# ai-governance AI governance is the set of policies, standards, controls, and oversight used to direct and manage the safe, fair, transparent, accountable, and responsible development and use of artificial intelligence. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Getting started with AI governance 🔒 DevFeed: [Getting started with AI governance 🔒]() Original publisher: [Read original article]() Author: Luca Rossi Published: 2026-09-16T13:03:30Z Content type: article Language: en Sources: [Refactoring]() Topics: [ai-governance](), [Artificial Intelligence](), [Tool]() Tags: [agents](), [ai](), [ai-governance](), [governance](), [tools]() ### AI overview A primer on governing people, agents, tools, and actions in AI systems. ### Source excerpt A primer on how you should think about governing people, agents, tools, and actions. ## DigiCert's AI Trust framework for governing enterprise AI agents and models DevFeed: [DigiCert's AI Trust framework for governing enterprise AI agents and models]() Original publisher: [Read original article]() Author: Robin Birtstone Published: 2026-09-15T15:00:00Z Content type: article Language: en Sources: [www.theregister.com - Articles]() Topics: [ai-governance](), [AI Agent](), [Authorization](), [Security](), [data]() Tags: [agents](), [ai](), [ai-governance](), [authorization](), [data](), [security](), [sponsored]() ### AI overview This sponsored feature presents DigiCert's AI Trust framework for governing enterprise AI agents. The framework uses public key infrastructure, DNS, and attestation to help organizations identify agents, track data and credentials, stop compromised agents, and reconstruct incidents. ### Source excerpt SPONSORED FEATURE: DigiCert wants to hand every agent a passport, complete with an expiry date and a named human owner ## What is CIAM in 2026 and why does it matter? DevFeed: [What is CIAM in 2026 and why does it matter?]() Original publisher: [Read original article]() Author: Ravleen Kaur Published: 2026-09-15T00:00:00Z Content type: tutorial Language: en Sources: [Twilio Blog]() Topics: [identity and access management](), [trust](), [ai-governance](), [Security](), [Artificial Intelligence](), [IAM](), [Generative AI]() Tags: [ai-agents](), [ai-governance](), [email](), [fraud](), [fraud-detection](), [identity](), [identity-and-access-management](), [industry-insights](), [messaging](), [mobile](), [trust]() ### AI overview This article explains how customer identity and access management (CIAM) is evolving from point-in-time password checks into a continuous trust and control layer. It describes CIAM's role in authenticating users, governing delegated authority for AI agents, evaluating risk across channels, and balancing low-friction access with fraud detection. It also distinguishes customer identity from workforce IAM. ### Source excerpt Discover how customer identity and access management (CIAM) uses continuous trust, deepfake defense, and agentic AI governance to protect users. ## AI Security Governance: A Practical Framework for 2026 DevFeed: [AI Security Governance: A Practical Framework for 2026]() Original publisher: [Read original article]() Author: Christine Ferrusi Ross Published: 2026-09-15T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [Security](), [Securing AI](), [ai-governance](), [Software Engineering]() Tags: [2026](), [ai](), [ai-security](), [governance](), [practical](), [security]() ### AI overview This article presents AI security governance as a structured program built on four pillars: policy, risk assessment, monitoring and audit, and accountability. It explains how these controls address untracked AI systems, unclear ownership, and missing records of automated actions, and discusses regulatory and organizational pressures driving adoption. ### Source excerpt Build an AI security governance framework covering policy, risk assessment, monitoring, and accountability, plus a risk register template to copy today. | Blog ## AI, Disruption, and Standards DevFeed: [AI, Disruption, and Standards]() Original publisher: [Read original article]() Author: L. Jeffrey Zeldman Published: 2026-09-10T16:12:17Z Content type: opinion Language: en Sources: [Jeffrey Zeldman]() Topics: [Artificial Intelligence](), [ai-governance](), [web-standards](), [Generative AI](), [MCP](), [a2ui](), [Accessibility]() Tags: [a2ui](), [accessibility](), [ai](), [ai-governance](), [appearances](), [architecture](), [best-practices](), [design](), [designers](), [ethics](), [formats](), [generative-ai](), [governance](), [mcp](), [open-source](), [standards](), [ux](), [video](), [web-standards](), [webstandards]() ### AI overview This article introduces a video panel on AI and standards featuring Jeffrey Zeldman and Patrick Neeman. The discussion connects lessons from the web standards movement to AI interfaces, focusing on fragmented user experiences, accessibility, interoperability, provenance, and the role of open-source and community efforts. ### Source excerpt Individually, we have very little power, but together we have a great deal of power. In response to a series of Medium articles by Patrick Neeman--like this one that addressed issues of AI governance, fairness, and standardization--publisher Louis Rosenfeld invited Patrick and me to come on his show and talk about AI and standards. A [...] The post AI, Disruption, and Standards appeared first on Jeffrey Zeldman Presents. ## WSIS Forum 2026: From commitments to measurable implementation DevFeed: [WSIS Forum 2026: From commitments to measurable implementation]() Original publisher: [Read original article]() Author: Joyce Chen Published: 2026-09-06T23:14:00Z Content type: article Language: en Sources: [APNIC Blog]() Topics: [Development](), [ai-governance](), [SIEM, Security, Observability]() Tags: [2026](), [community](), [development](), [global](), [governance](), [igf](), [internet-governance](), [metrics](), [platform](), [policy](), [recommendations](), [wsis]() ### AI overview The WSIS Forum 2026 marked a shift from documenting digital-development commitments to demonstrating measurable implementation. The forum emphasized implementation roadmaps, evidence, targets, indicators, metrics, gap analysis, and policy recommendations aligned with the WSIS framework, the Sustainable Development Goals, and Global Digital Compact commitments. ### Source excerpt WSIS Forum 2026 marked the start of a new phase for global digital development, shifting the focus from commitments to measurable implementation. ## ASUS Lays Out a Full AI Factory Platform: Vera Rubin NVL72 Racks, STX Storage, and a Governance Layer DevFeed: [ASUS Lays Out a Full AI Factory Platform: Vera Rubin NVL72 Racks, STX Storage, and a Governance Layer]() Original publisher: [Read original article]() Author: Lyle Smith Published: 2026-09-04T17:54:45Z Content type: article Language: en Sources: [StorageReview.com]() Topics: [AI Factory](), [AI Infrastructure](), [AI Platform](), [NVIDIA Vera Rubin](), [NVIDIA DGX](), [NVIDIA Vera](), [MLOps](), [NVIDIA DSX](), [ai-governance](), [Server]() Tags: [2026](), [ai](), [ai-factory](), [ai-governance](), [ai-infrastructure](), [asus](), [enterprise](), [mlops](), [nvidia-dsx](), [nvidia-vera](), [nvl72](), [object-storage](), [platform](), [storage](), [vera-rubin-nvl72]() ### AI overview ASUS is broadening its AI infrastructure business from individual servers to a full AI factory platform covering accelerated computing, networking, storage, deployment, infrastructure management, MLOps, and governance. The article describes NVIDIA DSX-based planning, ASUS deployment and management tools, governance for AI services and autonomous agents, and server systems based on NVIDIA Vera Rubin hardware. ### Source excerpt ASUS is expanding its role in AI infrastructure, moving from individual AI servers to platforms for building, deploying, and operating entire AI factories. At AI Tech 2026 in Seoul, the company laid out a broader strategy that brings accelerated computing, networking, storage, deployment software, infrastructure management, and AI governance together under one platform. That puts The post ASUS Lays Out a Full AI Factory Platform: Vera Rubin NVL72 Racks, STX Storage, and a Governance Layer appeared first on StorageReview.com. ## Hedge 316: AI Governance DevFeed: [Hedge 316: AI Governance]() Original publisher: [Read original article]() Author: Russ Published: 2026-08-20T15:38:28Z Content type: article Language: en Sources: [rule 11 reader]() Topics: [ai-governance](), [Artificial Intelligence](), [Network]() Tags: [ai](), [ai-governance](), [audio](), [cost](), [governance](), [hedge](), [privacy](), [productivity]() ### AI overview This podcast episode examines AI governance for AI operations and