Welcome to the last post in the series about AI myths and realities. So far we’ve discussed 10 AI myths and uncovered the reality behind them. In this post, we’ll learn what AI still gets wrong about being human.

Trust Issues: What AI Still Gets Wrong About Being Human

Part 3 of “The Myths and Realities of AI at Work”

Let’s be honest-AI feels almost magical sometimes. It remembers your favorite email phrasing, predicts what you want to say next, and can summarize a 10-page report before your coffee cools. It’s no wonder so many people start to trust it like a super-smart coworker.

But here’s the thing: AI isn’t a person. It doesn’t understand humor, stress, or that weird tension in the room when someone’s about to quit. It’s incredibly powerful at analyzing data, but it doesn’t grasp context.

In this final post of our AI myth series, we’re talking about trust-what AI can do brilliantly, what it fumbles, and why humans still need to stay in the loop.

Myth 11: AI Always Gives Correct Answers

If you’ve ever asked ChatGPT or Gemini for information and thought, “Wow, that’s exactly what I needed,” you’ve also probably had the opposite experience-where it confidently gives you an answer that’s completely wrong.

AI doesn’t know things. It predicts them. It uses patterns in its data to guess what words probably go together in response to your question. Sometimes those guesses are perfect; other times, they’re pure fiction.

Remember the viral story of an AI-generated photo of the Pope wearing a designer puffer jacket? Totally fake, yet it fooled millions. That’s what happens when AI makes something that sounds or looks plausible but isn’t grounded in truth.

In business, this can mean serious consequences-like sending clients inaccurate info, misquoting research, or even violating privacy laws. AI is a brilliant assistant, but you still need a human fact-checker on duty.

Real-world example: A marketing manager used AI to summarize customer feedback and present findings to leadership. The AI grouped some negative feedback as “positive” because it misread the tone of sarcasm. The result? The team celebrated a “win” that was actually a red flag.

Moral of the story: trust, but verify.

Myth 12: AI Can Design My Business Strategy

This one’s easy to fall for. AI can sound thoughtful. It can weigh pros and cons, list tradeoffs, and even “recommend” actions. But it doesn’t actually think.

When you ask ChatGPT to “suggest the best pricing strategy for a new bakery,” it doesn’t reason like a strategist in your industry or local. It pulls from patterns in its training data about bakeries, pricing models, and marketing advice and predicts what a smart-sounding answer should look like.

There’s no genuine understanding, just advanced mimicry.

That’s why AI can tell you what to do (e.g., “offer discounts to attract new customers”) but not why it matters to your specific industry or location (e.g., “you’re in a large town where coupons work better than word of mouth”).

AI is great at logic. Humans are great at wisdom. You need both to make real decisions.

Myth 13: AI Would Never Give Me Information That Was Unethical

It would be nice if AI were born ethical-but it’s not. AI learns from us, and humans are full of biases, blind spots, and conflicting values.

If you train an AI on internet data, it’s going to pick up everything-from brilliant insights to conspiracy theories. Without careful design and oversight, those biases leak into the results.

Example: facial recognition tools have repeatedly been shown to misidentify people of color at higher rates because their training data included fewer diverse faces. That’s not the AI “being racist”-it’s the data reflecting human bias. But the harm is real nonetheless.

Even simple tools can cross ethical lines. Imagine uploading a client’s confidential data into ChatGPT to “summarize notes faster.” That’s risky because not all tools guarantee your data won’t be stored or reused. Always double-check the tool’s privacy settings and terms of use before inputting anything sensitive.

Quick rule of thumb: if you wouldn’t post it on a company Slack channel, don’t put it in an AI chat box.

Myth 14: You Can Safely Use AI with All Your Information

Here’s where a lot of small businesses get caught off guard. AI tools often store or share data-sometimes even using it to “train” their systems unless you opt out.

For instance, if you use a free AI tool to transcribe a user research interview, a meeting, or draft a proposal, you might unknowingly be feeding proprietary information into the model. Once it’s out there, it’s not coming back.

