Demystifying AI: My Chief Wine Officer Talk

Beyond the Hype
One of my key messages was about looking past the current AI hype cycle. While viral examples like the “Pope in a puffer jacket” capture headlines, they don’t reflect AI’s true business potential. As both an AWS leader and a Chartered Director speaking regularly with boards, I see a clear gap between the frenzy around generative AI and what organisations can actually achieve with it.
Generative AI represents the first mass consumerisation of AI technology, but it’s just one piece of a much larger puzzle. While ChatGPT may have caught the public imagination and left many businesses playing catch-up, the foundations of AI success - from machine learning and data science to natural language processing and predictive analytics - remain crucial.
Real-World Implementation
During the evening, I shared several compelling industry use cases that demonstrate how organisations are already using AI to transform their operations:
- Financial Services: Close Brothers and Goldman Sachs are leveraging AI for risk assessment, contract generation, and regulatory compliance
- Theatre & Entertainment: The Old Vic is exploring dynamic ticket pricing and real-time language translation
- Communications: VCCP is using AI for content generation and brand consistency
- Publishing: Hatchett is implementing AI for content creation, summarisation, and automated editing
- Legal: Mathys & Squire is revolutionising IP law with AI-powered prior art searches and predictive litigation analysis
Starting Your AI Journey
For organisations looking to begin their AI transformation, I emphasized that success comes from:
- Finding the right use cases for your business
- Defining clear goals and outcomes
- Understanding your data requirements
- Building effective prompts
- Integrating with existing workflows rather than reinventing the wheel
- Having a clear scaling strategy
Building for Success
The key to successful AI implementation lies in taking a comprehensive approach. This means:
- Building a responsible AI team that spans disciplines - from finance and risk to IT, marketing, and customer experience
- Defining clear organisational principles and ethical guardrails
- Publishing your approach widely to ensure buy-in
- Continuously identifying new processes that could benefit from AI
- Maintaining an iterative approach to implementation
Looking Ahead
I closed with some crucial thoughts for business leaders:
- Generative AI isn’t a passing trend - it’s here to stay
- In increasingly uncertain times, AI can help ensure businesses operate more effectively
- Rather than eliminating jobs, AI will drive reskilling and smarter working practices
- Those who don’t adopt AI risk falling behind competitors and disruptors
- The technology is moving rapidly - look where it’s going, not where it’s been
The evening generated fantastic discussions over some excellent wine, and I was particularly encouraged by the audience’s strategic thinking about AI implementation. It’s clear that business leaders are moving beyond the hype and starting to focus on practical applications that can drive real value.
About the Author
Mario Thomas is a Chartered Director and Fellow of the Institute of Directors (IoD) with nearly three decades bridging software engineering, entrepreneurial leadership, and enterprise transformation. As Head of Applied AI & Emerging Technology Strategy at Amazon Web Services (AWS), he defines how AWS equips its global field organisation and clients to accelerate AI adoption and prepare for continuous technological disruption.
An alumnus of the London School of Economics and guest lecturer on the LSE Data Science & AI for Executives programme, Mario partners with Boards and executive teams to build the knowledge, skills, and behaviours needed to scale advanced technologies responsibly. His independently authored frameworks — including the AI Stages of Adoption (AISA), Five Pillars of AI Capability, and Well-Advised — are adopted internationally in enterprise engagements and cited by professional bodies advancing responsible AI adoption, including the IoD.
Mario's work has enabled organisations to move AI from experimentation to enterprise-scale impact, generating measurable business value through systematic governance and strategic adoption of AI, data, and cloud technologies.