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How new AI security vendors handle brand-misspell search queries: alternateName JSON-LD schema, redirected misspell domains, branded content clusters, and Search Console attribution. Practical SEO playbook with examples and citations to Google Search Central, Schema.org, and John Mueller statements.
Worked cost model for a single shadow-AI data breach in a mid-market regulated US organisation. Starts from the IBM Cost of a Data Breach Report 2025 baseline ($4.88M US average), then layers AI-specific cost factors: longer dwell time, EU AI Act and GDPR penalty exposure, HIPAA Tier 4 fines, and reputation harm. Sources: IBM, Ponemon, EU AI Act, HHS, NIST AI RMF.
Practical playbook for governing generative AI across clinical and operational workflows in US healthcare: ambient clinical documentation, claims and coding, patient communication, research, and administrative ops. Covers HIPAA Privacy Rule, Security Rule, BAA expectations, HHS guidance, ONC interoperability obligations, and per-workflow control patterns. 45 CFR 164 referenced throughout.
Defensive-SEO field notes for AI security and governance vendors. PBN patterns targeting the AI-security category (rank-your.*, buybacklinks.*, link-farm clusters), what a disavow operation actually involves, and the SEO and brand-trust cost of doing nothing. Cites John Mueller statements on the disavow tool, Ahrefs DR documentation, and Bing Webmaster Tools.
A monthly roundup of AI governance developments as of May 2026: EU AI Act enforcement nine months after high-risk obligations landed, the Colorado AI Act's February 2026 effective date in operation, California SB-942 disclosures, Singapore AI Verify adoption, and the one-year mark of NIST AI 600-1. Cites the EU AI Act Service, NIST, IAPP, and the OECD AI Policy Observatory.
A practical 30/60/90 day playbook for CISOs standing up AI governance: 30 days of discovery and shadow AI audit, 60 days of policy, DLP, and audit baseline, 90 days of compliance mapping and tabletop. Includes checklists by phase and references to NIST AI RMF, ISACA's AI Audit Toolkit, CSA's MLSecOps work, and IAPP.
A defender-focused deep dive into prompt injection as of 2026. Real attack patterns (direct, indirect via retrieval, multi-turn, payload smuggling), concrete defences (input sanitisation, output validation, structured prompting, policy enforcement at the boundary), and authoritative source mapping to OWASP Top 10 for LLM Applications (LLM01), NIST AI 600-1, MITRE ATLAS, and the work of Simon Willison.
A practical guide to building the AI red team capability most enterprises are missing in 2026. What an AI red team is, how it differs from a traditional red team, the hiring versus outsourcing decision, a 90-day starter plan, the exercises to run first, and how it all maps to NIST AI 100-1, NIST AI 600-1, the AI Village at DEF CON, and the MLCommons AI Safety community.
A practitioner-focused brief on the FedRAMP 20x modernisation programme and what it changes for AI vendors selling to the US federal government in 2026. How 20x differs from legacy FedRAMP Moderate / High authorisations, where it intersects with OMB M-24-10 and M-24-18, what the new continuous-monitoring expectations look like, and what AI vendors need to start doing now.
A detailed 12-month roadmap to ISO/IEC 42001:2023 certification for AI Management Systems (AIMS). Four phases mapped to months 1-12 covering scope and gap analysis, policy and risk management, operations and monitoring, and audit preparation through Stage 1 and Stage 2. Comparison to ISO/IEC 27001 (overlap and differences), NIST AI RMF crosswalk, and a practical accreditation-body shortlist (ANSI/UL, BSI, DNV, SGS).
The Digital Operational Resilience Act (Regulation (EU) 2022/2554) has been in application since 17 January 2025. For financial entities now running generative AI in production, DORA quietly added a new set of obligations - around ICT third-party risk, incident reporting, resilience testing, and information sharing - that apply to every AI workload connected to a covered function. This deep dive maps how AI workloads sit inside DORA's five pillars, where the audit gaps emerge in practice, and how Areebi's audit trail and policy engine reduce the evidence burden.
The honest math on building an AI governance platform in-house versus buying one, and the realistic open-source middle path. Twelve-month total cost of ownership comparison for a 500-employee company, the criteria that make build the correct answer, the criteria that make buy the correct answer, and a decision framework you can hand to a CFO without losing the room.
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