That’s why larger companies often have strict rules about AI usage and some go as far as creating their own proprietary AI they know that data privacy isn’t just a legal issue-it’s a trust issue.

So what can you do? • Check the settings: Many tools (like Notion AI or Zoom’s transcription feature) allow you to disable data sharing. • Anonymize sensitive info: Use initials or codes when testing AI workflows. • Educate your team: A quick “AI 101” workshop by a qualified person can prevent big mistakes later.

It’s not about avoiding AI-it’s about using it responsibly.

Myth 15: AI Adoption Is a One-Time Setup

Installing AI isn’t like setting up a printer-you don’t just plug it in and walk away. AI needs ongoing tuning, review, and retraining to stay useful. Think about it: your business evolves. Your products change, your audience shifts, your employees rotate in and out. If your AI tools don’t evolve with you, they’ll start making outdated or irrelevant recommendations.

For example, a café owner might use AI to forecast inventory. Over time, the café adds new menu items and seasonal promotions. If the data set isn’t updated, AI keeps ordering based on last year’s trends-leading to waste or shortages.

Successful AI adoption looks more like gardening than engineering. You plant it, water it, prune it, and adapt it as conditions change.

The Big Picture: AI Needs Human Guardianship

AI is incredible, but it’s not a mind-reader, moral compass, or crystal ball. It’s a powerful mirror that reflects what we feed it.

If we feed it diverse, clean data and use it with care, it can transform how we work. But if we let it run unchecked-without oversight, ethics, or updates-it can amplify the very problems we’re trying to solve.

Applied anthropologists (like me!) love to remind people that only humans can analyze humans. AI can see patterns in behavior, but it can’t understand why those behaviors happen. That’s where context, culture, and empathy come in-and those can’t be automated.

So as you explore new AI tools for your business-whether it’s ChatGPT, Jasper, Notion AI, or even that chatbot on your website-remember: AI is a partner, not a replacement. It’s at its best when it works with your people, not instead of them.

So, Where Do We Go From Here?

The Wrap-Up: Making AI Work with You, Not on You

If you’ve made it through this three-part series-first off, congratulations. You’ve officially survived the marketing noise, tech hype, and sci-fi storytelling around AI and arrived somewhere much more useful: reality.

We’ve talked about what AI is (and what it’s not), busted a few myths, and hopefully helped you see that while AI is powerful, it’s not a magic wand. It’s more like a new coworker-brilliant at certain tasks, occasionally clueless, and definitely not ready to run the place unsupervised.

Here’s What We’ve Learned Together In Part 1, we untangled the biggest myths about AI’s capabilities-like the idea that it “understands” your business or that it works the same across every industry. Spoiler: it doesn’t. AI can analyze numbers, spot patterns, and churn out ideas, but it still needs a human brain (and a good dose of common sense) to turn all that data into meaningful action.

In Part 2, we tackled the money myths-the tempting belief that AI instantly saves time and cash. In reality, it takes planning, training, and a bit of patience to make it pay off. Think of it less like flipping a switch and more like onboarding a new team member who’s learning on the job.

And in Part 3, we got real about trust. We looked at how AI can be wrong, biased, or even risky if you’re not careful with your data. We also explored why AI isn’t “ethical” or “intelligent” on its own-it mirrors the data and people that shape it. Which means it’s our job to guide it responsibly.

The Real Takeaway: It’s About Partnership, Not Replacement AI is changing the way we work, but not the reason we work. It can help you write, plan, and automate-but it can’t think creatively, empathize with your customers, or make value-driven decisions. That’s still human territory.

If you’re a small business owner, freelancer, or community leader, the goal isn’t to “get ahead of AI”-it’s to learn how to work alongside it. When used wisely, AI can handle the routine so you can focus on the meaningful. Imagine your AI tools managing your scheduling, summarizing meetings, or organizing data-while you handle the people, ideas, and vision that actually make your business thrive.

That’s the sweet spot.