general network use, focusing on privacy, cost control, accuracy, productivity measurement, and effective deployment. ### Source excerpt Deploying AI for AI Ops, or even just for general use in your network, is very simple--but we often forget that these kinds of new technologies need to be governed. From privacy through cost, operators need to decide how to govern their AI deployments to control costs, ensure accuracy, measure productivity, and make certain these systems are being used effectively. Colin Cosgrove joins Russ and Tom to look at AI governance. ## 4 FAQs about designing agentic systems for production DevFeed: [4 FAQs about designing agentic systems for production]() Original publisher: [Read original article]() Author: Kristin Crosier Published: 2026-08-19T00:00:00Z Content type: article Language: en Sources: [Redpanda]() Topics: [Artificial Intelligence](), [ai-governance](), [Responsibility & Safety](), [Architecture & Design](), [observability]() Tags: [agentic](), [ai-agents](), [ai-governance](), [architecture](), [cheat-sheet](), [observability](), [security]() ### AI overview This article presents practical guidance for designing and operating enterprise AI agents in production. It focuses on governance, policy enforcement, data access controls, observability, immutable action logs, audit transcripts, emergency shutdown capabilities, and guardrails for token and budget usage. ### Source excerpt Learn about the technical challenges many organizations face while deploying agentic systems, and how to ensure AI agents can operate safely and consistently. ## AI governance gaps leave developer and agent access to AI tools insufficiently controlled DevFeed: [AI governance gaps leave developer and agent access to AI tools insufficiently controlled]() Original publisher: [Read original article]() Author: Anubhav Sharma Published: 2026-08-05T01:56:41Z Content type: opinion Language: en Sources: [Nirmata]() Topics: [ai-governance](), [Security](), [Access Control](), [Authorization](), [developer-productivity](), [Monitoring](), [Large Language Model]() Tags: [access-control](), [ai](), [ai-governance](), [cloud-native](), [cncf](), [developer](), [devsecops](), [engineering](), [kubernetes](), [kyverno](), [llms](), [policy-management](), [risk-management](), [security](), [visibility]() ### AI overview The article presents aggregated responses from security leaders about AI governance in fast-moving engineering organizations. It identifies gaps in centralized access control, policy enforcement, session auditing, real-time visibility, and protection against exposing permissions or environment variables to LLMs. ### Source excerpt Three Questions We Asked About AI Governance -- And What the Answers Reveal Over the past few months, we've been having the same conversation on repeat with security leaders about AI at fast-moving engineering organizations. Different companies, different tech stacks, same three questions -- and,... The post The AI Innovation-Security Paradox first appeared on Nirmata. ## From pilot to production: The platform team's playbook for scaling AI coding agents in regulated industries DevFeed: [From pilot to production: The platform team's playbook for scaling AI coding agents in regulated industries]() Original publisher: [Read original article]() Author: Eric Paulsen Published: 2026-07-24T11:13:47Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [AI-assisted coding](), [ai-governance](), [observability](), [shadow AI](), [Deployment](), [coding]() Tags: [ai-adoption](), [ai-coding-agents](), [ai-governance](), [developers](), [financial-services](), [government](), [observability](), [shadow-ai]() ### AI overview This article presents a platform-team playbook for scaling AI coding agents from pilots to governed production in regulated industries. It emphasizes governance, observability, production infrastructure, and controls that provide visibility into agent actions, model usage, data access, token consumption, and costs. ### Source excerpt Scaling AI coding agents in regulated industries requires more than just successful pilots; it demands robust governance and production-ready infrastructure. Discover how platform teams can bridge the gap between experimentation and compliance by implementing observability, structured context engineering, and ephemeral workspace patterns to ensure