# governance Published articles for governance. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## WSO2 Releases Agent Manager as Enterprises Look to Control Growing AI Agent Sprawl DevFeed: [WSO2 Releases Agent Manager as Enterprises Look to Control Growing AI Agent Sprawl]() Original publisher: [Read original article]() Author: Craig Risi Published: 2026-09-18T12:00:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [AI Agent](), [Artificial Intelligence](), [Authorization](), [Security](), [Deployment](), [Kubernetes](), [Model Context Protocol](), [OpenTelemetry]() Tags: [agent-identity](), [agentic-ai-architecture](), [ai](), [ai-agent](), [ai-agents](), [ai-development](), [ai-ml-data-engineering](), [aiops](), [authorization](), [deployment](), [devops](), [governance](), [kubernetes](), [ml-data-engineering](), [model-context-protocol](), [news](), [opentelemetry](), [ws02-agent-manager](), [ws02-stratos]() ### AI overview WSO2 has released Agent Manager, an open-source platform for governing AI agents across models, frameworks, and deployment environments. The general availability release adds agent identity and authorization, MCP governance, lifecycle controls, a Kubernetes-native sandboxed runtime, and OpenTelemetry-based tracing and evaluation. ### Source excerpt WSO2 has announced the general availability of WSO2 Agent Manager, an open-source platform designed to provide centralized governance, identity management, security controls, and operational oversight for AI agents running across different models, frameworks, and deployment environments. By Craig Risi ## AI Agent Security in the Enterprise: Interview With Isabelle Mauny DevFeed: [AI Agent Security in the Enterprise: Interview With Isabelle Mauny]() Original publisher: [Read original article]() Author: Bill Doerrfeld Published: 2026-09-18T07:00:00Z Content type: article Language: en Sources: [Nordic APIs]() Topics: [Artificial Intelligence](), [AI Agent](), [Security](), [Securing AI](), [Model Context Protocol](), [API]() Tags: [access-control](), [ai](), [ai-agent](), [ai-agents](), [api-governance](), [api-security](), [apis](), [authorization](), [blog](), [cost](), [governance](), [llm](), [mcp](), [owasp](), [platform-summit](), [security](), [supply-chain]() ### AI overview An interview with Isabelle Mauny examines enterprise AI agent security, including MCP governance, API risks, supply chain threats, and cost control. ### Source excerpt AI agents are quickly rising in the enterprise. They're granting more powers to knowledge workers across sales, finance, engineering, marketing, and other disciplines in the process. Yet, as most quick technological adoptions go, security is often falling by the wayside or being implemented after the fact. Ahead of Nordic APIs Summit 2026, we're connecting with ... ## AI Cost Visibility: Why Policies Don't Stop Surprise Bills DevFeed: [AI Cost Visibility: Why Policies Don't Stop Surprise Bills]() Original publisher: [Read original article]() Author: Kelsey Rosen Published: 2026-09-17T00:00:00Z Content type: opinion Language: en Sources: [Harness Blog]() Topics: [Artificial Intelligence](), [finops]() Tags: [ai](), [cost](), [finops](), [governance](), [organizations](), [policies](), [report](), [visibility]() ### AI overview Organizations are establishing AI spending policies but continue to receive unexpected bills because policies do not provide sufficient cost visibility or enforcement. The article argues that AI spending requires FinOps governance capable of tracking actual usage, detecting issues such as oversized models and retry loops, and assigning clear ownership. ### Source excerpt Organizations are writing AI spend policies but still getting surprise bills. Learn why governance alone fails without real policies. | Blog ## GPT-6 Astra Is the First Model OpenAI Classifies as Critical for Cybersecurity DevFeed: [GPT-6 Astra Is the First Model OpenAI Classifies as Critical for Cybersecurity]() Original publisher: [Read original article]() Author: Steef-Jan Wiggers Published: 2026-09-17T04:59:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [Cybersecurity](), [gpt-6-astra](), [OpenAI](), [Vulnerabilities](), [Exploit](), [browser](), [Kernel](), [Chain-of-thought]() Tags: [agents](), [ai](), [ai-ml-data-engineering](), [architecture](), [architecture-design](), [azure](), [browser](), [chain-of-thought](), [cloud](), [cybersecurity](), [development](), [devops](), [exploit](), [generative-ai](), [governance](), [gpt-6-astra](), [gpt-6-astra-critical-cyber](), [kernel](), [machine-learning](), [ml-data-engineering](), [news](), [openai](), [vulnerabilities](), [zero-day]() ### AI overview OpenAI classified GPT-6 Astra as the first model to reach its Critical cybersecurity threshold. Expert-led evaluations reported previously unknown vulnerabilities in a browser and an operating-system kernel, along with working exploit chains. The system card also reported a substantial decline in chain-of-thought monitorability. ### Source excerpt OpenAI has classified GPT-6 Astra at the Critical cybersecurity threshold under its Preparedness Framework, a first. In expert-led testing the model found previously unknown vulnerabilities in a browser and an OS kernel and built working exploits. The same system card reports a substantial decline in chain-of-thought monitorability. By Steef-Jan Wiggers ## Developer portal security and governance best practices DevFeed: [Developer portal security and governance best practices]() Original publisher: [Read original article]() Author: Jesse Wang Published: 2026-09-17T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [internal developer portal](), [Security](), [Access Control](), [Automation](), [audit](), [Vulnerabilities](), [Terraform](), [Deployment]() Tags: [access-control](), [auditability](), [automation](), [developer](), [governance](), [hardcoded-credentials](), [internal-developer-portal](), [microservices](), [security](), [security-compliance]() ### AI overview This article presents security and governance practices for internal developer portals. It focuses on role-based access control, automated audit logging, centralized visibility, software catalog governance, and reducing risks from infrastructure drift and workflow sprawl. ### Source excerpt Enhance developer portal security, compliance, and auditability without slowing down engineering teams. See how Harness helps simplify IDP governance. | Blog ## Automattic CEO Matt Mullenweg returned after 33 hours of leave without a public explanation DevFeed: [Automattic CEO Matt Mullenweg returned after 33 hours of leave without a public explanation]() Original publisher: [Read original article]() Author: Adrian Bridgwater Published: 2026-09-16T20:39:42Z Content type: news Language: en Sources: [The New Stack]() Topics: [WordPress](), [App](), [Open Source](), [Tumblr]() Tags: [cloud-services](), [company](), [cto](), [developer-tools](), [governance](), [matt-mullenweg](), [open-source](), [wordpress]() ### AI overview Automattic CEO Matt Mullenweg was placed on leave and reinstated about 33 hours later. The company has not publicly explained what prompted the leave or return, while observers have raised--but not established--the possibility of an attempted change in control. ### Source excerpt There were unusual goings-on this month at Automattic, a company known for its free and open-source app for building WordPress The post Automattic says CEO Mullenweg was gone and back inside 33 hours. What happened between? appeared first on The New Stack. ## Beyond the sync: Argo CD needs an Enterprise Control Plane DevFeed: [Beyond the sync: Argo CD needs an Enterprise Control Plane]() Original publisher: [Read original article]() Author: Eric Minick Sudarshan Purohit Published: 2026-09-16T20:28:57.610955Z Content type: opinion Language: en Sources: [Harness Blog]() Topics: [argo-cd](), [GitOps](), [Orchestration](), [DevOps](), [Platform Engineering](), [Deployment](), [Artificial Intelligence]() Tags: [argo-cd](), [deployment](), [gitops](), [governance](), [orchestration](), [platform-engineering](), [verification]() ### AI overview This article argues that Argo CD's manifest synchronization is only one part of enterprise software delivery. It describes how scaling GitOps can create operational toil and Argo sprawl, and proposes an enterprise control plane with workflow orchestration, governance, and deployment verification. ### Source excerpt Scaling GitOps? Argo CD is great for syncing manifests, but enterprise delivery requires workflow orchestration, governance, and AI verification. | Blog ## AI Agent Governance: Why It Belongs in Your Platform DevFeed: [AI Agent Governance: Why It Belongs