If 2025 has been one thing for me, it has been my “AI year.” I made the conscious decision to lean in and treat it as a proper learning journey. From my early Microsoft learning paths to formal training with MMC Learning, I’ve invested time and energy into understanding AI. And yet, the biggest lesson so far is also the simplest: AI learning never stops.
It’s exciting, humbling, and at times overwhelming. Just when you think you’ve caught up, something new arrives. But that’s also what makes it fun — because every week brings another opportunity to discover how AI can help us work smarter.
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The Pace of Change
AI doesn’t move in years or even months — it moves in weeks. Tools evolve, features are released, and what felt cutting-edge a few months ago quickly becomes routine.
I even wrote a previous article about this: AI Is Overwhelming — Until You Make It Work for You. That piece was all about the moment I realised that the only way to keep up is to make AI practical for yourself. You don’t need to master everything — you just need to build enough confidence to get started, and then keep adapting.
That’s why I now see AI not as a single skill but as an ongoing capability. You don’t learn it once. You keep learning it, over and over, because the landscape keeps shifting.
The Power of Trial and Error
You don’t learn AI by reading reports or sitting in theory sessions. You learn by trying. Trial and error is the best teacher.
In my own work, I’ve seen this play out in very practical ways. We’ve tested AI in our Learning Management System (LMS), making training available in multiple languages. We’ve trialled it in customer correspondence, using it to adjust tone and simplify language so customers feel more supported. We’ve created explainer videos in other languages, giving global users more accessible onboarding materials. And we’ve even started multilingual knowledge bases — something that simply wouldn’t have been possible without AI.
What began as small trials quickly turned into new ways of working. These aren’t experiments anymore — they’re embedded into our day-to-day CX delivery.
Tools That Made a Difference
The tools themselves don’t matter as much as how you use them. But a few have really shaped my journey this year.
- ChatGPT and Copilot → everyday companions for drafting, structuring, and exploring prompts.
- Descript → a personal favourite for audio, video, and translation work.
- Synthesia → avatars and explainer videos that make training more engaging.
- Heygen → used at work for multilingual CX use cases.
- Runway → I’ve trialled it for video, and I know there’s more to explore.
- Gamma → what a revelation! Professional presentations created quickly, and a tool I now use often.
- LMS + Knowledge Bases → where AI has moved us from theory to reality, making global onboarding and product support scalable.
What strikes me most is how many of these “trials” have already moved beyond experiments. They’ve become established practices. AI isn’t something on the side — it’s part of how we now operate in CX, from product onboarding and training to information materials and customer communications.
Staying Up-to-Date
So how do you stay on top of something that never stands still? For me, the answer is to treat AI like continuous professional development (CPD). That means:
- Investing in structured learning (MMC Learning, Microsoft certifications, and soon IAPP for privacy and governance).
- Keeping a curious mindset — trying tools, exploring prompts, and sharing knowledge with my team.
- Building learning loops, not just one-off training. This is something I’ve encouraged within my CX team: informal sessions, knowledge-sharing spaces, and celebrating small wins.
It’s not about mastering everything. It’s about having the confidence to keep adapting.
Conclusion
The lesson from 2025 is clear: AI learning never stops. And that’s not a weakness — it’s a strength. Because every new update, every new tool, every new use case brings fresh opportunities.
This year has shown me how much is possible — and how much more there is still to learn. That can feel daunting, but it can also feel magical. Because when you look back, many of the things AI now helps us do were unimaginable just a year ago.
For me, that’s what makes this journey so exciting. AI is not a destination. It’s an ongoing capability, and the leaders and teams who embrace continuous learning will be the ones who thrive.
