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All news with #ai governance tag

403 articles · page 12 of 21

AI Regulation Emerges as Central Issue in U.S. Midterms

🗳️The December Trump executive order constrains state AI regulation by directing federal lawsuits and withholding funds from states that attempt limits, effectively prioritizing industry interests over local consumer protections. Polling in 2025 shows broad bipartisan support for greater state and federal oversight, yet the order reshapes political fault lines ahead of the midterms. Candidates may use AI as a wedge—highlighting job displacement, datacenter opposition, and corporate concentration—while organizers work to broaden the debate beyond local fights.
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Cybersecurity, AI, and Sovereignty: Next for Infrastructure

🔐 At the World Economic Forum’s Industry Strategy Meeting in Munich, leaders explored how rapid AI deployment and rising data sovereignty pressures are reshaping digital infrastructure and investment. The piece argues that cybersecurity must be embedded from day zero to enable trusted data exchange, interoperability between sovereign systems, and secure distributed AI. It highlights the shift from large general models toward specialized, context-aware architectures and notes Fortinet’s role in public-private collaboration to operationalize secure systems.
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Governing AI Agent Behavior Across Intent Layers Guide

🧭 This article presents a practical framework for governing AI agents by aligning user, developer, role-based, and organizational intent. It prescribes a precedence model—organization, role, developer, then user—to resolve conflicts and preserve security and compliance. The authors illustrate expected agent behaviors (refuse, escalate, clarify, or proceed) and advocate for guardrails, least-privilege access, continuous evaluation, telemetry, and human-in-the-loop controls to sustain safe, reliable agent operations.
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Majority of Cyber Staff Uncertain How to Shut Down AI

🚨 New ISACA research finds that 56% of IT and cybersecurity professionals cannot say how quickly they could shut down AI systems after a cyber-attack or security incident. The global survey of over 3,400 security and digital professionals found just 32% believe they could halt compromised AI within an hour, and 7% expect it would take longer. Respondents reported confusion over AI ownership, with many unsure who is accountable, limited human oversight of AI actions, and mixed confidence in their organisation's ability to investigate and explain serious AI incidents.
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Five Priorities CISOs Must Address at RSAC 2026 Summit

🤖RSA Conference 2026 reframes AI from a single track to the event itself, with roughly 40% of sessions AI-weighted and artificial intelligence woven across identity, cloud, threat intelligence and human-focused tracks. CISOs face a dual mandate: accelerate AI adoption to remain competitive while protecting the enterprise from new attack surfaces such as RAG pipelines, vector databases, prompt injection and model inversion. Key priorities at RSAC include securing the AI stack, defining AI governance and compliance (including preparation for the EU AI Act), managing non‑human identities, mitigating shadow AI and AI-assisted coding risks, and preparing SOCs for autonomous remediation.
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Cybersecurity, Trust, and the Law: Governance Shift

🔐 In a March 2026 episode of Brass Tacks, Professor Oreste Pollicino argues that cybersecurity has transitioned from a technical specialty to a constitutional concern that underpins trust and fundamental rights. He warns that fear-driven enforcement undermines cooperation and urges regulators to act as mediators by fostering dialogue, literacy, and mutual learning with the private sector. The episode advocates governance over punishment, calls for harmonization rather than uniformity, and supports naming accountable individuals to enable communication instead of creating scapegoats.
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Microsoft, NVIDIA Expand Azure AI Infrastructure and Foundry

🚀 Microsoft and NVIDIA announced deeper integration at NVIDIA GTC, extending Microsoft Foundry to support NVIDIA Nemotron models and to simplify building production agents. New Azure AI infrastructure optimized for inference and reasoning will bring Vera Rubin NVL72 into liquid‑cooled datacenters and add initial support on Azure Local. Foundry Agent Service, Control Plane observability and a Voice Live API preview aim to accelerate prototype‑to‑production paths, while Fabric–Omniverse links and a public Physical AI Toolchain support simulation‑to‑operations workflows.
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Shadow AI Is Everywhere — Find and Secure It Today

🔍 Nudge Security provides continuous discovery, monitoring, and governance for shadow AI, delivering a Day One inventory of every AI app and account introduced into an organization. A lightweight IdP integration analyzes machine-generated SaaS emails (without storing content) to detect account creation, password changes, and security setting updates. An optional browser extension monitors AI conversations, flags sensitive data and file uploads, visualizes data flows, and issues real-time nudges and configurable alerts to guide users toward approved tools and enforce acceptable use.
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Canada Should Build a Nationalized Public AI Platform

🇨🇦 The Carney administration's $2‑billion Sovereign AI Compute Strategy forces a fundamental choice about where AI value and control will reside. Bruce Schneier warns that initiatives like OpenAI's “OpenAI for Countries” could simply transfer benefits and authority to U.S. tech firms, citing the Tumbler Ridge incident and private secrecy. He advocates for a publicly funded, transparent national AI—modeled on Switzerland's Apertus—to serve healthcare, education, transit, and democratic oversight rather than private profit.
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Five-Step Strategy to Manage Shadow AI Risks for the Enterprise

🛡️AI adoption has outpaced controls, creating widespread "shadow AI" risk that can expose sensitive data, distort decisions and create compliance gaps. The article recounts an incident where a product manager accidentally pasted production API keys into a public model, triggering outbound alerts. It presents a five-step program grounded in the NIST AI Risk Management Framework: inventory and discover AI use, standardize assessments, deploy layered defenses (DLP and AI monitoring), enforce human-in-the-loop checks, and tie risk reduction to business value.
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Gemini for Government Adds Agent Designer on GenAI.mil