in Your Platform]() Original publisher: [Read original article]() Author: Prateek Mittal Published: 2026-09-16T20:28:57.610955Z Content type: article Language: en Sources: [Harness Blog]() Topics: [AI Agent](), [Artificial Intelligence](), [observability](), [audit](), [test](), [Deployment](), [Monitoring](), [pull-requests]() Tags: [ai](), [ai-agent](), [audit](), [deployment](), [governance](), [monitoring](), [observability](), [pull-requests](), [test]() ### AI overview Engineering leaders from Yelp, Platformable, and Harness argue that AI agent governance must be automated, continuously enforced, and built into the platform rather than left to policy documents. The article discusses audit trails, agent-to-agent access controls, experiment tracking, testing, latency monitoring, rollback paths, and observability for agent-driven changes. ### Source excerpt Engineering leaders from Yelp, Platformable, and Harness explain why AI agent governance has to be built into the platform, not a policy doc. | Blog ## The Future of Data Engineering in the Age of AI | Erfan Hesami DevFeed: [The Future of Data Engineering in the Age of AI | Erfan Hesami]() Original publisher: [Read original article]() Author: Daniel Beach Published: 2026-09-16T13:21:19Z Content type: article Language: en Sources: [Data Engineering Central]() Topics: [data-engineering](), [AI Engineering](), [agent observability](), [coding](), [Security]() Tags: [agents](), [ai](), [ai-agents](), [ai-engineering](), [coding](), [data-engineering](), [fundamentals](), [governance](), [security]() ### AI overview An interview with Erfan Hesami examines how AI and agents may change data engineering, including the evolving role of data engineers, the overlap with AI engineering, the continuing importance of fundamentals, and the need to manage governance, security, costs, technical debt, and human judgment. ### Source excerpt AI Agents, Coding & Fundamentals ## 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. ## Glyph: A Multi-Strategy Agentic System for Column Description and Sensitivity-Ontology Tagging of Enterprise Data Catalogs DevFeed: [Glyph: A Multi-Strategy Agentic System for Column Description and Sensitivity-Ontology Tagging of Enterprise Data Catalogs]() Original publisher: [Read original article]() Published: 2026-09-16T00:00:00Z Content type: article Language: en Sources: [Apple Machine Learning Research]() Topics: [data](), [Large Language Model](), [Code](), [Retrieval-Augmented Generation](), [Access Control](), [Graphs](), [GitHub]() Tags: [agents](), [classification](), [code](), [data](), [documentation](), [governance](), [production](), [provenance](), [retrieval](), [vector-database]() ### AI overview Glyph is a production system for generating column descriptions and assigning sensitivity-ontology labels in enterprise data catalogs. It uses cooperating LLM agents, source-code-grounded retrieval, parallel tagging strategies, vector-based metadata matching, and ranked-output fusion to support auditable cataloging. ### Source excerpt Enterprise data lakes accumulate tables faster than human stewards can document or classify them, leaving columns with missing descriptions and unassigned governance labels. This documentation debt undermines data discovery, access control, and regulatory compliance. We present Glyph, a production system that frames two coupled problems, column description generation and column type annotation for data classification, as cooperating LLM agents orchestrated as stateful graphs. The Descriptor grounds generation in the pipeline source code that produces each column, retrieved on demand from an... ## Thinking Like A Naturalist: An Interview with Claire Barrett DevFeed: [Thinking Like A Naturalist: An Interview with Claire Barrett]() Original publisher: [Read original article]() Author: J Simpson Published: 2026-09-15T07:00:00Z Content type: article Language: en Sources: [Nordic APIs]() Topics: [Artificial Intelligence](), [systems](), [Testing]() Tags: [2026](), [ai](), [ai-agents](), [ai-readiness](), [api-governance](), [api-integration](), [api-security](), [artificial-intelligence](), [awareness](), [blog](), [digital-transformation](), [driving](), [generative-ai](), [governance](), [integration](), [summit](), [systems](), [testing]() ### AI overview Claire Barrett discusses the mindset shift