How Every Generation at My Christmas Table Uses AI (And Why It Matters)

This end-of-year episode wasn’t planned — it unfolded naturally around my family’s Christmas table.

As we gathered early this year, missing family members, reflecting on work and life, and celebrating a small but significant personal milestone — recovering from back surgery after six months of pain — the conversation drifted to AI. What surprised me wasn’t how advanced the technology has become, but how differently every person around the table was experiencing it.

From a developer using ChatGPT daily to pull together complex technical reports and save enormous amounts of time, to creative experiments with AI-generated video, imagery, and even transforming travel photos into physical Christmas cards. From organisations feeling pressure to “use AI” without knowing why, to my mum quietly replacing Google with ChatGPT because she can simply ask questions and keep asking. And finally, a group of Gen Z and Gen Alpha kids who were completely unimpressed — calling AI aesthetics lazy and expressing frustration with how AI has taken over platforms like Pinterest.

This episode explores what that one conversation revealed about AI adoption, AI readiness, creativity, and the very real gap between hype and usefulness. I reflect on six months spent working deeply in AI readiness in the workplace, why preparation and structure matter more than clever prompts, how tools like Copilot work best when your information is ready first, and why AI doesn’t fix messy systems — it exposes them.

More than anything, this is a human episode. It’s about how AI shows up differently depending on where you sit, what you do, and what you need. It’s about curiosity, resistance, creativity, confusion, and quiet everyday use — all existing at the same table.

If you’re feeling pressure to “use AI” without a clear purpose, experimenting creatively without wanting to lose your voice, questioning where this technology really fits, or simply curious about how others are navigating it, this conversation will resonate.

Because the future of AI won’t be defined by hype or age — it will be defined by relevance, readiness, and how well it fits into real human lives.

Transcript

This episode wasn’t planned.

It didn’t start as a podcast idea or something I’d been drafting in advance. It started the way some of the best conversations do — around a table, a bit earlier than usual, because that’s how Christmas works in our family.

My sister wasn’t around — she’s an international customer service manager and a flight attendant, so we always do Christmas early. That part’s normal for us.

What wasn’t normal was me.

For the first time in six months, I was actually sitting at that table properly. Not half-standing. Not constantly shifting my leg. Not counting down the minutes until I’d have to move again.

I’d had back surgery just two days earlier. It was touch and go whether it would even happen before Christmas — but somehow it did. And it worked.

I still had surgery pain — but the sciatic pain, the leg pain that had dominated every part of my life for half a year — that was gone.

So there I was. Sitting. Walking. Present.

And as we talked about the year — work, life, what everyone was tired of, what surprised us — we somehow ended up talking about AI.

Someone asked a simple question.

“How have you been using AI this year?”

No agenda.
No debate.

Just curiosity.

And what unfolded around that table honestly surprised me — because every generation, and every organisation represented, had a completely different answer.

My brother went first.

He works in tech as well, but in a very different space to me. He’s a developer. Deeply technical. And right now, he’s finishing the year by writing a massive report covering everything he’s worked on across the last twelve months.

Complex. Detailed. Technical.

He said, very casually:

“I use ChatGPT every day.”

He uses it to pull together technical specifications, structure ideas he already has, and collate large volumes of information into a coherent final report. Not to replace his thinking — but to accelerate it.

For him, the benefit is obvious. It saves an enormous amount of time. Hours. Days. Sometimes weeks.

But then he said something that really stuck with me.

At his company, there’s a strong push to use AI. To try things. To get ahead. To not be left behind.

But there’s no direction.

No clarity on why they’re using it.
No guidance on how to use it well.
No conversation about readiness.

Just pressure.

And that gap — between expectation and support — is something I’ve seen over and over again this year.

Because for the last six months, I’ve been knee-deep in AI readiness at work.

Educating teams.
Producing agents.
Answering the same questions in different forms.
Being the very visible, very real “cold face” of AI in an organisation.

And here’s what I’ve learned:

AI adoption isn’t a technology problem.

It’s an information problem.
A structure problem.
And very often, a confidence problem.

People aren’t scared of AI because it’s powerful. They’re scared because they don’t know where to start — and they’re afraid of getting it wrong.

And the biggest lesson of all?

AI doesn’t fix messy systems.

It exposes them.

Then my sister jumped in — and her experience with AI this year couldn’t have been more different.

She discovered a creative course focused on AI-generated images and video, and she absolutely loved it.

She created something she calls “My Laura.”

She took photos and videos of me, fed them into an AI system, and started creating short-form videos. Some of you might have seen a couple already — me walking across the office with Chaos, stepping out of a lift, little Devil Wears Prada–style moments woven into messages.

Some are brilliant.
Some are absolutely terrible.

And honestly? The terrible ones have been half the fun.

We’ve laughed so much experimenting, playing, and seeing what works — and what really doesn’t.

But one of the most beautiful things she did this year wasn’t digital at all.

She took photos from her travels — places she’d visited, moments she’d captured — and used AI to transform those images into Christmas scenes. Snow where there had never been snow. Warm lights. Winter skies.

And then she turned them into physical Christmas cards.

Not content.
 Not posts.
 Not clicks.

Something tangible. Something thoughtful. Something human.

