Articles
Practical advisory articles on AI strategy, operating, and execution. Decision-ready guidance for leaders building durable AI capability.
Use-Case Scoring for CFOs: Impact × Feasibility ×Risk
A practical scoring model for CFOs to tie AI investments to unit economics, control requirements, and risk management.
Signal Packs for Prioritization: Market, Ops, andRisk
Use curated external and internal signals to re-rank your AI portfolio every quarter. Market, operational, and risk signals combined for sharper decisions.
Risk & Ethics Training for Non-DataTeams
Deliver short, role-based AI risk and ethics training for non-data teams to ensure safe usage, compliance, and escalation readiness.
Responsible AI Policy Kit in OneWeek
A sprint plan to ship policies, role assignments, and lightweight controls that unblock AI delivery without stalling innovation.
Regulatory Readiness AcrossJurisdictions
Map AI governance controls to global regulatory frameworks and prepare documentary evidence for audits and inspections.
Privacy by Design: PII/PHI Safe Zones for AI
Segment risk with safe zones, tokenization, and dynamic policy enforcement to enable compliant AI delivery across PII/PHI.
Org Design for AI: Roles, RACI, andTalent
Define control-plane roles, delivery pods, and clear accountabilities to operate AI safely and at speed. Practical RACI, team topologies, and hiring guidance.
Model Risk Management for GenerativeSystems
Adapt traditional Model Risk Management to generative AI: address hazards, testing, monitoring, and change control for LLMs and other advanced models.
Minimal Viable Data Posture forExecutives
What’s truly required to unlock 70% of priority AI use cases in months, not years, with a minimal viable data posture.
Metadata & Lineage as the ControlPlane
Operationalize metadata and lineage as a control plane for trust, governance, and compliance in AI data ecosystems.
Measuring Cycle-Time & QualityUplift
Define leading indicators and guardrails to capture value early. Measure time-to-decision, right-first-time, exception rate, and rework to prove AI impact.
Incentives & Performance: Rewarding AIOutcomes
Tie compensation and recognition to measurable AI-driven outcomes such as cycle-time reduction, quality improvements, and adoption rates.
Frontline AI: Safety, Maintenance,Scheduling
How frontline AI copilots can drive safety compliance, proactive maintenance, and optimized scheduling across industries. Practical plays to reduce downtime and risk.
Productivity Baselines: Measure the Tax Before You Cut It
Cost-out programs misfire when teams have not measured the baseline. The pre-program week that prevents painful surprises and locks in real productivity gains.
From Pilots to Platforms: Consolidating AIFoundations
Reduce duplicate tooling and fund shared AI platforms that speed delivery across lines of business. A practical path from scattered pilots to scalable foundations.
Explainability & Human-in-the-LoopStandards
Define decision-use thresholds, escalation paths, and override logging to ensure AI systems remain explainable and accountable.
Event Pipelines Without Regret: IngestionPatterns
Design event ingestion pipelines with late-binding semantics, idempotency, and replayability to ensure resilient AI data flows.
Knowledge-Base Hygiene: A 30-Day Sweep Before AI GoesLive
Most retrieval-augmented systems underperform because the knowledge base is the bottleneck. A four-week sweep that fixes content quality before the model touches it.
Enablement Kits: From Prompts toPlaybooks
Equip teams with reusable prompts, proof libraries, and structured playbooks to drive safe, consistent AI delivery.
Decision-Centric Reviews: Operating the AIFactory
Turn status meetings into decision forums with owners, options, and gates. Run your AI portfolio like a factory with measurable throughput and quality.
Data Products: Ownership, SLAs, andContracts
Shift from tables to products with explicit ownership, service-level objectives, interfaces, and financial chargeback to drive reliable AI delivery.
Change Comms that CreatePull
Position AI as a capability, not just tooling. Use before/after storytelling with real work examples to inspire adoption.
Capital Cadence: Quarterly Gates That ActuallyWork
Design quarterly stage gates and reallocation rights that reward evidence, not momentum. A practical cadence for moving capital at the speed of proof.
Back-Office Copilots: 12 Plays in Finance, HR,Legal
Twelve actionable plays to deploy AI copilots across finance, HR, and legal. Target high cycle-time, high-error processes first and measure time-to-decision.
Automation Guardrails: Access, Approval,Audit
Design control points for safe autonomy without stalling the work. Build layered guardrails across access, approval, and audit to balance speed and safety.
Strategic AI Roadmapping &Prioritization
Advisory articles for building and operating an AI roadmap: portfolio definition, CFO scoring, quarterly capital gates, platform consolidation, and signal-based prioritization.
AI-Driven Workflow & ProcessRedesign
Advisory articles on operating models and automation in the flow of work: back-office copilots, frontline AI, decision-centric reviews, value measurement, and automation guardrails.
AI Thesis to Portfolio: 90-DayRoadmapping
Turn AI themes into a ranked use-case portfolio in 90 days with bet statements, funding cadence, and measurable value tracking.
Responsible AI Governance &Compliance
Advisory articles for launching and operating Responsible AI governance: policy kits, MRM for generative AI, explainability & HITL, incident response, and multi-jurisdictional readiness.
AI Incident Response: Detection toDisclosure
Playbooks for AI-specific incidents including drift, leakage, jailbreaking, and model failure — from detection through disclosure.
Data Readiness & ArchitectureModernization
Advisory articles on executive data posture, data products, event ingestion, metadata & lineage, and privacy-by-design safe zones for AI.
Change Management & WorkforceEnablement
Advisory articles on org design for AI, enablement kits, change communications, incentives & performance, and risk & ethics training for non-data teams.