612v1 Announce Type: cross Abstract: Artificial intelligence is rapidly evolving from generative systems to agentic AI capable of autonomously planning and executing tasks. Widely charact