🤖Agent Designer is now available within Gemini for Government on GenAI.mil, enabling Department of Defense civilian and military personnel to build customized AI agents for unclassified tasks using natural language. This no-/low-code platform lets users automate repetitive, multi-step administrative workflows—such as drafting meeting read‑aheads, extracting action items, or breaking projects into task checklists—without programming skills. Google Public Sector is supporting the rollout with training and office hours run in partnership with the U.S. Chief Digital and Artificial Intelligence Office to accelerate adoption and responsible use.
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Preparing Your SOC for Agentic AI: Four Key Actions

🤖 Organizations must prepare SOCs for agentic AI by reskilling staff, redesigning processes, and instituting governance to ensure safe autonomous operations. The piece explains that AI is already augmenting alert triage, enrichment, IOC validation and initial containment, and could soon handle more complex tasks like incident investigation and response. It recommends new roles—content engineers, data architects and orchestration platform engineers—and stresses auditability, least-privilege, red-teaming and clear approval thresholds for autonomous actions.
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Anthropic vs. Pentagon: AI Supply, Ethics, and Policy

⚖️ The Pentagon’s removal of Anthropic from US defense contracts, and the swift substitution by OpenAI, marks a high-profile clash over AI use for military and surveillance purposes. Anthropic refused DoD terms that would permit mass surveillance or fully autonomous weapons, provoking political backlash and a presidential order halting its federal partnerships. OpenAI has agreed to supply classified systems, raising questions about vendor politicization and how safety commitments will be enforced. The episode underscores procurement power, potential legal battles, and the limits of corporate ethical posturing.
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EC-Council Adds Four AI Certifications and CISO v4

🔐 EC‑Council launched its Enterprise AI Credential Suite, introducing four role-aligned certifications—Artificial Intelligence Essentials (AIE), Certified AI Program Manager (CAIPM), Certified Offensive AI Security Professional (COASP), and Certified Responsible AI Governance & Ethics (CRAGE)—alongside an updated Certified CISO v4. The suite is structured around the proprietary Adopt, Defend, Govern (ADG) framework to build practical capability across AI adoption, security, and governance. EC‑Council positions the expansion as a response to growing AI risk exposure and a pronounced workforce reskilling gap.
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New RFP Template for AI Usage Control and Governance

🔒 A new RFP Guide for Evaluating AI Usage Control and AI Governance Solutions provides security teams with a practical framework to convert vague AI-governance goals into measurable procurement criteria. It emphasizes interaction-level inspection — governing the moment a prompt is typed or a file is uploaded — rather than cataloging every shadow app. The template forces vendors to demonstrate browser- and client-side visibility, real-time enforcement, and contextual policy controls. A scoring model across eight domains helps CISOs avoid legacy checkbox tools and evaluate readiness for agentic, browser-native workflows.
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GraphML and Digital Twins for Autonomous Telco Networks

🔗 Google Cloud describes using graph-based digital twins and GraphML to enable autonomous telecommunications networks that self-configure, self-optimize, self-heal and self-secure with minimal human intervention. The post outlines an integrated stack combining tf-GNN and NetAI's fine-tuned GNNs to model live topology and dependencies as input for deterministic root-cause analysis. A MasOrange PoC at MWC 2026 showcases managed AIOps driven by these models.
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AI Agents as Identity Dark Matter: Governance Risks

🔐 The article explains how Model Context Protocol (MCP)-driven AI agents are rapidly moving from chat assistants into enterprise workflows, creating an emergent class of non-human identities that often evade traditional IAM controls. It warns these agents gravitate to low-friction credentials—local accounts, long-lived tokens, and API keys—creating pervasive “identity dark matter.” The piece recommends pairing agents with human sponsors, enforcing dynamic, context-aware access, centralizing visibility and auditability, and applying consistent governance across hybrids to prevent privilege drift and regulatory blind spots.
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Standardized IAM Context Keys for AWS-Managed MCP Servers

🔐 AWS introduced standardized IAM context keys for its managed remote Model Context Protocol (MCP) servers so AI agents can operate with existing IAM credentials while enabling distinct governance controls. The two keys — aws:ViaAWSMCPService (boolean) and aws:CalledViaAWSMCP (string) — let you allow or deny MCP-initiated actions and restrict access to specific MCP servers. AWS will also simplify public endpoint authorization so AI calls use standard IAM permissions (no separate MCP actions) and plans to add VPC endpoint support for private-network enforcement and two-stage authorization.
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From Vibe Checks to Continuous Evaluation for AI Agents

🔎 Manual 'vibe checks' are unreliable for production AI agents; this article recommends adopting continuous evaluation (CE) to guard against regressions, hallucinations, and unseen edge cases. It outlines a practical engineering approach—separating discovery and defense modes—and demonstrates implementation patterns using Agent Development Kit (ADK), Vertex AI evaluation services, and Cloud Run. The guidance covers dataset design, automated rubrics, tool-trajectory metrics, shadow deployments, CI/CD gating, and distributed tracing to establish robust, auditable agent behavior.
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AWS Completes First ISO/IEC 42001:2023 Surveillance Audit

🔒 In November 2025, AWS completed its first surveillance audit for ISO/IEC 42001:2023 — the Artificial Intelligence Management System standard — with no findings. This follows AWS’s November 2024 announcement that several AI services, including Amazon Bedrock, Amazon Q Business, Amazon Textract, and Amazon Transcribe, were accredited under the standard. The successful no-findings outcome provides independent validation of AWS’s ongoing commitment to responsible AI practices and gives customers added assurance when building and operating AI applications on AWS.
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