AI Has No Playbook—Here's Ours

Hype is everywhere. Best practice isn’t. We’re writing ours in the open and sharing as we go.

"It feels like when I first got the internet."

George, our VP of Engineering, and I were huddled at a café table discussing AI's arrival in our industry: the excitement, the possibilities, the Rails-esque productivity gains (possibly fuelled by my 3rd flat white of the day). But our somewhat sobering conclusion was: "We're not ready for it." This shift felt different as it would affect our whole organisation, not just the tech team.

So we made a decision: rather than wait for best practices to emerge, we'd write our own AI transformation playbook.

Why Acting Now Matters

Our technology platform transformed how we work, enabling us to move fast, react quickly, and deliver better customer experiences. It's what made us the UK's fastest-growing travel company.

"What technology did for engineering efficiency, AI can now do for every role in the business."

But we've reached an inflection point. The same transformation that let our developers enable 250,000+ changes annually can now happen in finance, marketing, customer service—everywhere.

We had a simple choice of finding how to harness AI to extend these gains company-wide, or watch others do it first.

We've already seen what's possible. Our content team went from manually optimising 2,000 hotels to AI-orchestrating content for 38,000. They transformed from content creators to content conductors. Instead of generic listings, customers now see richer, more consistent content that helps them make confident decisions.

Wins like these showed the potential, but without a playbook, they risk staying isolated success stories.

Why There's No Playbook (And Why That's Our Opportunity)

McKinsey has frameworks, consultants have opinions, tech giants have case studies products looking for customers but nobody has a proven playbook for AI transformation that actually works.

In these situations, most businesses follow predictable patterns: they outsource thinking to consultants, create "innovation labs" for a privileged few, or stifle innovation with restrictive access and onerous governance.

We've always done the opposite. We invest in building capability within our organisation: the people, processes, and platforms that give us an advantage. Rather than restricting AI to specialists, we're making it available across the business.

We can't wait for someone else to figure this out. So we're writing our playbook as we go and doing it with our people, in the open, built on three interconnected streams that work together.

Our Playbook: Three Streams of AI Transformation

Instead of creating a special innovation team that "does AI" while everyone else watches, our playbook flows through three streams: how we build, how we upskill, and how we embed.

1. Tech Transformation – Rewiring How and What We Build
How we design, code, and ship. This stream is focused on how AI changes the act of building itself, as well as the output. Our leaders don't sit in steering groups. They build with teams to develop the patterns and frameworks that redefine software delivery. AI reinforces our approach of delivering customer value early and often, true to our Agile roots.

2. Services & Tools – Upskilling Everyone
Getting AI into every hand, not just a few specialists. This stream is about making AI everyone's skill. Hackdays, workshops, Google-trained ambassadors. We're giving everyone access and confidence.

3. Org Design – Embedding the Learnings
Turning experiments into how we operate. This stream ensures experiments don't stay experiments. New roles, new workflows, new expectations. We take lessons from the first two streams and wire them into our structure.

Transparency is what makes the three streams work. We share progress openly across the company, so learning spreads faster than any tool. Every experiment, success, and failure feeds back into the system.

What's Emerging So Far

A few months in, we've already seen a lot: scrappy workarounds, breakthrough wins, and areas where we're only just scratching the surface.

Stream 1: Rewiring How We Build

AI is starting to reshape how we design, build, and scale software.

We've run plenty of scrappy experiments, rolled out Copilot to everyone. But we keep evaluating new tools, nudged forward by the team's own experiments, and even when they aren't yet enterprise-ready, the results point to the immense possibilities.

When the foundations are solid, the results are transformational. A standout breakthrough was connecting AI directly into our data platform, built on years of rigorous standards. Suddenly, the mesh of data products we'd invested in revealed itself as AI-ready, unlocking capabilities we could never have bolted on afterwards.

There is a clear lesson emerging that AI accelerates strong foundations.

Strong foundations aren't the end goal, though. The real test is whether AI helps us build things people actually need, not just spin up another chat interface. Sometimes that means resisting the shiny demo and instead using AI to make the current customer experience more powerful, simpler, and faster.

But this can't stay confined to engineering.

Stream 2: Upskilling Everyone

AI is a capability every role can use. That's why we're rolling it out across marketing, trading, service, finance: every team, every role.

Google's partnership compressed our learning curve, not just by providing tools and training, but by sharing lessons from many other transformations.

Here's what we're seeing so far.

• Our Customer Experience team built an AI system that analyses 526 customer messages in 5 minutes—work that used to take 4.3 hours. That's a 52x improvement, saving £100+ per complex case.

• Our Finance team uses Gemini to automate month-end reporting checks, cutting 6 hours from every cycle.

How we scaled it.

• Low-stakes, continuous experimentation

• Hackdays allowing cross-functional teams to tackle real problems together.

• Google-trained AI ambassadors spreading skills and confidence across the organisation.

The real challenge wasn't access, as we rolled out Gemini on day one. It was helping people see how AI could transform their daily work. This is the role of our AI ambassadors, helping spread adoption virally. Encouraging teams to share new techniques and building on each other's discoveries.

It started to feel like it was working when people began sharing AI tricks unprompted and presenting great results almost weekly.

But giving people tools isn't enough. We need to change the organisation itself.

Stream 3: Embedding the Learnings

The fear is always the same: does this replace me?

Let's be direct. No.

We're seeing new patterns emerge. Roles are evolving beyond "prompt engineering" to orchestrating increasingly agentic processes. From how we personalise emails and generate content to how our chatbot Sandy handles complex customer queries.

When documents become trivial to write, thinking becomes the differentiator. Our finance team isn't just using Claude—they're building capabilities and uncovering insights that weren't possible before.

Systems thinking becomes more valuable when AI handles routine tasks. Your expertise plus AI equals an unstoppable combination.

This stream naturally lags behind the others. Organisational change takes time. But the signals emerging show the future isn't AI replacing roles—it's expanding what's possible, the same way technology always has.

But changing roles isn't enough on its own. To make it stick, you need a partnership between commercial and the technology teams.

Your Move: Partnership is Everything

That's why our playbook flows through three streams: build, upskill and embed. Whatever your context, your playbook will look different. But one principle has driven our adoption: you can't outsource it.

This transformation requires partnership between commercial and technology teams. Each brings different perspectives on where AI can add value. Find your champions in both camps—they're already experimenting, already discovering what works.

Our journey started with exactly this partnership. Now it's driving everything we build.

Our playbook so far:

• Identify early adopters in both commercial and technical teams

• Start small and iterate

• Create safe spaces for and encourage experimentation

• Track and share both successes AND failures openly

• Let adoption spread organically, then codify it into the organisation

We're six months in and the details will keep evolving, but already some of the patterns are becoming clear.

Follow Our Journey

We'll be sharing what we learn as we go. George will be writing about the Tech Transformation team's discoveries. I'll be documenting the broader organisational changes. Others will share their experiences from the front lines.

Because there's no established playbook for AI transformation. Every organisation's journey will be unique.

Maybe it always will be. But already we can see two types of companies emerging: those figuring it out for themselves and those waiting for the manual.

And if you're waiting for the manual, it'll be the story of how your competitors pulled ahead.