All news with #ai governance tag

🧭 Microsoft announces the general availability of Microsoft Discovery, a platform for building and governing agentic AI workflows tailored to scientific and engineering R&D. The release includes a preview of the Microsoft Discovery app, a local desktop experience for researchers and small teams to explore hypotheses, literature, and iterative experimentation. The platform emphasizes evidence preservation, traceability, governance, and integration with existing tools and institutional data to support repeatable, transparent scientific workflows.

🧭 At Infosecurity Europe 2026, Bayer CISO Kevin Jones outlined a shift from checklist-based guidance to psychology-first security awareness to counter AI-enabled social engineering. The firm mandates behavior-focused training, ties AI access to role-based modules, and gates agent development behind completion. Bayer is moving SOCs toward supervised automation and updating supplier contracts and governance to enforce AI transparency and controls.

🔍 New research from ManageEngine reveals UK IT and business leaders view AI-powered cyber-attacks as their top risk over the next 12 months, with 43% identifying it as the single biggest threat. The survey of 1,500 decision-makers across five European markets shows 41% of UK respondents plan to prioritise spending on tackling AI and advanced threats. Despite strong detection rates, UK organisations report increasing incidents, skills gaps and recovery challenges, alongside rising investment in resilience and governance.

📝 This article analyzes the new SEC 10-K cybersecurity disclosure section (1.C) across the top 200 S&P companies, summarizing governance, reporting lines, standards, and trends between 2024 and 2025. It highlights that the CISO remains the principal cybersecurity role, with the CIO commonly as the reporting executive and audit committees most frequently overseeing cyber risk. The piece also reviews common practices such as TPRM, proactive testing, human-centric training, AI risks, and the author’s AI-assisted data collection and analysis methods.

📰 Over eight years GDPR set global data-protection norms, notably the 72-hour breach notification standard, but nearly 40% of announced EU fines by value are annulled or under appeal. Experts say large tech firms contesting fines isn’t surprising and that rulings provide practical guidance for compliance teams. As the EU’s AI Act and proposed GDPR reforms arrive, regulators must shore up procedural robustness while organisations adapt governance to evolving AI risks.

🔍 The LayerX Security State of AI Usage Report 2026 finds enterprise AI risk is concentrated among a small set of power users and a few dominant platforms, while usage fragments across personal accounts, browser extensions, embedded copilots, and connectors. The study shows ChatGPT still dominates conversations, Copilot M365 is growing, and consumer AI like Gemini is often used via personal accounts. Shadow AI now spans a long tail of under-the-radar tools and extensions that evade corporate visibility and governance.

🛡️ CIOs rushing to deploy AI agents without visibility risk major failures; experts warn that observability and governance are required. Many organizations treat agents like RPA and set-and-forget systems, but agents operate in model runtimes and need end-to-end tracing, least-privilege permissions, and human-in-the-loop checks. Vendors and cloud providers offer tools, yet governance can become a bottleneck if it’s not scalable and actionable.

⚠️ Anne Keast-Butler, director of GCHQ, urged UK businesses to treat cybersecurity as national defence during the agency's first annual lecture at Bletchley Park on May 27. She warned that rapid AI development narrows the window to stay ahead of threats and called on boardrooms to act now. GCHQ plans a machine-speed national cyber defence using agentic AI within five years while urging adoption of basic controls and quantum-resistant cryptography.

🛡️ New RUSI research warns that adversaries, notably North Korea and Iran, are moving from AI-assisted to AI-enabled sanctions evasion and proliferation financing. The report highlights AI’s ability to mass-produce fraudulent documents, automate shell-company administration, and analyze blockchain flows to evade detection. Experts urge enterprises to adopt behavior-based analytics, defensive AI, stronger identity verification and updated training to counter these evolving threats.

🔒 More than two-thirds of UK businesses plan to increase cybersecurity spending over the next 12 months as AI adoption and geopolitical uncertainty reshape budgets. The Q1 2026 Barclays Business Prosperity Index found 68% of leaders expect higher cyber investment and 46% say new technologies raise their exposure. Large firms have led the increase, with average cyber spend hitting £505,000 so far in 2026, and cloud, cyber and AI account for 44% of planned tech budgets.

🛡️ New guidance from India's CERT-In urges organizations to remediate actively exploited internet-facing vulnerabilities within 12 hours, citing AI-driven acceleration of reconnaissance and exploitation. The document, published on May 25, maps how generative AI, LLMs and autonomous agents speed up vulnerability discovery, phishing and malware creation. It sets tiered timelines for remediation, recommends using the KEV catalog and EPSS for prioritization, and advises interim mitigations when patches are unavailable.