needed for AI-enabled strategies, emphasizing systems thinking, governance, testing, awareness, and attention to long-term risks. ### Source excerpt Ahead of Nordic APIs Summit 2026, we catch up with speaker Claire Barrett on the mindset shift needed for adopting AI-enabled strategies. "Imagine driving around an old town," responds Claire Barrett when asked to describe what it means to be AI-ready from an integration perspective. "Imagine a European city that's been inhabited for thousands of ... ## How Databricks' marketers use data 3x more with Genie, an AI analytics assistant DevFeed: [How Databricks' marketers use data 3x more with Genie, an AI analytics assistant]() Original publisher: [Read original article]() Author: Elizabeth Dobbs; Thomas Russell; Katy Yuan; Sydney Sundell Published: 2026-09-15T00:36:33Z Content type: article Language: en Sources: [Databricks]() Topics: [databricks](), [Artificial Intelligence](), [data](), [dashboards]() Tags: [ai](), [best-practices](), [dashboards](), [data](), [databricks](), [enterprise](), [governance](), [marketing](), [metrics]() ### AI overview Databricks describes how its marketing organization unified campaign, sales, CRM, web analytics, advertising, and other data in a governed lakehouse. It built Marge, a Genie Agents-based conversational analytics assistant that answers marketers' natural-language questions using governed enterprise data. The article says this approach helped the marketing department use data three times more often in decisions. ### Source excerpt Most marketing teams aspire to be data-driven. In practice, getting a trusted answer,... ## 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 ## Open Secure AI Alliance Joins the Linux Foundation to Build a Shared, Open Defense Stack for the AI Era DevFeed: [Open Secure AI Alliance Joins the Linux Foundation to Build a Shared, Open Defense Stack for the AI Era]() Original publisher: [Read original article]() Author: andrewb@proximabiz.com (The Linux Foundation) Published: 2026-09-14T16:00:00Z Content type: news Language: en Sources: [Linux Foundation - Blog]() Topics: [Linux](), [Artificial Intelligence](), [Securing AI](), [open-source-security](), [Cybersecurity](), [Security](), [Resilience](), [Inference]() Tags: [ai](), [ai-security](), [collaboration](), [cybersecurity](), [governance](), [infrastructure](), [linux](), [models](), [nvidia](), [open-source](), [open-source-security](), [open-source-software](), [resilience](), [security](), [september-2026](), [standards]() ### AI overview The Open Secure AI Alliance has joined the Linux Foundation under neutral governance. It aims to help organizations collaborate on open AI security tools, research, shared standards, and verifiable defenses spanning models, inference, agents, identity, policy, enforcement, containment, and infrastructure. ### Source excerpt Originally founded by dozens of enterprise leaders and NVIDIA, the Alliance moves to neutral governance to expand industry collaboration on open AI security tools, research and shared defenses ## Presentation: Decision Models in Agentic Architectures: From Production to Agent Skills DevFeed: [Presentation: Decision Models in Agentic Architectures: From Production to Agent Skills]() Original publisher: [Read original article]() Author: Alex Porcelli Published: 2026-09-14T11:00:00Z Content type: article Language: en Sources: [InfoQ]() Topics: [Agent Skills](), [Artificial Intelligence](), [Large Language Model](), [NeMo]() Tags: [agent](), [agent-skills](), [agentic](), [agentic-ai-architecture](), [agents](), [ai](), [ai-architecture](), [ai-ml-data-engineering](), [architecture](), [architecture-design](), [architectures](), [artificial-intelligence](), [business](), [decision-models-agentic-ai](), [development](), [enterprise](), [enterprise-architecture](), [governance](), [infoq](), [large-language-models](), [llms](), [ml-data-engineering](), [models](), [nemo](), [presentation](), [production](), [qcon-ai-boston-2026](), [qcon-software-development-conference](), [skills](), [transcripts]() ### AI overview Alex Porcelli explains how DMN decision models can be integrated with LLMs, agent skills, and NeMo guardrails to create auditable and deterministic agentic architectures for high-stakes enterprise decisions. ### Source excerpt Alex Porcelli discusses the critical gap