Stuart Kirk Tests ChatGPT as AI Investment Adviser, Readers React

Watching people ask ChatGPT for a model investment portfolio is either a clever stress test or a slow-motion car crash, depending on how much you trust your own judgment. I’m not against the experiment. I’m against the tone some people take afterward—like the bot is either a genius stock picker or a dangerous fraud. It’s neither. It’s a mirror with confidence. And that’s exactly why this whole thing matters.

Based on public reporting, investment columnist Stuart Kirk asked ChatGPT to create a model portfolio and then shared the experience. Readers didn’t land in one place. Some sounded impressed, some sounded uneasy, and a lot of people basically said, “Sure, but I wouldn’t bet my money on it.” That split reaction is the story. Not the specific portfolio. Not the novelty of a chatbot talking about markets. The story is that we’re starting to treat a language machine like a decision machine—and we’re doing it in public.

Here’s my judgment: asking a chatbot for investing advice is less risky than asking it to write your wedding vows, and more risky than asking it for a recipe. Because investing isn’t about sounding right. It’s about being right when it counts, and being wrong in ways you can survive. The bot can sound calm, balanced, and “diversified” while quietly making assumptions that don’t match your life at all.

And if you’re a content creator or a marketer, you should pay attention, because this is the same pattern playing out in your world—just with different stakes. Swap “portfolio” for “brand strategy” or “campaign plan” and you’ve got the same trap: a tool that speaks fluently can fool you into thinking it thinks clearly.

People call ChatGPT an ai writing tool or an ai writer, and that’s fair. But the moment you start treating it like a content intelligence platform—like it has taste, context, and accountability—you’re already sliding. It’s an ai content generator. It’s an ai content creator tool. It can be an ai content creation tool. It can even be content creation software ai inside a bigger workflow. But it does not carry consequences in its body. You do.

Imagine you’re a solo creator with a small audience. You use a content ideation tool to plan a month of posts. The bot gives you a clean list of topics, bold hooks, even a confident posting schedule. It feels like relief. Then you publish, and the comments are cold. The ideas were “fine,” but they didn’t sound like you. The bot didn’t know your history with your audience, the things you’ve promised, the lines you won’t cross. It didn’t know the one old post you wrote that people still bring up. You did. You just got outvoted by something that writes fast.

Now imagine you’re a marketer with a real budget. You treat the bot like a content research tool and ask it what customers care about. It gives you neat segments and pain points. You build a campaign. But the “insights” are really just well-worded averages. If you don’t validate them, you’re not doing research—you’re doing theater. And when the campaign flops, the bot doesn’t take the heat in the meeting. You do.

That’s why the Stuart Kirk reaction split makes sense. The optimists see speed. The skeptics see a tool that can produce plausible nonsense at scale. Both are right. The danger isn’t that AI will always be wrong. The danger is that it will be wrong in a way that feels right, and that “feels right” is often enough to get approved, posted, or purchased.

For content people, the temptation is even stronger because the payoff is immediate. An ai content automation tool can pump out drafts. An ai content workflow tool can turn one idea into ten variations. A content marketing ai tool can spit out headlines, emails, scripts, landing pages. A marketing content generator ai can keep your calendar full. An ai content marketing platform can make you look consistent, which is basically currency online.

But consistency without thinking is how brands get weird. You’ve seen it: the same safe phrasing everywhere, the same “helpful” tone, the same bland certainty. When everyone uses the same content idea generator, everyone starts sounding like the same person. That doesn’t just hurt creativity. It creates real business risk. If your competitors can produce your voice in an afternoon, your “voice” wasn’t a moat. It was a template.

To be fair, there’s a solid argument on the other side: most teams are drowning. They need drafts. They need options. They need a starting point, not a masterpiece. And AI can help people who aren’t natural writers get something on the page. I agree with that. Used as a first pass, this stuff can be great. Used as a final brain, it’s lazy in a way that will punish you later.

Because the second-order effect is trust. With investing, the cost is money and years. With content, the cost is attention and reputation. Say you’re a creator who relies on your audience believing you’re careful. If you start publishing AI-shaped takes that are slightly off—subtly wrong definitions, shallow advice, confident claims without real experience—people may not call you out right away. They’ll just stop sharing you. Quietly. And that’s worse, because you won’t get feedback, you’ll get disappearance.

The part I can’t fully settle is where responsibility sits when these tools become normal. If a reader follows a chatbot-built portfolio and loses money, the easy answer is “that’s on the reader.” But what about when big platforms and brands bake AI into everything and normalize the idea that fluent equals reliable? What happens when an entire market of content trains people to accept confident language as a substitute for proof?

So if you’re a marketer or creator using these tools, the real question isn’t whether the bot can write—it can—it’s whether you’re still doing the job of thinking, checking, and deciding, or whether you’re letting an ai content generator slowly replace your standards because it’s fast and you’re tired.

At what point does using AI for drafts turn into outsourcing your judgment—and how would you even notice it happening?