Insights
Practical thinking on AI strategy, governance, and implementation. Written by consultants who've built and shipped enterprise AI — not just advised on it.
AI in Financial Services in 2026: What's Working, What Isn't, and Why
A practitioner's view of AI in financial services in 2026. What's delivering value, what's stuck in pilot, and where the opportunities are.
implementationAI Model Monitoring: Why It Matters and What to Track in Production
What to monitor when AI models are in production. Covers data drift, performance degradation, operational metrics, and alerting strategies.
governanceAI Governance: What It Is and How to Build a Framework That Works
How to build an AI governance framework that balances innovation with risk. Covers accountability structures, model risk management, and regulatory alignment.
strategyWhat Is Generative AI Consulting? (And What Makes It Actually Useful)
What generative AI consulting involves, how it differs from traditional AI advisory, and how to tell substance from hype in this rapidly evolving space.
implementationEnterprise AI Implementation: From Pilot to Production
How to move AI from pilot to production in the enterprise. Covers MLOps, change management, integration patterns, and the organisational shifts required.
marketAI and the Future of Work: What's Actually Happening Right Now
What AI is actually changing about work right now. Cuts through the hype to cover real impacts on roles, skills, productivity, and organisational design.
strategyHow to Build an AI Strategy That Actually Delivers
A practical framework for building an AI strategy that moves beyond pilots. Covers capability audits, use-case prioritisation, and governance foundations.
marketThe Family Office Guide to Building an AI Investment Thesis
How family offices can build an AI investment thesis. Covers deal sourcing, evaluation, portfolio construction, and family capital advantages.
strategyWhat Is AI Transformation? (And What It Actually Requires)
What AI transformation means in practice, why most transformation programmes fail, and the operating-model shifts required to make AI work at scale.
due diligenceAI Due Diligence: What PE Firms and Investors Need to Evaluate
A practical guide to AI due diligence for private equity firms and investors. Covers technical risk, data assets, IP defensibility, and team evaluation.
due diligenceHow to Evaluate an AI Company Before You Invest
A practical framework for evaluating AI companies before investing. Covers technical moats, data assets, team quality, market positioning, and risk factors.
due diligenceAI M&A Due Diligence: A Checklist for Acquirers
A structured checklist for AI due diligence in M&A transactions. Covers technical review, data assets, IP, team assessment, and regulatory exposure.
strategyWhat to Look for in an AI Consultant (And Red Flags to Avoid)
How to evaluate AI consultants. What separates credible advisors from vendor resellers, and the red flags that signal you should walk away.
strategyWhat Is an AI Readiness Assessment? (And Why Most Companies Aren't Ready)
What an AI readiness assessment covers, why most organisations score poorly, and how to use the results to build a credible AI strategy.