AI is becoming an increasingly important part of how marketers work, but if you're still trying to figure out how to use it effectively, the best place to start might not be your job. For AJ Wilcox, founder of B2Linked and host of The LinkedIn Ads Show, learning to use AI professionally started with experimenting with it in his personal life.

From troubleshooting Christmas lights to planning trips and monitoring flight prices, AJ has discovered that some of the most useful ways to learn AI have very little to do with marketing. By experimenting with everyday tasks, you can become more comfortable with the technology, understand what it does well, and develop the skills you'll eventually need to use it more effectively at work.

In a recent conversation with Kevin, AJ shared some of his favorite personal uses for AI, along with practical advice for anyone who wants to get better at using it.

Start Using AI for Everyday Problems

Before AJ felt comfortable relying on AI professionally, he found it helpful to experiment with it in situations where the stakes were relatively low. One of his favorite examples started with a surprisingly ordinary problem: programming the permanent Christmas lights on his house.

After struggling to configure the lights, AJ decided to ask AI for help and show it the device he was working with. The AI recognized the equipment and helped him figure out how to create the lighting patterns he wanted, turning a frustrating task into a much easier process.

That experience illustrates one of the biggest advantages of modern AI tools: you don't always need to know exactly what to ask or how to describe a problem before you get started. Depending on the tool, you can share an image, explain what's happening, and work through possible solutions in a conversation.

AJ has also used AI to help with recipes, travel planning, and comparing different options. In some cases, he's even used it to monitor rental car and flight prices over time, so he can receive an alert when prices appear to be as low as they're likely to get.

These examples might not sound particularly advanced, but they're a useful way to discover how AI can fit into your routine. Rather than trying to master every feature before you begin, you can start with a problem you already have and see whether AI can help you solve it.

The Best Way to Learn AI Is to Get More Practice

When Kevin asked AJ what advice he'd give to someone looking to improve their AI skills, his recommendation was simple: just start using it.

The more you experiment, the more you'll discover where AI can save time, help you think through a problem, or make an everyday task easier. You'll also learn its limitations and start to understand which kinds of requests produce useful results.

At first, some of the terminology and features can feel overwhelming. Concepts like tokens, agents, and prompting can take time to understand, especially when you're still learning what the tools can actually do. But you don't need to master all of those concepts before you can get value from AI.

Start by using it for things like meal planning, organizing your calendar, brainstorming ideas, or comparing different options. As you get more comfortable, you'll naturally begin to recognize opportunities to use more advanced features and build more sophisticated workflows.

This approach is especially useful if you eventually want to apply AI to your professional work. When you've already spent time experimenting with it, you'll have a better understanding of how to communicate your needs, evaluate the answers it gives you, and identify the tasks where it can genuinely help.

Use the Same Chat When You're Building on an Idea

One practical lesson AJ has learned is that how you organize your conversations with AI can make a difference in the results you get.

A new chat is useful when you're starting a completely different task or asking an unrelated question. However, if you're working through an ongoing problem, developing a skill, or refining an idea over time, continuing in the same conversation can be more effective.

Instead of explaining the entire situation from scratch every time, you can build on the previous discussion, incorporate feedback, and make your requests increasingly specific. When the relevant context remains available, the AI can use the earlier conversation to produce responses that are more tailored to what you're trying to accomplish.

AJ recommends pinning conversations he frequently returns to and renaming them according to their topic. This makes it easier to find the right chat and continue working without having to reconstruct the entire conversation.

For example, you might keep a dedicated conversation for planning trips, another for developing ideas, or one for working through a recurring professional challenge. Over time, these conversations can become useful working spaces where you build on previous questions and refine your approach.

Of course, continuing in the same chat doesn't guarantee that an AI tool will remember every detail indefinitely. The amount of context it can use depends on the tool and its capabilities, so it's still worth checking that important instructions and information are available when you need them.

AI Has Come a Long Way in Handling Context

AJ also reflected on how frustrating AI could be when he first started using it. Earlier tools often struggled to maintain context during long conversations, sometimes seeming to forget information that had been discussed just a few messages earlier.

That made it difficult to work through complicated problems because users had to repeat themselves or remind the AI of information that was already present in the conversation.

AI tools have improved considerably in their ability to work with longer conversations, making it easier to develop an idea through multiple rounds of questions, feedback, and revisions. This is particularly useful when a task requires more than a single prompt and answer.

Instead of treating every interaction as an isolated request, you can increasingly use AI as part of an ongoing process. You might start with a rough idea, ask for alternatives, explain what you like or dislike, and continue refining the result until it meets your needs.

The important takeaway is to recognize when continuity matters. For a quick factual question, a new chat may be perfectly adequate. For a complex task that depends on your preferences, earlier decisions, or previous feedback, keeping the relevant context together can make the experience much more productive.

Moving Between AI Tools? Don't Start From Scratch

As you become more comfortable with AI, you may find yourself experimenting with different tools and language models. Each may offer different features or work better for particular tasks, but switching between them can create a problem: the new tool may not have the context you've already established elsewhere.

Kevin recommends looking for an import memory or similar feature when moving from one AI tool to another. Depending on the platforms involved, these features may help transfer information from your previous conversations or provide the new tool with a summary of your preferences, goals, and working context.

That can make the transition more efficient because you don't have to rebuild everything from the beginning.

However, the process varies by platform, and importing information doesn't necessarily transfer every conversation or reproduce the original tool's memory exactly. It's worth reviewing what has been imported and making sure the new tool has the context you actually want it to use.

This is also a good opportunity to be thoughtful about what you share. Before transferring conversation histories or saved information, review the data involved and avoid importing sensitive personal or client information unless you're comfortable with how the new platform will handle it.

How Personal AI Practice Can Improve Your Professional Work

Learning to use AI in your personal life isn't just a convenient way to experiment. It can also help you build the habits and judgment you'll need when using AI professionally.

By working through everyday problems, you'll get practice explaining what you want, providing useful context, evaluating the results, and correcting the AI when it gets something wrong. You'll also become more familiar with the differences between a quick question, an ongoing conversation, and a more advanced workflow involving agents or other automation features.

Those skills can carry over into marketing, where AI can help with brainstorming campaign ideas, exploring creative angles, organizing research, and supporting other parts of the workflow. The key is understanding where it adds value instead of using it simply because it's available.

For a team working in LinkedIn Ads, for example, AI might help generate initial ideas for ad copy or organize research into an audience. But the advertiser still needs to bring the strategic judgment required to understand the audience, evaluate the messaging, and decide what is most likely to resonate.

The more experience you have using AI, the easier it becomes to recognize where it can support your work and where human judgment remains essential.

The Bottom Line: Start Small and Keep Experimenting

You don't need to understand every AI feature, learn how agents work, or develop elaborate prompts before you can start benefiting from the technology. As AJ's experience shows, some of the best learning opportunities come from using AI to solve small, everyday problems and gradually building on what you learn.

Try it when you're planning a trip, comparing options, working through a frustrating task, or brainstorming an idea. Pay attention to what works, keep track of the conversations you want to revisit, and don't be afraid to experiment with different approaches.

Over time, those small experiences can help you develop a much better understanding of how AI works and how to use it more effectively in your professional life.

Watch the video above to hear AJ and Kevin discuss their experiences with AI and share more advice on getting started.

Want more LinkedIn Ads tips, strategies, and practical advice? Subscribe to The LinkedIn Ads Show podcast, hosted by AJ Wilcox, or join the private LinkedIn Ads Fanatics community at fanatics.b2linked.com to learn alongside other LinkedIn Ads practitioners.
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