The reality check everyone’s feeling

A few months ago, I resigned from my role and, like many of you, started observing the job market more closely. What I saw was unsettling.

Jobs would appear. Within hours, hundreds had already applied.
It wasn’t just competitive. It was overwhelming. And the ongoing waves of layoffs at companies like Meta, Microsoft, and LinkedIn only added to the pressure. It became painfully clear: having a strong CV and solid experience is no longer enough. One force is rapidly reshaping how we all work: AI.

I’ll be honest with you. At that point, I had a moment of reckoning.
I could see the potential of AI, but I also realised something else: I had waited too long to get serious about learning how it works. I regretted not starting earlier. I knew I had to act fast. Not just to catch up, but to differentiate myself. To reshape my expertise and stay relevant in a landscape that was shifting faster than most of us were prepared for.

In a now-viral internal memo, Fiverr CEO Micha Kaufman didn’t mince words:

“AI is coming for your jobs. Heck, it’s coming for my job too. This is a wake-up call.”

The message sparked a lot of debate. But underneath the noise, it held a clear signal.

The smartest response isn’t fear.
It’s literacy.

So what is AI literacy? (spoiler: it’s not coding)

Let’s clear up a common misconception.
AI literacy isn’t about becoming a programmer or understanding how to fine-tune a neural network. AI literacy is the ability to understand and critically evaluate AI technologies, and to communicate and collaborate effectively with them, according to the Open University. It’s about navigating a world increasingly shaped by AI, including understanding its capabilities, limitations, and ethical implications.

It’s not about mastering the tech.
It’s about learning how to think with it.
How to collaborate with AI the same way you would with a new tool, a colleague, or a junior teammate.

So the good news is that you don’t need to be an expert to become fluent, but you do need to understand how to bring AI into your daily decision-making with intention, responsibility, and confidence.

It comes down to three things:

Why AI literacy matters now (not later)

This isn’t theoretical anymore. AI is already:

• Screening CVs

• Powering customer conversations

• Drafting presentations

• Analysing data

• Writing marketing copy

The professionals who know how to collaborate with it are moving faster, producing more, and spending less time on the tasks that burn them out.

You don’t need to compete with AI. You need to learn how to work with it — and use it to enhance your value.

That’s AI literacy.

Debunking the top myths about AI literacy

Let’s bust some myths:

❌ “I’m not technical.”
You don’t have to be. Most tools are made for everyday users.

❌ “I’m too late to learn.”
You’re right on time. We’re all still figuring this out — even leaders.

❌ “AI will just replace me anyway.”
Not if you learn to work with it. AI won’t replace jobs — but people who can use AI will replace those who don’t.

So what do you need to learn?

When I first started learning about AI, I focused on tools and prompts. But I quickly realised that real AI literacy isn’t just about “using AI.” It’s about understanding the bigger picture: the impact, the ethics, the creativity, and the responsibility that come with it.

That’s why I love the Critical AI Literacy framework developed by The Open University. It approaches AI learning through different lens helped me to better structure what I learn.

If you’d like to get a clearer picture of where you currently stand and where to focus your learning next, I’ve put together a simple, practical AI Literacy Self-Assessment Grid based on Open University framework. Whether you’re just getting started or already experimenting with tools like Copilot or ChatGPT, it will help you reflect on your strengths, spot gaps, and build confidence at your own pace.

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How to build AI literacy?

You don’t need a PhD in AI to get started and build your AI literacy.
You don’t need to take a sabbatical or sign up for an expensive course.
What you do need is a bit of time, a bit of curiosity, and a willingness to figure things out as you go.

When I realised I needed to deepen my own AI literacy, I didn’t have a plan or a fancy setup. Just time I was willing to invest and a gut feeling that if I didn’t start soon, I’d fall behind.

If you’ve been feeling the same? Honestly, you’re not alone.
Most people are still trying to get their heads around all this. The difference comes from starting even if it’s messy.

And let’s be real: time is tight.
You’re not sitting around all day with hours to spare just to “learn AI.” That would be nice, but… no.

So what helped me most was putting together a lightweight, flexible way to learn, something I could dip into during breaks, scroll through on the go, or test out while working on something real. No pressure. Just progress.

Here are six things that worked for me:

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1. Start with the basics

If you’re just beginning your AI journey, this is the move: learn the language.

Personally, getting familiar with the core AI terms was a turning point. It helped me connect the dots faster, understand how different tools work, and spot where AI was already showing up in my day-to-day. From that point on, everything else made more sense.

