Since Thing 1, you've compared AI models side by side, learned to write prompts and briefs that get useful results, and used AI to search, research and write, and to make sense of documents and data. You've tried the AI already built into your work tools and your phone, turned speech into text and text into speech, and made images, music and video from a short description. You've caught AI making things up, questioned its fairness, checked what it knows and remembers about you, learned to spot a scam or a fake, and thought about the part AI companions play in people's lives. You've used AI to make things more accessible, to learn something new and to build a working tool without writing code. You've connected it to your other apps, and handed a task to an agent with clear limits.
That's a remarkable amount of ground to cover. And the honest truth is that the ground you've been covering has probably already shifted in the time it took you to work through the programme. Tools have been updated, new models have been released, pricing has changed, and at least one feature you tried has probably been quietly retired or replaced with something better.
That's not a problem. It's the point. The specific tools were never the real lesson. They were the vehicle for building something more durable: the ability to understand what AI can do, evaluate new tools when they appear, use them well and think critically about when and whether to use them at all. Those skills don't expire when a tool updates its interface.
This final Thing is about keeping those skills sharp. You'll build a simple, realistic way to stay informed, look at what AI is changing about work and get a clear picture of how the rules around AI are developing.
The challenge of keeping up
AI moves faster than almost any technology before it. New models are announced weekly. Tools launch, merge, rebrand, and occasionally disappear. Features that seemed like science fiction six months ago become standard, while things that were standard six months ago get quietly dropped. If you try to follow everything, you'll exhaust yourself. If you follow nothing, you'll gradually fall behind.
The good news is that you don't need to follow everything. What you need is a small, curated set of reliable sources that give you enough signal to stay oriented without overwhelming you with noise. Think of it as building a personal radar: a set of resources that reliably surface the things worth knowing about, so you can ignore the rest.
The key is finding sources that match your level and your interests. The AI information ecosystem ranges from deeply technical research papers to breathless hype about the latest tool launch. Neither extreme is particularly useful for a working professional who wants to stay informed without becoming an AI specialist. What you want is the middle ground: sources that explain what's changing and what it means for people who actually use these tools in their work.
Building your AI radar
A good personal AI radar has three components: something regular that arrives in your inbox without you having to seek it out, something visual for when you want to go deeper, and somewhere to check when you hear about something specific and want to understand it quickly.
Newsletters
Email newsletters are the most efficient way to stay current because they come to you. You don't need to remember to check a website or scroll through a feed. Someone else has already done the filtering and summarising. A good AI newsletter should take five to ten minutes to read and leave you feeling informed rather than overwhelmed.
For someone coming out of this programme, these are worth considering:
A daily newsletter that covers the biggest AI news in a concise, accessible format. It does a good job of explaining why things matter, not just what happened. Free.
A daily newsletter with a practical, productivity-focused angle. It regularly includes prompts, tutorials, and tool recommendations alongside news coverage. Free.
You don't need to subscribe to all of these. Two is plenty: one daily and one weekly gives you a good balance of keeping current and having time to think about what you're reading.
YouTube channels
Video is often the best way to understand a new tool or concept because you can see someone actually using it. A few channels are particularly good for non-technical professionals:
Covers AI news, tool reviews, and practical demonstrations with an approachable, enthusiastic style. His FutureTools.io website is also a useful directory of AI tools.
Focused on practical AI use cases and productivity. Teaches you how to actually use tools rather than just reviewing them. Particularly good for professionals who want to apply AI in their work.
Takes a more analytical approach, explaining not just what new AI developments do but what they mean and how they fit into the bigger picture. Good for building deeper understanding.
Websites and reference points
When you hear about a new tool or development and want to understand it quickly, these are useful starting points:
A curated directory of AI tools and AI news, maintained by Matt Wolfe. Useful for quickly discovering and comparing tools in a specific category.
The largest directory of AI tools, searchable by category and use case. When you find yourself thinking "I wonder if there's an AI that can do that," this is where to check.
In-depth technology journalism. When a major AI announcement happens and you want more than a newsletter summary, Ars Technica typically provides thorough, balanced coverage.
AI and your work
AI is changing tasks faster than it's changing jobs. The people who do well will be the ones who decide how they use it.
Most of the change AI is bringing to work is happening at the level of tasks rather than whole jobs. Drafting, summarising, searching, note-taking, first-pass analysis: these are the parts of many jobs where AI is already helping, often inside the tools people use every day (Thing 7). In a 2026 government survey, more than half of UK adults who use generative AI said they used it for work.
That doesn't mean nothing else is changing. Some roles are being reshaped, and there are signs that entry-level work is under pressure. In one 2026 survey of UK employers, over a third said they'd cut entry-level jobs, with AI and automation among the reasons. Lots of people are worried about what AI means for jobs, and that's a fair question to ask. The honest answer is that nobody knows exactly how this will play out. What's clear is that knowing how to use AI well, and when not to, is becoming part of being good at most jobs.