in enterprise AI: non-deterministic output and lack of accountability in high-stakes decisions. He shares how integrating DMN decision models with LLMs, agent skills, and NeMo guardrails creates auditable, deterministic agentic architectures - allowing business leaders to own decision logic while engineers maintain robust architectural governance. By Alex Porcelli ## Second-Gen Single-Rack AWS Outposts Puts 2,688 vCPUs and 100TB of EBS in One 42U Rack DevFeed: [Second-Gen Single-Rack AWS Outposts Puts 2,688 vCPUs and 100TB of EBS in One 42U Rack]() Original publisher: [Read original article]() Author: Harold Fritts Published: 2026-09-12T18:24:22Z Content type: news Language: en Sources: [StorageReview.com]() Topics: [AWS Outposts](), [Amazon Web Services](), [cloud-infrastructure](), [Network](), [Latency](), [data-processing](), [Security]() Tags: [5g](), [automation](), [aws](), [aws-outposts](), [cloud](), [compute](), [connectx](), [data-processing](), [enterprise](), [governance](), [latency](), [low-latency](), [networking](), [security]() ### AI overview AWS has generally released a second-generation single-rack AWS Outposts configuration: a self-contained 42U rack combining compute, storage, and networking with up to 2,688 vCPUs and 100 TB of Amazon EBS. The article describes its on-premises cloud compatibility, compact footprint, supported instance families, and accelerated networking options for trading floors and 5G cores. ### Source excerpt AWS has made second-generation single-rack AWS Outposts generally available, a self-contained 42U rack that puts compute, storage, and networking together with up to 2,688 vCPUs and 100 TB of Amazon EBS. It runs the same APIs, console, automation, governance policies, and security controls as the multi-rack second-generation Outposts and the parent AWS Region, so an The post Second-Gen Single-Rack AWS Outposts Puts 2,688 vCPUs and 100TB of EBS in One 42U Rack appeared first on StorageReview.com. ## AI x QA Leadership Summit 2026: Building the AI-Native QA Engine DevFeed: [AI x QA Leadership Summit 2026: Building the AI-Native QA Engine]() Original publisher: [Read original article]() Author: Shweta Chhillar Published: 2026-09-11T06:34:59Z Content type: article Language: en Sources: [BrowserStack Blog]() Topics: [Testing](), [AI Strategy](), [Artificial Intelligence]() Tags: [2026](), [ai](), [events](), [free](), [governance](), [leadership](), [practitioner](), [qa](), [quality-engineering](), [september-2026](), [summit](), [virtual-event](), [workflow](), [workshops]() ### AI overview BrowserStack's 11th QA Leadership Summit is a free virtual event on 23 September 2026. It offers separate tracks on AI strategy and governance for QA leaders and applied AI testing skills for practitioners, with the theme "Building the AI-Native QA Engine." ### Source excerpt BrowserStack's 11th QA Leadership Summit runs 23 September 2026, free and virtual. Two tracks: AI strategy and governance for QA leaders, applied AI testing for practitioners. Speakers from AWS, Amazon, Atlassian, KPMG and S&P Global. ## Redefining Digital Resilience in the AI Era DevFeed: [Redefining Digital Resilience in the AI Era]() Original publisher: [Read original article]() Author: Kamal Hathi Published: 2026-09-10T17:00:15Z Content type: news Language: en Sources: [Cisco Blogs]() Topics: [Resilience](), [Artificial Intelligence](), [data](), [Architecture & Design](), [Security](), [SOC](), [monitor]() Tags: [agentic-ai-security](), [agentic-ops](), [agentic-security](), [ai](), [ai-agents](), [autonomous](), [cost](), [digital-resilience](), [executive-platform](), [governance](), [monitor](), [observability](), [resilience](), [scale](), [security](), [soc](), [speed](), [workflows]() ### AI overview Splunk is evolving its data platform for the AI era, focusing on digital resilience, trusted autonomous agents, machine-speed security operations, and economically governed AI workflows. ### Source excerpt Splunk is evolving for the AI era - removing constraints to help customers achieve digital resilience and leverage AI with speed, scale and trust. ## 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. ## Unifying governance across engines and catalogs in the Open Lakehouse DevFeed: [Unifying governance across engines and catalogs in the Open Lakehouse]() Original publisher: [Read original