Senior AI leadership for a few days a month, or as interim Head of AI. Strategy, team, portfolio and governance, until AI works in the business.
An independent senior sounding board for CEOs, boards, AI founders and investors, from strategy reviews to due diligence.
Practical sessions for executives, boards and new AI leaders. Not AI theory, but the decisions that make AI programmes scalable, trusted and worth the investment.
Talks on AI strategy, Responsible AI and agentic AI for conferences, associations and leadership offsites, with industry, academic and founder perspectives.
Ethical frameworks, bias detection, fairness metrics, transparency and accountability — directly aligned with EU AI Act Articles 9, 10, 13 and 14. Students build real compliance frameworks.
Production ML systems, MLOps, model deployment, monitoring and lifecycle management. From research prototype to enterprise production — the full delivery arc.
Foundational linguistics to transformer architectures. Production NLP systems and their cross-industry applications, including explainability requirements under EU AI Act Article 13.
Building AI-first companies, product strategy, go-to-market for AI solutions, and navigating EU regulation as a competitive advantage — not a constraint.
An integrated research programme producing interlocking components of a complete enterprise AI governance stack. Every advisory engagement draws on live research — not desk reviews or theoretical frameworks. When I advise a CTO on AI governance, the tools have been validated on real systems across Finance, Retail, Energy and NLP domains.
A 6-agent LangGraph pipeline that executes a full EU AI Act conformity audit automatically — ingesting AI system documentation and model artefacts, running a 6-phase protocol, and producing a compliance report in under 2 hours. Validated on 3 real AI systems across Finance, Retail and a live production environment.
A unified Python toolkit integrating SHAP explainability, fairness metrics, conformal prediction uncertainty intervals and drift detection — automatically selecting the minimum sufficient evidence set for each EU AI Act risk tier. Directly satisfies Articles 13 and Annex III requirements.
NLP and ML analysis of 200+ FTSE 350 and DAX 40 earnings call transcripts to identify seven recurring senior leadership AI decision failure archetypes. Delivers a board-ready diagnostic quantifying CXO AI decision risk and producing a competency gap roadmap.
NLP pipeline analysing 500 LinkedIn profiles of AI title-holders against a six-dimension credential scoring model, cross-referenced with 200 job postings. Enables organisations to audit their AI leadership bench before committing to governance programmes that depend on leadership capability.
About your AI agenda, your leadership team or your event. No pitch, just a clear next step.