AI Overload. You're Not Behind. The Ground Just Keeps Moving.

There's a specific feeling that hits when you're partway through learning something, a course, a new skill, a technology, and you see a headline telling you it's already been replaced.

It's not quite imposter syndrome, though it can look like it. It's more like the sensation of running on a treadmill that keeps speeding up. You're genuinely working hard. You're genuinely making progress. And somehow, it still doesn't feel like enough.

If you've felt that recently, especially when it comes to AI, you're not alone and the data backs that up.

If you've felt that recently, you're not alone, and the data backs that up.

33% of workers say they feel overwhelmed by AI in the workplace.

Pew Research Center, 2025 - survey of 5,273 employed US adults 

Only 1 in 3 workers say their employer is providing the training or guidance they need to use AI effectively.

Jobs for the Future / AudienceNet, 2026

This Mental Health Awareness Week, we want to be honest about what that gap costs, not just in productivity terms, but in confidence, mental load, and the willingness to keep learning at all.

IQ. EQ. And now enter LQ.

In the 1980s, IQ, cognitive intelligence, was held up as the critical professional capability. In the 1990s, EQ took centre stage: relational intelligence, the ability to understand and work with other people.

At Makers, we believe the defining capability of this decade is LQ: learning intelligence. The ability to keep learning, not just once, or in a formal setting, but continuously, in the face of uncertainty and change, in a world where the subject matter keeps shifting beneath your feet.

LQ is not about knowing more. It's about staying curious, staying brave, and staying in motion, even when the destination isn't yet clear.

The World Economic Forum's Future of Jobs Report 2025 found that curiosity and lifelong learning are among the fastest-growing skills in demand globally, sitting alongside resilience, analytical thinking, and creativity as the capabilities employers most need their people to develop.

This isn't a nice-to-have. It's the core skill of the era. And it's one that no AI model can replicate, because it is fundamentally human: the willingness to not yet know something, and to begin anyway.

Why AI learning feels different right now

Learning has always required tolerating uncertainty. You have to be comfortable not knowing things before you know them. That's just how it works.

But AI has introduced a new kind of uncertainty, one that doesn't resolve with practice. It's the uncertainty of a landscape that changes faster than any individual can track. A tool you spent three weeks mastering gets superseded. A skill that felt future-proof six months ago is described as 'table stakes' today. The goalposts don't just move; they get replaced entirely.

This isn't a learning problem. It's an environmental problem. And conflating the two is where the damage to confidence happens.

When the environment changes faster than your learning can keep up, the natural human response is to assume the gap is your fault. It isn't. But that feeling, of permanent inadequacy, of always starting over, is one of the most corrosive things that can happen to a learner's confidence.

How to ‘Take Action’ with tips from our AI Coach, Luke

1. Try to ignore the AI hype and avoid Linkedin Guru’s

We have all heard that AI now has PhD levels of intelligence and we see on social media people proclaiming that their prompt is the key to unlocking all your AI woes. Take these with a spoonful of salt.

Yes, AI is incredibly sophisticated, but even in 2026, they can struggle to make a powerpoint presentation that isn’t just black text on a white background or it can produce something wildly different to what you prompted it for. This often comes back to prompting, how are you interacting with the AI and telling it what you want. It may be that it needs more context or a template to improve outputs. A good prompt should include:

• A clear goal, the AI needs to know what you’re trying to achieve.
• Background information about the task the AI is completing
• What you want the output to look like
• Description of any data or information you are also providing

I see tons of posts on linkedin from Guru’s telling me how to use AI tools and even myself as an AI coach find this overwhelming at times, who am I supposed to listen to? Sadly, there is no such thing as a perfect prompt. Every person's use of AI is slightly different so what works for me, may not work for you. Instead, focus on prompting best practices like providing detailed context about what you want. This leads nicely onto my second tip!

2. Get comfortable with experimenting

Working out the limitations of AI is just as important as finding what is useful for. If you prompt AI and it doesn’t give you what you wanted, take this as a learning opportunity. Easier said than done, right?

To start an important point here, if you’re experimenting in work, make sure you only use approved AI tools for the company. This just makes sure you keep your data safe and you’re not risking compliance issues.

Give yourself time to play with these tools, get a goal in mind and see if you can get there. When you get a response, use these three questions to reflect on what you’re seeing:

• What did AI do well?
• Where did AI miss the mark?
• What would you do differently next time?

I use this approach myself when I’m trying new things with tools. Some common changes I make might include:

• Adding extra data to my prompt
• Giving more details about what I expect (eg “I need a one page report with action items laid out at the bottom” instead of “write a report”)
• Role fitting (this is where you tell the AI to act like a particular role, eg You are a senior data analyst or you are HR assistant that talks like a pirate)

3. Start simple

It is really common for people when starting out with AI to try to get it to complete multi step processes, extract this data, summarise, write a report and create a lovely diagram.

AI can complete all of those actions, but it doesn’t do well at multi tasking. When starting out, try to break down your tasks into single steps and prompt for these individually. There are two benefits from this:

• You are much more likely to get an output that resembles your expectations
• You can troubleshoot easier and work out why it might be going wrong.

4. Focus on one tool at a time.

Most AI tools work the same way. They have a chat window which you type or speak into and then you get a response. This is the same across all major providers, and what makes a good prompt is pretty similar across these platforms.

Pick one tool to start you learning (if this is for work, make sure its an approved tool!) start experimenting and seeing what you come up with. As you develop your understanding, you can branch out as required. For example, I learned a lot of my process and techniques from using ChatGPT, but my main AI tool now is Gemini.

Focus on developing your understanding and getting comfortable. Once you’re there, it is easy to transfer your knowledge for a new tool.

5. Think about what you actually need to achieve

Do you use Claude, gemini, chatGPT, Grok or Copilot? This in itself can be overwhelming. Some AI models are definitely better for particular tasks than others. Understanding what a model is suited for can help you choose the right tool for the job.

For coding, Claude and Gemini work really well. If you want to delve into your files at work and you’re a Microsoft organisation, then using Copilot will be your best bet. A quick read about each system or Youtube can help identify which tool is best suited for your task.

A note on asking for help

One of the things we see most often at Makers is learners who are struggling quietly, who assume that asking questions signals weakness, or that admitting confusion is the same as admitting failure.

It isn't. In a landscape this complex and this fast-moving, curiosity and the willingness to ask are genuine professional strengths. The people who will navigate the next few years well aren't the ones who pretended to know more than they did. They're the ones who kept asking, kept building, and kept going, even when it felt uncertain.

That's what taking action looks like. Not confidence. Continuation.

Get in touch to learn how to access Makers AI training.