← Back to reports library

2025 AI Guide Expansion Plan

Zeph Tech is adding four evidence-based guides to the AI pillar. Each playbook extends the nightly briefings into operational programmes with structured controls, sourcing, and measurement cadences. The outlines below catalogue section sequencing, primary…

AI Program · Coverage focus 2025 · Updated November 14, 2025

Zeph Tech is adding four evidence-based guides to the AI pillar. Each playbook extends the nightly briefings into operational programmes with structured controls, sourcing, and measurement cadences. The outlines below catalogue section sequencing, primary source material, and search targets to anchor distribution.

Model Evaluation Operations Guide

  • Working title: “AI Model Evaluation Operations Playbook — Scaling Assurance Across Frontier and Domain Models”
  • Audience: Chief AI officers, evaluation leads, ML platform teams, and governance stewards who must evidence safety, robustness, and compliance across general-purpose and high-risk AI systems.
  • Outline: 1. Executive summary and change log 2. Regulatory and standards backdrop (EU AI Act risk management, ISO/IEC 42001 Clause 8, NIST AI RMF Measure function) 3. Evaluation operating model (roles, independence requirements, committee structures) 4. Test coverage portfolio (functional, safety, adversarial, robustness, fairness) 5. Data and tooling governance (benchmark provenance, scenario design, synthetic data controls) 6. Continuous evaluation pipelines (CI/CD integration, telemetry, gating policies) 7. Reporting and evidence packs (Annex IV/Annex VIII artefacts, OMB Appendix C submissions) 8. Scaling considerations (GPU scheduling, third-party labs, shared assurance exchanges) 9. Implementation roadmap and maturity diagnostics
  • Primary sources:
  • Regulation (EU) 2024/1689 — EU AI Act Articles 9, 53, 55, 56, Annexes VIII & IX.
  • NIST AI Risk Management Framework 1.0 (January 2023).
  • ISO/IEC 42001:2023 Artificial Intelligence Management System requirements.
  • UK AI Safety Institute “Inspect” evaluation platform documentation (October 2024 release).
  • U.S. AI Safety Institute Consortium (AISIC) Charter and evaluation profiles (February 2024).
  • U.S. OMB Memorandum M-24-10 Appendix C evaluation expectations (March 2024).
  • SEO targets:
  • Primary keyword: “AI model evaluation framework”
  • Secondary keywords: “AI safety testing operations”, “EU AI Act Annex VIII evaluations”, “AISIC benchmarking”, “NIST AI RMF Measure function”.

AI Procurement Governance Guide

  • Working title: “AI Procurement Governance Blueprint — Contracts, Assurance, and Lifecycle Controls”
  • Audience: Chief procurement officers, legal teams, CAIOs, and third-party risk leaders negotiating AI services and model licences.
  • Outline: 1. Executive summary and enforcement timeline highlights 2. Policy drivers (EU AI Act Articles 28–30, U.S. OMB M-24-10 Sections 8–9, UK Crown Commercial Service guidance) 3. Intake and screening (use-case scoping, risk tiering, conflict checks) 4. Due diligence (technical evaluation, security/privacy reviews, workforce impact review) 5. Contracting controls (performance guarantees, transparency rights, audit clauses) 6. Supplier monitoring and change management (model updates, retraining notifications, incident escalation) 7. Public sector alignment (GSA AI marketplace, Defense acquisition guardrails, reporting obligations) 8. Metrics, dashboards, and assurance evidence (Annex IV artefacts, procurement scorecards) 9. Implementation roadmap and maturity progression
  • Primary sources:
  • Regulation (EU) 2024/1689 — Articles 25–30, Annex IV requirements for providers and deployers.
  • U.S. OMB Memorandum M-24-10 Sections 5, 8, 9 (March 2024).
  • UK Government “AI Procurement: A Guide for Public Bodies” (Government Digital Service/Crown Commercial Service, 2019).
  • U.S. General Services Administration AI Center of Excellence marketplace criteria (2023 refresh).
  • DoD Chief Digital and Artificial Intelligence Office (CDAO) Responsible AI Toolkit (2022).
  • NIST Special Publication 1270 “Towards a Standard for Identifying and Managing Bias in AI” (March 2022) for vendor assessments.
  • SEO targets:
  • Primary keyword: “AI procurement governance”
  • Secondary keywords: “AI contract clauses”, “OMB M-24-10 supplier requirements”, “EU AI Act provider obligations”, “AI third-party risk management”.

