Head of Innovation, Trinzo  ·  AI Strategy & People Development

Conor
Flynn

I am interested in what happens when people discover they can do more than they thought. In organisations, in technology, in sport. The conditions that make that possible turn out to be surprisingly similar in each.

Irish mountain lake landscape
"I have always been more interested in what is different than in what is familiar. That started in America after college, ran through Fiji, New Zealand and Australia, and ended up, somehow, in China."

Conor Flynn

Technology is the easy part.
People are the interesting part.

China was never the plan, but nine years in Nanjing changed how I think about most things. I built two companies there, learned Mandarin, and watched how differently people in different cultures approach the same problem. That interest in how culture shapes what people see, and do not see, has stayed with me and runs through most of what I do now.

The last twenty-five years have mostly been spent on one question, in language schools, technology start-ups, and AI programmes for large regulated companies: how do you help people do more than they thought they could? The technology changes. The question does not.

I came home to Ireland in the end, with a wife and now a family. Outside of that: triathlons and adventure races, science fiction, and anything on behavioural economics. And varying degrees of Mandarin, French and Irish. Varying degrees are doing a lot of work in that sentence.

View career history →

On AI

Most AI deployments fail not because the technology is wrong, but because organisations do not yet know what they are actually good at. That question turns out to be surprisingly hard to answer honestly.

On people

I tend to get as much from this work as the people I work with, probably more. The aim is to leave people genuinely more capable: not just informed, not dependent on me, but actually better at something that matters to them. I do not always manage it.

On values

High performance, humility, and service. These are aspirational. I fall short of them more often than I would like. What I have found is that the gap between the standard and the reality is not a problem to solve. It is where the actual work happens. You notice, and you try again.

On endurance

Triathlons and adventure races. The thing they keep teaching me is that the limits I thought were fixed usually turn out to be negotiated. I have found the same to be true in organisations, and in people.


Ideas, written
down.

Three papers on what AI does to the capability of an organisation over time, and what to build instead. Each also exists as four short articles, so you can take the argument at whatever length you have time for.

Part One of Three

The Flywheel and the Frenzy

AI amplifies what an organisation already has. It does not manufacture what it lacks.

Paper  ·  4 short reads

Part Two of Three

Cognitive Rusting

The workflow most firms call responsible deployment quietly removes the practice that built the judgment.

Paper  ·  4 short reads

Part Three of Three

The Scaffolding of Intellect

When the models commoditise, method is the last available differentiator.

Paper  ·  4 short reads

Cyclist on mountain road
Rock climbing outdoors
Open water swimming in mountain lake

Twenty-five years.
Three continents.

From Nanjing classrooms to Dublin boardrooms. The common thread has not been any particular sector, but the same underlying challenge: how do you build something real, with real people, that lasts after you leave?

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2023–
Present

Head of Innovation

Trinzo

Built Trinzo's AI & Innovation Hub from zero. Secured €750,000+ in government grants, designed AI automation programmes for Fortune 500 medical device and top-5 global pharma companies, and led a nine-person team across training, consultancy, and bespoke LLM product portfolios.

2022–
2023

VP Operations

Whyze Health

Led AI implementation projects inside two major hospital systems. Bridged the gap between clinical workflow and machine learning. The kind of regulated environment where getting it wrong has consequences.

2013–
2022

Co-Founder & COO

Adaptemy

Founded and led an adaptive learning company for nine years, from idea to multi-market commercial operation across Ireland, Singapore, Belgium, Spain, Slovakia, and Germany. Secured multi-million euro investment across multiple funding rounds. Now Non-Executive Director.

2008–
2011

Co-Founder & Director of Operations

West Education · Nanjing

Co-founded and built one of Nanjing's leading preparation schools for academic, professional language, and corporate examinations. The first company I built from the ground up, in a country and language not my own.

2006–
2008

Co-Founder & Managing Director

Sinoed Consultants · China

Created a network of service training professionals and courses for schools, government departments, and businesses across China. An early lesson in building something real with limited resources and no roadmap.

2003–
2006

Director of Studies

EF Nanjing

Led an international team of teachers to build the largest private language school in the city. Where I first learned that leadership is mostly about getting the right people in the right room and then staying out of their way.


Things built.
Problems solved.

Venture

Building from Zero in Nanjing

Arrived in China speaking no Mandarin and spent nine years building two companies there. West Education became one of Nanjing's leading training schools. Sinoed won four government contracts across schools, government departments, and businesses. The lesson: the skills that matter most in building something — listening, adapting, earning trust — turn out to be surprisingly universal.

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Venture

Nine Years Building Adaptemy

Co-founded a machine learning adaptive learning company in 2013. Raised multi-million euro investment across multiple rounds. Scaled to six international markets — Ireland, Singapore, Belgium, Spain, Slovakia, and Germany. Ran every function at different points. Nine years from idea to operating business. Still on the board as Non-Executive Director.

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Case Study

AI Capability Training in a Global Life Sciences Company

Designed and delivered a dual-track AI and regulatory compliance training programme for a major life sciences company — one track for all employees, one deep-dive for specialist QA and regulatory teams. Built to change how people work, not just what they know.

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Case Study

Fixing AI Adoption in an R&D Organisation

Diagnosed the root cause of low bespoke AI adoption in a major life sciences R&D department, despite 75% generic tool usage across the organisation. Designed a three-phase discovery, training, and embedded adoption programme. Core finding: tools positioned as optional aids consistently fail. Adoption requires being built into the process itself from the start.

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Recently
read

A selection of books I have read recently. No particular theme was intended, though one probably emerges anyway.

Range

David Epstein

The case against early specialisation. Breadth of experience turns out to be a genuine advantage in most of the domains that matter.

Prisoners of Geography

Tim Marshall

Maps don't just show you where things are. They explain why almost everything happened the way it did.

A Trick of the Mind

Daniel Yon

The brain does not receive reality. It constructs it. The implications of that for how we teach, manage and persuade people are still unfolding.

The Secret of Our Success

Joseph Henrich

Culture is a technology we mostly inherit unconsciously. The best explanation I know of why humans behave so differently from each other.

Alchemy

Rory Sutherland

The best argument that logic alone is a bad guide to human behaviour. The irrational solution is often correct, and we can't model our way to that conclusion.

AI Snake Oil

Sayash Kapoor & Arvind Narayanan

A useful corrective to most of what gets published about AI. The distinction between genuine capability and statistical pattern-matching turns out to matter enormously.

How Minds Change

David McRaney

On why people update their beliefs, and why rational argument is almost never the mechanism. More practically useful than it sounds.

Right Kind of Wrong

Amy C. Edmondson

On the science of intelligent failure. The distinction between preventable failure and productive failure is simple to state and almost impossible to get right in practice.

The Unaccountability Machine

Dan Davies

On why organisations so rarely do what anyone inside them actually wants. A book about systems that feels like it should be about ethics.


Now

What I am working on,
as of June 2026

Building Trinzo's AI regulatory practice. Writing the next piece in the LinkedIn series. Training for a 70.3 triathlon in Swansea in July, and the World Championship Triathlon in September. Reading Liu Cixin. Thinking about what the second wave of AI adoption in healthcare actually looks like. And why it will look nothing like the first.

Full /now page →

Get in touch.
I'd be glad to hear from you.

If something here resonated or you are working on a problem that feels relevant, I am happy to talk. I try to be genuinely useful in conversations, not just in engagements.

conorflynn@xuflynn.com