safe, scalable AI adoption. ## Deploy agents you can trust with centralized AI governance DevFeed: [Deploy agents you can trust with centralized AI governance]() Original publisher: [Read original article]() Author: Kristin Crosier Published: 2026-07-21T00:00:00Z Content type: article Language: en Sources: [Redpanda]() Topics: [ai-governance](), [Responsibility & Safety](), [audit trail](), [SIEM, Security, Observability](), [Model Context Protocol](), [observability]() Tags: [agentic](), [ai](), [ai-governance](), [audit-trail](), [autonomous](), [autonomous-agents](), [enterprise](), [hosting](), [infrastructure](), [mcp](), [observability](), [thought-leadership](), [vibe-coding]() ### AI overview This article explains why enterprises struggle to deploy autonomous agentic systems: organizations lack confidence in agents that can access data and tools without unique identities, audit trails, or kill switches. It argues for a centralized AI governance layer enforced by infrastructure that agents cannot access or modify, positioned between agents and the data, tools, identities, and models they use. The proposed governance platform also supports scaling through AI gateways, MCP hosting, observability, and budgeting. ### Source excerpt Discover why organizations are struggling to deploy and scale agentic systems, and how a centralized AI governance platform can help you trust and scale agents. ## Trust you can verify: Figma is now ISO 42001 certified DevFeed: [Trust you can verify: Figma is now ISO 42001 certified]() Original publisher: [Read original article]() Author: Tushar Badlani Published: 2026-07-01T12:00:00Z Content type: article Language: en Sources: [Figma Blog]() Topics: [ai-governance](), [Figma](), [responsible-ai](), [Security]() Tags: [ai](), [ai-governance](), [figma](), [iso](), [iso-27001](), [responsible-ai](), [security](), [soc-2]() ### AI overview Figma announces ISO/IEC 42001:2023 certification for its Artificial Intelligence Management System. An accredited independent auditor assessed Figma's AI governance policies, risk management processes, data practices, development practices, and technical safeguards across its platform. ### Source excerpt Saying you use AI responsibly is easy, but proving it to an accredited auditor is harder. We decided that was a standard worth meeting. ## Supporting Europe's work in ensuring a trustworthy AI ecosystem DevFeed: [Supporting Europe's work in ensuring a trustworthy AI ecosystem]() Original publisher: [Read original article]() Published: 2026-06-11T00:00:00Z Content type: release Language: en Sources: [OpenAI News]() Topics: [Artificial Intelligence](), [OpenAI](), [Trustworthy AI](), [ai-governance](), [Code]() Tags: [ai](), [ai-content](), [ai-governance](), [ecosystem](), [eu](), [global-affairs](), [openai](), [trustworthy-ai]() ### AI overview OpenAI announces support for the EU Code of Practice on Transparency of AI-Generated Content, building on provenance standards, C2PA metadata, marking and detection methods, research, and a public verification tool. The article frames provenance as a way to provide context about content and strengthen a trustworthy AI ecosystem. ### Source excerpt OpenAI supports the EU Code of Practice on AI content transparency, advancing provenance standards and tools to help people understand AI-generated content. ## A blueprint for democratic governance of frontier AI DevFeed: [A blueprint for democratic governance of frontier AI]() Original publisher: [Read original article]() Published: 2026-06-03T10:00:00Z Content type: opinion Language: en Sources: [OpenAI News]() Topics: [Frontier AI](), [ai-governance](), [Responsibility & Safety](), [Resilience](), [OpenAI]() Tags: [ai-governance](), [frontier-ai](), [global-affairs](), [openai](), [resilience](), [safety](), [security]() ### AI overview OpenAI proposes a durable U.S. federal framework for governing increasingly capable frontier AI. The blueprint calls for building on state safety laws, strengthening CAISI as the federal institution for frontier AI safety, and coordinating a broader government resilience plan addressing national security and public safety challenges. ### Source excerpt OpenAI outlines a blueprint for U.S. governance of frontier AI, proposing a federal framework for safety, resilience, and national security. ## Everything you need to know about ITIL 