And it was such a good reminder that AI doesn’t have to be about speed or scale. It can be about enhancement. About taking something personal and making it a little bit magical.

And it’s important to say this clearly:

We’re not using AI to write content.
 We’re not using it to replace voice or experience.

We use it to refine ideas. To experiment visually. To explore creatively.

AI as an artistic assistant — not a shortcut.

Across all of this — creative work, blogging, experiments — one lesson kept coming up.

Craft your prompt first.

Before jumping into flashy tools.
Before burning credits.
Before wasting time.

We use ChatGPT as our thinking space.

To clarify the idea.
To shape what we’re actually asking.
 o refine the prompt.

Then — and only then — do we take that prompt into other AI tools.

The output is always better.

And this lesson applies directly to Copilot in the workplace.

I’ve watched end users spend hours going back and forth with Copilot — adding context bit by bit, correcting things, wondering why the output feels off.

Here’s my biggest tip for anyone using Copilot at work:

Have everything ready before you start prompting.

Copilot can only work with what it can see.

So collect everything first.

Your documents.
Your meeting notes.
Your emails.
Your project updates.

Put them all into one place — ideally one of the new Copilot notebooks. Create pages. Treat it like a contained workspace.

Then start chatting with Copilot inside that environment.

As your project grows, you just drop in new information. The notebook grows. The context stays intact.

Structure first.
 AI second.

That’s when Copilot actually becomes useful.

Then we asked my sister-in-law.

Her response was probably the most honest of the night.

“Yes, I use ChatGPT,” she said.
“But I actually want your brother to come into our organisation and help us use AI.”

When we asked how she wanted to use it, she paused and said:

“I don’t know.”

And then she added something I hear constantly:

“We’ve just been told we should be using it.”

No use case.
No problem to solve.
No clarity.

ust… we should.

That moment captured exactly where so many organisations are right now — all at completely different levels of AI readiness, often without realising it.

Some are experimenting quietly.
Some are pushing hard with no structure.
Some are waiting.
Some are overwhelmed.

And nearly all of them are asking the same question:

“How do we start properly?”

Then came the biggest surprise of the night.

My mum — the oldest person at the table.

A year ago, she wouldn’t have touched AI.

Now? She uses ChatGPT every day.

Not for work.
Not for content.

Instead of Google.

She asks questions the way she used to type them into a search bar — but now she can ask follow-up questions. Clarify things. Bring information together. Without ads. Without ten tabs open.

She summed it up perfectly:

“I don’t search anymore. I just ask.”

And honestly, I think that’s where we’re headed.

Away from search.
Toward conversation.

Finally, we asked the younger generation.

Gen Z — and one Gen Alpha.

Absolute chaos. Everyone talking at once.

But once it settled, something really interesting emerged.

They don’t like AI.

And not in a vague way — they were very specific.

They said they hate what AI has done to Pinterest.

They used to go there for outfit inspiration. Room aesthetics. Mood boards.

Now it’s full of AI-generated images.

Perfect. Polished. Unreal.

They find it disappointing.
They said it feels fake.
And this was the word they used — lazy.

They’re consumers of AI through movies and YouTube, but they’re not actively using it themselves. They’re not impressed. They’re not excited.

To them, AI is just background noise.

And the contrast — adults using AI daily, kids completely unimpressed — turned into one of the funniest conversations of the night.

And it led me to this realisation:

AI adoption isn’t generational.

It’s about relevance.

Around one table, we had:

A developer using AI for efficiency.
A creative using AI for experimentation and physical art.
An organisation wanting AI help but not knowing why.
A mum replacing Google with conversation.
Kids rejecting AI aesthetics as lazy.
And me — sitting in the middle — working on readiness, structure, and education.

Same year.
Same technology.
Completely different experiences.

For me personally, this year was shaped by pain.

Six months of it. Limited movement. Life shrinking down to what I could manage.

AI became something I used a lot because I was stuck at my desk — writing, thinking, building.

Now, sitting at that table, walking without that pain — it felt like a turning point.

Not just physically.

But mentally.

What stayed with me most wasn’t how advanced the technology had become.

It was how naturally it had slipped into our lives.

From technical reports, to creative experiments, to confusion, to quiet everyday use — AI didn’t replace us this year.

It met us where we were.

And sometimes, the most important conversations about the future don’t happen in meetings or strategy sessions.

They happen quietly — around a table — when we finally have the space to reflect.

Thanks for being here with me this year.

Whether you’ve listened to one episode or every single one, I really appreciate you spending your time here with me.

Looking ahead to 2026, there’s a lot coming on this podcast — more regular episodes, guest speakers already lined up, and deeper conversations around how we actually work, create, and make sense of AI in the real world.

I’ll also be releasing my complete workflow training deck and my AI readiness program — both built from everything I’ve learned working on the ground with teams and organisations, not theory or hype.

And I’m hoping to get out into the world a bit more too — attending and speaking at conferences, meeting people face to face, and continuing these conversations beyond a microphone.

I’m genuinely excited about what 2026 might bring. It feels like a year of momentum, clarity, and putting ideas into motion.

If anything in this episode resonated with you, or if you want to connect, reach out — I’d love to hear from you.

Wherever you are in the world, I hope you have a great end to the year, a fresh start to the next one, and a very happy New Year.

I’ll see you in 2026.