All news with #ai governance tag

🔒 The 2026 AI Cybersecurity Summit addresses the widening gap between rapid AI adoption and lagging security by focusing on practical, deployment-stage risk management. Speakers and sessions will explore visibility, governance, and layered protections across GenAI tools, custom models, APIs, and agentic systems. Attendees will receive operational guidance to secure AI as it moves from experimentation to production. The summit emphasizes integrating security, infrastructure, and operations to reduce accumulating risk.

🤖 RSA 2026 highlighted a rapid, industry-wide shift toward AI-driven security, with CISOs clustering into three archetypes—proactive, curious/confused, and blissfully ignorant. Vendors stressed the need to build AI foundations (data/context engines, control planes, execution layers) and then layer agents atop them. Microsoft, legacy security vendors, and AI-native startups all showcased approaches, while pricing, governance, and evolving threats remain open challenges.

🔐 In this episode of the Talos Threat Perspective, Hazel Burton examines how identity is being used to gain, extend, and maintain access inside environments. Drawing on the 2025 Talos Year in Review, the video outlines how attackers target identity systems and MFA workflows, establish persistent high-trust access, and use internal phishing to move laterally. It also explores risks from over-permissioned AI agents and identity-linked access, and how adversaries blend into normal user behaviour, complicating detection and containment.

🔍 CISOs should treat AI outputs as drafts, keep humans in the loop for high‑stakes decisions, and demand traceability from vendors before accepting compliance or control assessments. The story cites practitioners who stress-test models for consistency, measure hallucination and drift rates over time, and validate AI findings against scanners and penetration testing. It warns against automated regulatory mapping without technical verification and emphasizes audit trails, human signoff, and vendor proof as essential controls.

🛡️ Treat AI like a very new, junior employee and as software: it’s capable but not infallible, so give clear goals, explicit permissions, and limit its authority. Apply distinct identities and least-privilege controls, avoid relying on AI for deterministic access decisions, and test for indirect prompt injection (XPIA) using techniques such as Spotlighting and Prompt Shield. Design end-to-end systems that include people and processes, document safety plans and failure modes, and continuously monitor and vet models and agents for changes.

🔒Over the past four years organizations have been increasingly challenged by threats that originate in third-party networks, with more than 35% of breaches tied to compromised vendors or partners. International conflict, generative AI and growing supply-chain exposure are accelerating risk and extending impact to Operational Technology (OT) and IoT environments. Leaders should elevate OT risk to the board, adopt immutable 3-2-1-1 backup strategies, and establish an AI Risk Council to enforce governance and pentesting before broad AI adoption.

🔒 RSA Conference 2026 made clear that AI dominated every conversation, reframing priorities for CISOs and security teams. Sessions and hallway discussions emphasized securing the AI stack, managing rampant shadow AI usage, and governing machine or non-human identities. Speakers warned that AI accelerates both attacks and defensive response, while capital and workforce dynamics are shifting rapidly.

🤖 Enterprise GRC teams often have the technical capability to deploy agentic AI but stall over a deeper concern: identity and role. Agents can replace operational tasks—evidence gathering, control testing, remediation tracking—but they still require human-defined logic for risk appetite, remediation criteria, and context. Anecdotes builds agentic GRC that automates operations while relying on practitioner judgment. The outcome is an opportunity for practitioners to reclaim time to focus on true risk management rather than program maintenance.

🔒 Shadow AI — the unapproved use of AI tools and embedded AI features — is proliferating as employees seek productivity gains and vendors quietly enable capabilities. CISOs should first assess data sensitivity, storage practices and whether corporate inputs are being used to train models. After evaluating risk, organizations must choose to block or formally integrate tools and apply mitigations such as filtering, acceptable-use policies and targeted employee education. Clear governance, cross-functional review and simple approval pathways help balance innovation with security without unduly punishing productive behavior.

🗳️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.

🔐 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.

🧭 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.

🚨 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.

🤖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.

🔐 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.

🚀 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.

🔍 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.

🇨🇦 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.

🛡️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.

🤖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.