I have a friend who's a first-gen adopter of any technology. No limits, no hesitation. No matter the cost or the risk, shiny new gadgets are his jam.
I'm not that person.
My hesitation has always been about being a test subject for some corporation that couldn’t care less about me as long as it improved their bottom line. But there comes a point where fear runs out of room. The technology permeates everyday life and culture too much to hold the line indefinitely.
With generative AI, we're very much at that point.
Over the last year, I've watched people like my friend dive in unabashedly, experimenting with tools like Claude and ChatGPT to find ways to integrate them into their daily life. Others, like myself, stayed largely on the sidelines. My hesitations haven't gone away, and there's no promise this article will resolve all of them.
But what I can speak to is the specific kind of hesitation that comes from not knowing where to start. If that's your barrier, you’re in luck because it's the most solvable one.
Why AI feels intimidating
Learning curves vary. What feels intuitive to one person feels like alien code to another. That said, a few patterns tend to come up when people describe why generative AI has been hard to approach. Maybe you’ll catch your reason!
- The blank page problem: Most AI tools open with an empty prompt box and zero instruction. If you don't already know what to ask, that blinking cursor doesn't exactly help.
- The fear of looking incompetent: Nobody wants to feel like they can't figure out a tool that everyone else seems to be using confidently. That self-consciousness is real, and it's worth being honest about.
- Information overload: Tech moves fast — new models, new workflows, new tools. By the time you've gotten comfortable with one thing, it feels like it's already been replaced by something newer. Keeping up starts to feel like a full-time job on top of your actual full-time job.
But here's the thing: you don't need to keep up with all of it. Even if the world makes you feel that way. You only need to understand the parts that help you do your work better. Tunnel vision, in this case, for the win!
Why I’m beginning to come around
My hesitation with AI is really a combination of all three. Information overload, no clear entry point, and a nagging fear that AI was designed to eventually replace me. But because fighting it isn't a real option, I started asking myself a more useful question: how can this work for me?
As a producer and project manager, there are some definite benefits to my workflow.
- Zoom's AI-generated meeting summaries is a useful cross-check against my own notes, catching things I misheard or missed entirely.
- Granola, a meeting notes extension, produces clean, editable bullet-point summaries that I can build on rather than start from scratch.
- For recurring admin tasks like morning standups and data-centric weekly client reports, I've been able to hand those off to a scheduled workflow, which frees up mental space for the parts of my job that require more human judgment.
- Drafting project timelines has been another practical plus. The first pass AI produces is never client-ready, but it gives me a structural foundation to pressure-test, which can be a faster starting point than a blank document.
On the copywriting side, I still take the first pass on everything. The thinking, the tone, the audience, all of that is mine. But when I'm stuck or struggling to translate an idea from my head onto the page, collaborating with Claude to brainstorm and outline has become a nice addition to my process. I also use it as a second set of eyes on tone and flow in sections where I'm less confident.
None of this means I've handed the wheel over. I'm still the gatekeeper of quality. The outputs require review, the timelines require reality-checking, and the refined copy still needs my final approval.
AI doesn't make the work faster every single time. But there are more opportunities where the final product is that much better.
What AI is bad at
I think we all know AI is not the end all be all (or at least it shouldn’t be). Nonetheless, it's worth being super honest about the limitations.
Generative AI is the epitome of fake it ‘till you make it. It produces confident-sounding information that is sometimes factually wrong, and obviously, it won’t fess up to it. It also lacks context. It doesn't know your client, your history, your constraints, the dynamics of your team — it doesn’t know you. No matter how hard it tries to scare you by the little things it “remembers” about you over time. It works from what you give it, which is usually incomplete.
That means human judgment isn't optional. AI is a useful collaborator, not a reliable authority. Anything it produces that you intend to use, share, or act on requires your thorough, critical review. Relinquishing your critical thinking to AI is when things go sideways.
Resources to get you more comfortable with AI
There's no shortage of AI learning content. Here are five free resources worth starting with.
Anthropic Courses: The creators of Claude offer free courses for a range of needs. For an introduction, the AI Fluency: Framework & Foundations course covers the basics of generative AI, practical prompting tips, and guidance on ethical and safe collaboration.
DeepLearning.AI's Generative AI for Everyone: A thorough, accessible beginner introduction that doesn't assume any technical efficiency.
Google's AI Essentials: Practical and approachable, with a focus on real-world application rather than theory. It also comes with a shareable LinkedIn certificate upon completion.
YouTube: YouTube University has a plethora of beginner-friendly AI content. Channels like AI Explained, Matt Wolfe, and All About AI will keep you out of the technical deep end before you're ready.
For those who want structured, paced learning, Coursera, LinkedIn Learning, and Maven all offer AI courses, some free and others paid.
A 30-Day AI challenge
The goal here is familiarity. Don’t hold yourself to mastery at the end of this. It’s just a framework for getting more acquainted with AI on your own terms, in ways that are actually useful to you.
Week 1: Just start. If you don’t have one already, create a free account on Claude or ChatGPT. Ask ten questions about anything: a hobby, an interest, something you're curious about. Don't worry about being productive yet. The only goal is to not feel intimidated by the interface or interacting with it.
Week 2: Use it on one real task. Pick something from your actual workload and bring AI into it. A first draft, a timeline, a summary, a brainstorm. It doesn't have to go well. It just has to happen.
Week 3: Compare. Look at something you've done with AI assistance alongside something you've done without it. What's different? What's better? What needed more of your judgment than you expected?
Week 4: Find your workflow. Identify one repeatable task where AI genuinely saved you time or improved your output. It may take some trial and error. Once you find it, build from there.
Hopefully with a more intentional approach where the expectations of yourself are more realistic, generative AI isn’t so intimidating. AI doesn’t need to be to the backbone of everything you do, but it’s undeniably the direction in which the world is moving.
Meeting it on your terms will ensure you’re keeping up with these changes but also in a way that feels authentic and true to you.