5, AI and incident management DevFeed: [Everything you need to know about ITIL 5, AI and incident management]() Original publisher: [Read original article]() Author: Chris Evans Published: 2026-02-01T17:09:00Z Content type: article Language: en Sources: [The incident.io Blog]() Topics: [ai-governance](), [incident management](), [incident](), [AI Agent](), [Frameworks](), [audit trail](), [Automation]() Tags: [ai](), [ai-agent](), [audit-trail](), [automation](), [compliance](), [framework](), [governance](), [incident](), [incident-channel](), [incident-management](), [incident-response](), [operational](), [outage](), [post-mortem](), [regulatory](), [slack-incident]() ### AI overview This article explains how ITIL 5 updates incident management guidance for organizations using AI. It focuses on a new AI Governance extension module covering responsible adoption, risk management, transparency, accountability, and regulatory compliance, including governance questions around AI-suggested remediation, generated incident summaries, automated actions, and audit trails. ### Source excerpt We break down ITIL 5's governance framework and what it means for teams using AI in incident response. For incident management, it addresses questions like: Who's accountable when an AI-suggested remediation backfires? How do you audit AI-generated updates? ## BNY builds "AI for everyone, everywhere" with OpenAI DevFeed: [BNY builds "AI for everyone, everywhere" with OpenAI]() Original publisher: [Read original article]() Published: 2025-12-12T00:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [OpenAI](), [AI Strategy](), [ai-governance](), [Generative AI](), [AI Platforms/Deployment]() Tags: [agents](), [ai](), [ai-adoption](), [ai-agents](), [ai-governance](), [efficiency](), [enterprise](), [generative-ai](), [openai](), [platform](), [responsible-ai]() ### AI overview BNY is expanding enterprise-wide generative AI adoption with OpenAI through Eliza, an internal AI deployment and education platform. More than 20,000 employees are building AI agents across over 125 live use cases, while governance and responsible AI practices support safe experimentation and scale. ### Source excerpt BNY uses OpenAI to expand AI adoption enterprise-wide through Eliza, where 20,000+ employees build AI agents that improve efficiency and client outcomes. ## Streamfest Day 1: AI, governance, and enterprise agents DevFeed: [Streamfest Day 1: AI, governance, and enterprise agents]() Original publisher: [Read original article]() Author: Jenny Medeiros Published: 2025-11-11T00:00:00Z Content type: article Language: en Sources: [Redpanda]() Topics: [Streaming](), [Artificial Intelligence](), [ai-governance](), [migration](), [Databricks Unity Catalog integration](), [databricks]() Tags: [2025](), [acquisition](), [agents](), [ai](), [ai-governance](), [catalog](), [chat](), [confluent](), [databricks](), [databricks-unity-catalog-integration](), [developers](), [enterprise](), [event](), [migration](), [product](), [streaming](), [virtual-event]() ### AI overview Redpanda Streamfest is a two-day virtual event focused on data streaming for the AI era. Day one highlights sessions on AI, governance, enterprise agents, product capabilities, customer use cases, and migration from Confluent to Redpanda. ### Source excerpt Redpanda Streamfest is a two-day virtual event for developers to master data streaming for the AI era. Here's what happened on day one. ## Building AI Trust with Snyk Code and Snyk Agent Fix DevFeed: [Building AI Trust with Snyk Code and Snyk Agent Fix]() Original publisher: [Read original article]() Author: Liqian Lim (æž—åˆŠč’¨); Brendan Hann Published: 2025-06-23T04:00:00Z Content type: news Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [snyk](), [snyk-code](), [ai security](), [Application Security](), [ai-governance](), [Securing AI](), [Pull Request](), [ide]() Tags: [ai](), [ai-coding](), [ai-governance](), [ai-security](), [application-security](), [auto-remediation](), [autonomous](), [blog](), [code-security](), [compliance](), [developer](), [devops](), [engineering](), [pmm](), [pull-requests](), [sast](), [security](), [snyk](), [snyk-code](), [snyk-platform]() ### AI overview Snyk describes its AI Security Platform, Snyk Code, and Snyk Agent Fix for governing AI-assisted development. Snyk Agent Fix autonomously generates and