So if you’re feeling a bit overwhelmed, don’t start with the tech. Start with the terms.

We’ve put together a no-jargon AI Glossary to help you build your foundation. Use it as your first step — so terms like machine learning, NLP, or algorithmic bias feel like familiar territory, not barriers. Once the language clicks, the learning flows faster.

2. Try a tool each week

You don’t need to overthink it.
Open ChatGPT or Perplexity. Or try Microsoft Copilot if you’re already using Word or Excel. Pick a task you do regularly — writing an email, summarising notes, generating ideas — and ask the AI to do it for you. This isn’t about perfection. It’s about practice. You’re learning how to steer the tool.

Tip: Try something low-risk and routine first. No pressure, just play.

Stay curious about the tools emerging in your specific industry.
Whenever possible, test them out or at least take the time to understand what they can (and can’t) do. Knowing their strengths and limitations is just as important as knowing how to use them.

3. Find smart people and learn with them

Start by following a few people on LinkedIn who explain things in plain language. Join a LinkedIn group or an online community where people are sharing real experiences. Take a look at Meadow Brooke’s Linkedin page. We break down the latest AI news, share real-world use cases, and offer practical insights to help you build confidence.

And if podcasts are your thing, they can be a brilliant way to stay updated without it feeling like “work.” I personally love listening while I’m cooking or out for a walk. We all have different styles of learning. For me, this makes the learning feel light and easy. These are a few example of podcasts I subscribed and that you might like:

You can also bring AI into your everyday conversations. Ask your colleagues or friends what tools they’re trying out. You might be surprised how many people are quietly experimenting in the background. This isn’t about being the smartest in the room.
It’s about surrounding yourself with people who are thinking forward — and learning together.

Learning is easier — and way more fun — when you do it together.

4. Practice prompting

Prompting is the new professional writing skill.
If you can ask good questions, you can get good results.

Don’t just say “write an email.” Try:

“Write a concise follow-up email to a client after a project wrap-up, in a warm and professional tone.”

Or:

“Summarise this article into key bullet points for a social media post, keeping the voice playful but informed.”

It’s like briefing a junior teammate. The more context you give, the better the response.

Think of it like co-writing, not commanding.

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5. Subscribe to something small

AI is a moving target. Stay close to the conversation, but keep it manageable.

Choose one newsletter.
My go-to? The Rundown.. It lands in my inbox every morning with clear, no-fluff explanations of AI concepts, practical use cases, and the news that actually matters. You don’t need a dozen newsletters,  just one or two that consistently deliver signal over noise. This one’s worth it.

More of a podcast person? There are some real gems out there. Some lean more technical, others keep it light, but there’s something for every level.

Personally, I enjoy AI Hustle by James McClauley and Jeaden Schafer. The episodes are short (usually 9–15 minutes), cover the latest innovations, and strike a nice balance between accessible and technical. They’ve helped me stay in the loop without feeling overwhelmed.

Now, these make more sense to me because I’ve built up a solid understanding of how AI works. As you explore, you’ll find the ones that match your learning curve and grow with you.

That’s enough to keep your radar on without overwhelming yourself.

One small drip of insight a day is better than bingeing once a month.

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6. Reflect by sharing what you’ve learned

One of the best ways to deepen your learning is to talk about it — out loud, in public, or even just with your team. I picked up this mindset from Steven Bartlett’s book The Diary of a CEO, and it’s something I’ve come back to again and again. For me, sharing what I’ve learned helps to stamp it in — it turns a passing insight into something that sticks.

Write a short post about what you tried and what surprised you or what you learned. Share a use case in a Slack channel. Or host a quick show-and-tell with colleagues over coffee. You don’t need to be an expert — you just need to be honest.

“I tested Microsoft Copilot for meeting summaries and here’s what I learned.”
“I used ChatGPT to write a first draft of this report. It saved time, but it wasn’t magic.”

You’ll not only process the experience more deeply yourself, but you’ll help others learn too. It builds confidence, momentum, and creates a culture of shared curiosity.

Learning becomes more powerful when you don’t keep it to yourself.

The bottom line: you don’t need to be an AI expert. You just need to start.

I build agentic AI systems for a living. But even I don’t have all the answers.

What I do know is this:
The people who start small, build smart, and stay curious — they’re the ones who thrive.

AI literacy isn’t about becoming a machine. It’s about knowing how to stay human, while using machines to your advantage.

So let’s get practical. Let’s get hands-on.
And let’s do it together.