Strategic AI Adoption for Real-World Impact

I help organisations move beyond AI hype by embedding AI strategically, responsibly, and with measurable organisational impact.

+44 7482 131972

Less than 1% of CEOs have an AI strategy, that means most companies are going in blind. This is where I come in.

AI adoption has accelerated faster than most organisations’ ability to govern it. Tools are being introduced informally, teams are experimenting without shared standards, and leadership often lacks visibility of how AI is actually being used across the business.

My approach focuses on clarity first, understanding organisational needs, identifying where AI can genuinely add value, and putting a strategic framework in place before scaling adoption. The result is confident decision-making, safer implementation, and AI that supports people rather than disrupts them.

How I Support Organisations

Practical, strategic support to help organisations move from uncertainty to confident, responsible AI adoption. My work focuses on clarity, prioritisation, and real-world outcomes, not technical experimentation.

Structured workshops and reviews to understand how work is currently done, where friction exists, and where AI can deliver the most immediate value. This includes identifying quick wins and high-impact opportunities likely to show early return on investment.

Clear, leadership-level AI strategies aligned to organisational goals, risk appetite, and governance needs. This work translates ambition into a practical roadmap for responsible and sustainable AI adoption.

Identification of everyday processes that can be streamlined or automated using existing AI tools. The focus is on reducing duplication, improving efficiency, and freeing up staff time for higher-value work.

Practical, accessible training to help teams use AI confidently and responsibly. This includes support with existing tools, AI agents or applications where appropriate, and embedding good practice into day-to-day workflows.

Support to identify, compare, and prioritise AI use cases based on impact, feasibility, and risk. This helps organisations focus on opportunities most likely to deliver early return on investment while avoiding low-value experimentation.