Building your own AI habits
You don't need a grand plan. A few habits will do more than any amount of reading.
- Start with your own to-do list. Notice the tasks you repeat every week and try AI on one of them. Keep what works and drop what doesn't.
- Keep a prompt library. When a prompt or brief works well, save it so you can reuse and improve it.
- Check before you trust. Everything from Things 13 to 16 still applies, however good the tools get.
- Know your organisation's rules. Use the tools your employer provides and follow its AI policy. If there isn't one, ask.
- Protect the skills you want to keep. If writing or thinking something through is how you learn, do that part yourself and use AI to review it.
- Share what works. Swap tips with colleagues. Some of the best learning about AI happens between people who do the same job.
- Review every few months. Your radar will tell you when something new is worth a try.
AI and the rules
The rules around AI are still being written. You don't need to be a lawyer, but it helps to know their shape.
The UK approach
The UK doesn't have a single law written specifically for AI. Instead, existing regulators, such as the Information Commissioner's Office (data protection), Ofcom (online safety) and the Competition and Markets Authority, apply the rules they already have to AI in their own areas. This principles-based approach goes back to the government's 2023 white paper, A pro-innovation approach to AI regulation. A dedicated UK AI bill has been talked about for some time, but as of autumn 2026 none had been introduced.
The Data (Use and Access) Act 2025
This act updated UK data protection law. It became law in June 2025, and most of its data protection changes came into force in February 2026. One change matters for AI in particular. Organisations now have more room to make significant decisions about people using automated processing alone, as long as safeguards are in place: you have the right to be told about such a decision, to challenge it and to ask for a human to look at it. Thing 15 covers your wider data rights. The government's guide to the changes explains them in plain terms.
The EU AI Act
The EU's AI Act is the most far-reaching AI law so far, and it affects UK organisations that offer AI products or services in the EU. It's arriving in stages. Bans on the most harmful uses applied from February 2025. From August 2026, AI services must tell people when they're talking to an AI, AI-generated content must carry a machine-readable marking and deepfakes must be labelled (Thing 11). The rules for high-risk uses, such as recruitment and access to essential services, were pushed back in 2026 and now apply from December 2027 and August 2028. The act also asks organisations to support their staff's AI literacy, which is exactly what you've been building.
Scotland's AI strategy 2026 to 2031
In March 2026, the Scottish Government published Scotland's AI strategy for 2026 to 2031. It aims to make sure AI benefits everyone in Scotland, sets up a new AI Scotland programme to bring government, business and universities together, and is guided by the Scottish Government's commitment to Fair Work. It's a strategy rather than a law, so it shapes priorities and investment rather than setting legal rules.
None of this needs action from you today. But when a headline about AI rules lands on your radar, you'll know where it fits.
Thinking about what's next
While you were working through this programme, AI kept moving. Some of the trends that will shape the next year or two are already visible, and knowing about them will help you make sense of what you'll encounter through your AI radar.
None of these trends require you to do anything right now. But when they start showing up in your AI radar, you'll have enough context to follow along instead of starting from scratch.
Activity: your AI toolkit and programme reflection
This final activity has two parts. First, you'll set up a personal AI radar so that staying informed becomes easy rather than effortful. Second, you'll reflect on your time with the programme, because thinking back over what you've learned is one of the best ways to make sure it sticks.
-
Set up your AI radar. Choose the sources you want to follow going forward and actually set them up now, while you're thinking about it.
-
Reflect on your programme journey. Look back across all 23 Things and write a personal reflection covering the questions below.
-
Compile your final submission. Put together a short document that includes your AI radar choices and your programme reflection.
Why this matters
Setting up your radar while you're thinking about it is the difference between good intentions and an actual habit. Most people who tell themselves they'll "stay up to date with AI" without a concrete system end up doing nothing. The ones who subscribe to two newsletters and bookmark one reference site actually stay informed, because the information comes to them.
The reflection matters too. People who take time to think back over what they've learned remember more of it and find it easier to apply in new situations. Writing down what surprised you, what challenged you, and what you plan to do next turns 23 separate activities into something you can actually build on.
And here's the thing worth remembering: you now know more about practical AI than most of the people you work with. You haven't memorised a list of tools (many of which will change). What you've built is the ability to find new tools, evaluate them, use them well, and decide when they're worth using at all. That doesn't go out of date.
Claim your Open Badge
Submit your AI radar set-up (the sources you've chosen with screenshots showing you've subscribed or bookmarked them) and your programme reflection covering at least three of the reflection prompts.
Submit your AI radar set-up and programme reflection to claim this badge via cred.scot.
Claim now