🚦The author argues that traditional post-hoc compliance reviews fail for AI because AI systems change continuously. Drawing on research into Chinese and EU approaches, the piece recommends embedding governance into CI/CD pipelines so model cards, data lineage and risk evaluations are generated and enforced as deployment gates. It also urges treating agent identity as first-class security control and positioning compliance as operational release infrastructure rather than a review layer.

🛡️ Security professionals at DTX argued that integrating AI into SOCs is now essential to counter autonomous attacker tooling and AI-accelerated threats. Panelists stressed sustaining core cyberdefence fundamentals—system hardening, patching, access control and monitoring—before deploying AI, and preserving human oversight to manage model risk. They noted role shifts toward validation, prompt engineering and GRC, and urged rigorous testing and SDLC-like deployment controls.

🔍 While many organizations intentionally deploy AI to improve productivity, unsanctioned AI is proliferating faster — employees install tools or vendors embed assistants into existing apps. The article defines four AI categories and maps specific detection techniques to each, covering DNS, web gateways/NGFW, EPP/EDR, application and browser controls, and SSPM/identity governance. It flags OAuth consent as a high-risk channel and summarizes admin steps for Microsoft Entra, Google Admin, Salesforce, and ServiceNow to block or restrict app access.

🔒 The UK’s National Cyber Security Centre (NCSC) has published new guidance for organisations considering the adoption of agentic AI, summarising a wider report produced with Five Eyes partners. It flags the heightened risk from agent autonomy and complexity, including excessive access, unpredictable behaviour and actions that can outpace human review. The NCSC advises incremental deployment with tightly bounded pilots, clear ownership, ongoing monitoring and meaningful human oversight, and points organisations to industry best practice such as ETSI EN 304 223.

⚠️ AI hallucinations—confident but incorrect outputs—are increasingly driving risky decisions in critical infrastructure and cybersecurity operations, exploiting human trust in authoritative-sounding responses. A 2025 AA-Omniscience benchmark of 40 models found most systems were more likely to offer a confident wrong answer on difficult questions, underscoring that AI outputs must be treated as potential vulnerabilities until vetted. Effective controls include enforced human review before sensitive actions, treating training data as a security asset, strict least-privilege for AI systems, and prompt-engineering training to reduce ambiguous inputs.

🔐 The ICO has published a five-step guide urging organisations to prepare for AI-enhanced cyber threats, including deepfake social engineering, adaptive malware and automated exploitation. It points readers to the NCSC's updated Cyber Assessment Framework and expects baseline adoption of Cyber Essentials and the UK Cyber Governance Code. The guidance emphasises robust patching, MFA, least‑privilege, supply‑chain vetting, DPIAs for high‑risk AI and human oversight of AI-enabled defences.

🔒 The updated AWS User Guide to Governance, Risk, and Compliance for Responsible AI Adoption provides Financial Services customers practical GRC guidance for deploying AI responsibly. It covers governance, risk management, compliance, data and model management, and AI agent oversight, and maps these considerations to AWS capabilities. The guide highlights services such as Amazon Bedrock AgentCore, Bedrock Guardrails, Bedrock Agents, SageMaker Autopilot, and SageMaker Model Monitor. It complements existing AWS responsible AI and Well-Architected resources and is available on the AWS Whitepaper portal.

🏥 The post argues that modern cloud infrastructure is the superior foundation for regulated Software as a Medical Device (SaMD), enabling faster innovation while meeting regulatory obligations. It outlines regulatory shifts in early 2026, including the FDA's QMSR alignment with ISO 13485 and the EU AI Act's applicability for high-risk systems. The author advocates Compliance as Code and describes three architectural planes—data, control, and evidence—on Google Cloud to deliver continuous audit readiness. It also highlights AI-driven monitoring and a shared fate model between cloud providers and manufacturers.

🔍 A G7 Cybersecurity Working Group paper published on 12 May defines minimum elements for software bills of materials (SBOMs) tailored to AI systems, aiming to boost transparency across AI supply chains. It outlines seven clusters — Metadata, System Level Properties, Models, Dataset Properties, Key Performance Indicators, Infrastructure and Security Properties — to guide producers and users. The guidance stresses clusters are non-mandatory, that SBOMs alone are insufficient, and recommends linking SBOMs to vulnerability, advisory and tooling ecosystems.