AI Incident Response and Resilience Guide

  • Working title: “AI Incident Response and Resilience Runbook — Meeting 24-Hour Reporting and Post-Market Monitoring Duties”
  • Audience: Security operations leaders, CAIOs, legal, and risk executives orchestrating cross-functional AI incident handling.
  • Outline: 1. Executive overview and drivers for AI-specific incident response 2. Regulatory landscape (EU AI Act Articles 62–75, U.S. OMB M-24-10 Section 7, CIRCIA developments) 3. Incident taxonomy and materiality thresholds (serious incidents, systemic risk events, safety breaches) 4. Detection engineering and monitoring (telemetry, guardrails, anomaly detection) 5. Response lifecycle (triage, containment, eradication, recovery, customer/regulator comms) 6. Reporting obligations (EU AI Office portals, NIST incident documentation, sector regulators) 7. Post-incident reviews and continuous improvement (lessons learned, model adjustments, audit trails) 8. Integration with enterprise resilience (BIA linkages, tabletop exercises, supplier coordination) 9. Implementation roadmap and readiness scorecards
  • Primary sources:
  • Regulation (EU) 2024/1689 — Articles 62, 72–75 on post-market monitoring and serious incident reporting.
  • U.S. OMB Memorandum M-24-10 Section 7, Appendix B.
  • Cyber Incident Reporting for Critical Infrastructure Act (CIRCIA) 2022 implementation updates from CISA (2024 notices).
  • NIST SP 800-61 Revision 2 Computer Security Incident Handling Guide.
  • CISA/NSA/NCSC “Guidelines for Secure AI System Development” (April 2024).
  • UK AI Safety Institute systemic risk reporting commitments (Bletchley Declaration follow-on statements, 2024).
  • SEO targets:
  • Primary keyword: “AI incident response plan”
  • Secondary keywords: “EU AI Act serious incident reporting”, “OMB M-24-10 24-hour notification”, “AI post-market monitoring”, “AI resilience tabletop”.

Workforce Enablement for AI Transformation Guide

  • Working title: “AI Workforce Enablement and Safeguards Guide — Training, Engagement, and Accountability”
  • Audience: HR leaders, learning & development teams, CAIO offices, and transformation executives scaling AI capabilities with workforce protections.
  • Outline: 1. Executive overview linking AI strategy to workforce commitments 2. Policy context (U.S. Department of Labor AI principles, EU AI Act transparency duties, OECD AI guidelines) 3. Skills and capability mapping (role segmentation, competency frameworks, baseline assessments) 4. Training and adoption programmes (learning journeys, human-in-the-loop practices, safety drills) 5. Worker protections and governance (contestability, privacy, health and safety integration) 6. Change management and communication (engagement plans, unions/works councils, metrics) 7. Procurement and vendor alignment (HR tech diligence, transparency clauses, monitoring) 8. Measurement and reporting (well-being metrics, productivity, retention, regulatory disclosures) 9. Implementation roadmap and maturity scoring
  • Primary sources:
  • U.S. Department of Labor “Artificial Intelligence and Worker Well-Being: Principles for Developers and Employers” (July 2024).
  • ISO/IEC 42001:2023 Clauses 5, 7, 8 for competence and awareness.
  • OECD “Guidelines on AI and Responsible Business Conduct” (June 2023 update).
  • International Labour Organization “Generative AI and Jobs: A global analysis” (August 2023).
  • UNESCO “Guidance for generative AI in education and research” (September 2023).
  • EU AI Act Article 52 transparency obligations for deployers.
  • SEO targets:
  • Primary keyword: “AI workforce enablement”
  • Secondary keywords: “worker-centered AI principles”, “AI change management”, “AI skills development”, “responsible automation training”.

Next steps

  1. Draft ≥3,000-word templates for each guide in zephtech-site/templates/pages/guides/ with accurate metadata, structured data, and cross-links to the briefings referenced above.
  2. Update guides/index.html.j2 structured data, navigation, and cards to incorporate the four new guides and surface the linked briefings.
  3. Extend the AI pillar landing page to feature the expanded guide catalogue and connect to the relevant research briefs.
  4. Rebuild the static site, regenerate the sitemap, and confirm the new guide URLs are listed for search indexing.