Giving people access to AI tools is only the first step. The real work is turning that access into value. Through Adaptive AI Enablement, I connect business needs, what AI can reliably do and people's expertise — then align on value, redesign and test work, build capability, embed effective use and evaluate what changes.
"Most organisations now use AI. Few can show it has improved their work."
Using AI is not the same as getting value from it. For over a decade, I've worked at the intersection of strategy, learning science, and organisational change — asking one question: what turns new capability into better work?
How I put Adaptive AI Enablement into practice — from aligning on value to evaluating what changes.
Design and deliver leadership and workforce programs that build skills and judgement through practice, coaching and protected time to apply — so confident use of AI becomes better work.
Diagnose needs and opportunities with business owners, assess organisational AI maturity, and agree a baseline and success measures before anything is scaled.
Build integrated environments where platforms, pathways, and workflows embed capability development into everyday work — not separate training events.
Track use, trust, performance, costs and risk against an agreed baseline, so leaders can decide what to improve, scale or stop — with evidence, not assumptions.
Help teams trial changes to how work gets done — with clear human review, decision rights and guardrails — and remove the barriers that stop effective use becoming routine.
Hands-on experience implementing AI-powered LXP platforms with 85%+ adoption, building GenAI badge programs, and creating AI-enabled design tools.
Frameworks matter only when they become something people can actually use. So I've turned this thinking into working tools you can try yourself.
Practical tools that translate research and experience into hands-on capability for organisations exploring AI.
A self-paced, hands-on course on working with AI without giving up ownership of the result. Across seven sections, learners use one method (Frame → Delegate → Verify → Own) to decide what AI does, where it stops and what they check, then stand behind the result. Each section ends with a lab, and together the labs build a personal Agency Workcard.
View the course on Udemy ↗Full dissertation: Strategically Leveraging Learning Technologies for Sustained Employee Engagement and Performance in Professional Service Firms. USC Rossier School of Education. Defended November 2025 — six months ahead of schedule. Graduation: August 2026.
A writing coach for dissertations and essays that goes well beyond editing. It automatically detects issues and returns suggestions and warnings grounded in APA7 rules — using algorithmic AI to embed each rule directly into the review and produce an annotated copy students can quickly scan and refine. The goal isn't just correctness; it's raising the efficiency and effectiveness of academic writing.
Try the review tool ↗An AI-powered adaptive learning experience — designed to personalise content delivery based on learner behaviour, knowledge state, and performance signals. A live proof of concept developed as a class activity, exploring the future of intelligent, learner-centred design.
Try the learning player ↗A research-based interactive assessment tool to help organisations diagnose their current AI readiness — evaluating strategy, workforce capability, data foundations, governance, and culture. Generates a tailored maturity profile with prioritised recommendations.
Try the diagnostic tool ↗A thinking-partner skill that turns an agreeable AI chat into a genuine sounding board — helping individuals reach their own insight rather than be handed a tidy answer. Built on the Johari Window, Edward de Bono's Six Thinking Hats, and the Socratic method. A practical example of AI capability at the individual level.
A high-standard communication coach for accomplished professionals, founders, experts, and senior operators — those whose substance is already strong, but whose spoken presence doesn't yet fully match the authority they've earned. A custom GPT built to coach to excellence, not comfort.
Open the Communication Coach ↗Every one of those tools rests on evidence, not opinion — and that evidence comes from my doctoral research into what really drives adoption — research that now forms part of the evidence behind my Adaptive AI Enablement framework.
A qualitative study of AI-powered learning platform adoption in professional service firms — dissertation defended November 2025, six months ahead of schedule. Graduation: August 2026.
University of Southern California · Rossier School of Education · Organisational Change & Leadership
Committee Chair: Dr. Monique Datta
Compliance created activity but not learning. Intrinsic motivation — when curiosity drives the learner — outperforms mandatory training as a lever for sustained engagement.
Employees engaged even during peak workloads when content was immediately relevant. The real obstacle was poor alignment between content, timing, and work demands.
When leaders shared their own learning journeys, employees perceived learning as legitimate and low-risk — more influential than system features or incentive schemes.
Employees showed greater trust when AI acted as a guide or sounding board — not merely a search or recommendation engine.
Unclear navigation and cognitive overload were the primary reasons for disengagement — removing micro-friction drives adoption more than motivation campaigns.
Leaders know platforms exist but lack procedural know-how for daily use. Embed how-to guides in the flow of work.
Currently driven by avoidance rather than approach. Leverage expectancy value — clarify relevance and why it helps client work.
High-performance culture vs. collective learning momentum. Leadership sponsorship is in high demand.
Research is never truly finished; it keeps opening new questions. Here's where I think out loud about how people and AI can work well together.
None of this is theoretical. It's been built, tested, and refined across 18 years of senior roles inside two of the world's most demanding organisations — where the stakes were real and the scale was large.
Select a role to explore the work behind the title.
Behind the practice, the tools, and the research is a deliberate, lifelong commitment to learning what matters — formally and in the field.
I'm always happy to connect with organisations, researchers, and practitioners working out how to turn AI into better work. A good first conversation starts with three questions: where would improvement matter most, how would we recognise success, and when would we change course?