article]() Author: Daniel Weeks; Ryan Blue; Andrei Tserakhau Published: 2026-09-10T15:05:10Z Content type: article Language: en Sources: [Databricks]() Topics: [Apache Iceberg](), [data](), [databricks](), [Apache Spark](), [DuckDB]() Tags: [apache](), [apis](), [catalog](), [data](), [databricks](), [duckdb](), [governance](), [open](), [product](), [spark]() ### AI overview The article examines two additions to the Apache Iceberg REST Catalog specification: read restrictions and catalog labels. It explains how they support governance across catalogs and engines, including centralized and delegated enforcement, and discusses trust requirements for engines such as Spark, DuckDB, and Trino. ### Source excerpt In our previous posts, we showed how open table formats, open APIs and unified governance... ## Agent Harness vs Platform Harness: Why Teams Need Both DevFeed: [Agent Harness vs Platform Harness: Why Teams Need Both]() Original publisher: [Read original article]() Author: Zohar Einy Published: 2026-09-10T04:47:42Z Content type: article Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [Agent Harness](), [AI Engineering](), [AI Agent](), [Orchestration](), [Software]() Tags: [agentic](), [ai-agent](), [ai-engineering](), [article](), [governance](), [memory](), [orchestration](), [platform](), [tools]() ### AI overview This article distinguishes between an agent harness, which wraps a model with prompts, tools, orchestration, memory, and guardrails, and a platform harness, which adapts an agent to an organization's systems, standards, skills, tools, and governance requirements. It explains why teams need both layers and why vendor-agent adopters should build the platform harness first. ### Source excerpt Agent harness vs platform harness: what each layer covers, who owns it, what breaks when you have only one, and why you need both. ## Five AI Questions We're Hearing from Financial Services Leaders DevFeed: [Five AI Questions We're Hearing from Financial Services Leaders]() Original publisher: [Read original article]() Author: Junta Nakai; Erin Butler; Roshni Joshi; Antoine Amend; Jennifer Miller; Andrea DeSosa; Rajaram Suresh; Kim Hatton; Naeem Rehman; Spencer Cook Published: 2026-09-09T18:09:29Z Content type: article Language: en Sources: [Databricks]() Topics: [Artificial Intelligence](), [databricks](), [audit trail](), [tokenization]() Tags: [2026](), [agentic-ai](), [ai](), [audit-trail](), [banking](), [compliance](), [data](), [databricks](), [financial](), [financial-services](), [governance](), [reconciliation](), [regulatory]() ### AI overview The article presents five questions that financial-services leaders are asking about trustworthy AI. It highlights governance, compliance, auditability, governed data, liquidity, reconciliation, tokenized settlement, financial-crime controls, and human oversight, with Databricks describing examples for banking operations. ### Source excerpt Last year at Sibos Frankfurt, the question was whether AI works. This year: can your... ## Evolving With Agentic Risk: Updating Our Integrated AI Security & Safety Framework DevFeed: [Evolving With Agentic Risk: Updating Our Integrated AI Security & Safety Framework]() Original publisher: [Read original article]() Author: Amy Chang Published: 2026-09-09T17:59:22Z Content type: article Language: en Sources: [Cisco Blogs]() Topics: [Artificial Intelligence](), [Securing AI](), [ai security](), [prompt injection](), [Responsibility & Safety](), [Jailbreak]() Tags: [agentic](), [ai](), [ai-security](), [artificial-intelligence-ai](), [governance](), [jailbreak](), [policy](), [prompt-injection](), [safety](), [security]() ### AI overview The article announces v2 of an integrated AI safety and security taxonomy. It introduces Agentic Autonomy Failures to address risks arising when agents plan, use tools, run code, move money, delegate work, expand permissions, replace goals, or manipulate success metrics. It also merges prompt injection and jailbreak into a unified treatment because their classification and defenses substantially overlap. ### Source excerpt Nine months ago, we introduced the Integrated AI Safety and Security Framework as a unified and comprehensive taxonomy to help organizations identify and mitigate the security and safety risks unique to AI systems. Existing frameworks remained..... [Next page]()