validates code-security fixes, offering auto-remediation in IDEs and pull requests, while Snyk Code provides SAST, visibility, prioritization, and policy controls. ### Source excerpt Secure and accelerate your adoption of AI coding with pre-screened auto-fixes and autonomous code security for modern, developer-loved SAST. ## 3 tips from Snyk and Dynatrace's AI security experts DevFeed: [3 tips from Snyk and Dynatrace's AI security experts]() Original publisher: [Read original article]() Author: Sarah Conway Published: 2024-01-22T06:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Securing AI](), [ai-governance](), [dynatrace](), [Generative AI](), [Security & Privacy](), [AI Development]() Tags: [ai](), [ai-governance](), [ai-security](), [application-security](), [awareness](), [blog](), [development](), [devops](), [dynatrace](), [executive](), [generative-ai](), [governance](), [megawatt](), [security](), [security-privacy](), [snyk](), [snyk-platform]() ### AI overview This article recaps a Snyk and Dynatrace fireside chat about generative AI security. It examines AI's effects on software development and business application security, emphasizing cross-team governance, careful testing and implementation, and sustained security attention throughout development. ### Source excerpt Learn more about generative AI security in this recap from our recent fireside chat, featuring security and privacy experts from Snyk and Dynatrace. ## AI Governance: Evaluators/Auditors should compete for quality DevFeed: [AI Governance: Evaluators/Auditors should compete for quality]() Original publisher: [Read original article]() Author: Andrey Breslav Published: 2023-10-04T10:25:20Z Content type: opinion Language: en Sources: [Stories by Andrey Breslav on Medium]() Topics: [ai-governance](), [Responsibility & Safety](), [Artificial Intelligence]() Tags: [ai](), [ai-governance](), [ai-safety](), [audits](), [evals](), [evaluations](), [governance](), [independent]() ### AI overview The author argues that independent evaluations and audits of large AI models may become useful and commercially important but face unclear standards, weak independence, and poor incentives for evaluators to improve. The proposed solution is to make evaluators compete for quality through economic incentives, including a possible bounty funded by a share of each training run's cost. ### Source excerpt This post is part of a short series on AI Governance. I've recently completed the learning portion of the AI Governance course from BlueDot Impact, and it made me think :) In these posts, I'm writing down some thoughts that crossed my mind and that I haven't seen written down yet. I'm not claiming I'm the first person to come up with these as I haven't done a proper literature review, and I'd be happy to talk to people working on something similar, so please reach out if you are interested.These are very coarse drafts. I'm not trying to provide all the necessary context or references. This will probably only make sense to those people who have been looking into AI Governance lately. I think that governments will demand independent evals/audits for large models soon enough. Here's one particular initiative in this vein: some US senators propose a lot of things, including independent audits. Some people already work on some evals/audits, e.g. ARC Evals or Apollo Research. I'm setting aside the difference between evals and audits as I don't think it's relevant to this discussion. While evals/audits are unlikely to be sufficient, I think they can be very useful. I also think they have a very good chance of becoming a lucrative business. However, there are at least these issues: we don't have good definitions of what an evaluator is looking for; "signs of dangerous capabilities" + an incomplete list of examples is pretty much as good as we could define it so far; the independence of evaluators is not guaranteed by anything; the easiest an AI lab can do to remain compliant is to look for the worst-quality evaluator on the market who won't find anything; evaluators are not economically incentivised to improve their methods; simply licensing them won't help because we don't know what to license for. I'm not saying AI labs or evaluators are malicious. I just believe in behavioural economics, let's put it this way :) Proposed solution: set evaluators up to compete for quality