The Costly Mistake Founders Make with AI—and How the Right Questions Can Fix It

Let’s start with a fictional—but very possible—story.

A few years ago, a startup founder—we’ll call her Lisa—ran a subscription box company curating wellness and beauty products. Inspired by the AI hype, she hired a data scientist to build a model predicting what customers would want next month.

Lisa imagined a smart system that could magically read customer minds.

She spent six months collecting data, investing in tools, and tweaking models.

But when the results came in, they were disappointing. The model’s predictions were consistently off. Customers didn’t want what the algorithm suggested.

Why? Because Lisa asked the wrong question.

The AI was built to forecast demand based on past sales trends. But it couldn’t anticipate emerging preferences or sudden market shifts—because those weren’t in the data.

Months of effort, money, and hope—gone.

Lisa’s mistake wasn’t technical. It was strategic. She misunderstood the core of working with AI:

AI isn’t about finding all the answers. It’s about asking the right question.

And this matters more than ever for founders and creators who want to use AI wisely—especially those in their late 20s and 30s, navigating growth, pressure, and big decisions.

Let’s dive into how to make AI work for your business by asking the right questions—because that’s where transformation begins.

The hard truth? AI isn't a crystal ball or an oracle. It’s a tool for finding patterns—not for making visionary decisions or reading emotions.

AI excels at:

• Making predictions based on historical data

• Categorizing information

• Automating repetitive tasks

AI struggles with:

• Complex human emotions

• Strategic creativity

• Out-of-the-box thinking

If you're trying to decide on your next business model, AI won’t help. If you're drowning in data and need clarity—AI just might.

Ask AI When:

• You want to predict which customers are likely to churn

• You want to optimize your inventory to avoid stockouts

• You need to automate 60% of repetitive tasks

Don’t Ask AI:

• “What should I build next?”

• “What’s the next big trend?”

• “Why do people love my product?”

AI can amplify your decisions, not replace them. Think of it like hiring a brilliant assistant—not a CEO.

One of the biggest issues founders face? Starting with the tech, not the business challenge.

Let’s say you run a fitness app and ask:

❌ “How can we use AI to improve customer experience?”

✅ “Can we use AI to identify users likely to cancel based on their last 30 days of engagement?”

The difference is night and day.

The right question is:

• Clear and focused

• Tied to a business goal

• Based on existing data

3 Steps to Frame a Great AI Question:

Step 1: Define a Clear Business Goal → What do you actually want? Lower churn? More sales? Better service?

Step 2: Check Your Data → Do you have the right data? Is it clean, structured, and relevant?

Step 3: Turn It Into a Specific Question → Ask, “Can AI predict [X outcome] based on [Y data]?”

Example: From “I want to use AI for marketing” → To: “Can AI rank email subject lines based on past open rates and click-through data?”

🚨 Mistake 1: No Data = No AI

AI needs a foundation. If you haven’t been tracking relevant behaviors, sales, or interactions—AI won’t have anything to learn from.

Fix: Start collecting clean data now. Even simple spreadsheets help.

🚨 Mistake 2: Wanting AI to Replace Human Judgment

You ask AI to choose your next brand ambassador—but it only knows numbers, not vibes or values.

Fix: Use AI for filtering options, not final choices. Combine human intuition with AI support.

🚨 Mistake 3: No Success Metrics

You say, “I want better engagement.” But what does “better” mean?

Fix: Set a number, timeframe, and benchmark. → “Increase repeat visits by 15% over 3 months” is something AI can work toward.

📌 Case Study 1: Fashion Retail – Smart Discounts

Problem: A fashion retailer was bleeding money due to blanket discounts. Question: “Can AI find the best discount per product based on past sales?” Result: Increased profits by 15%—without losing volume.

AI helped tailor offers. Customers got smarter deals. Win-win.

📌 Case Study 2: Healthcare – Reducing No-Shows

Problem: A clinic lost revenue from patients missing appointments. Question: “Can AI predict who’s likely to no-show based on history and demographics?” Result: AI flagged high-risk patients. Targeted reminders cut no-shows by 30%. 📊 [Source: IBM Watson Health Case Study]

📌 Case Study 3: SaaS – Retaining Customers

Problem: A mid-stage SaaS company struggled with churn. Question: “Can AI identify signals that a customer is about to leave?” Result: By tracking login frequency and feature use, AI flagged accounts in trouble. Retention strategies based on those signals led to a 20% drop in churn. 📊 [Source: Gainsight AI Churn Analysis]

Start small. You don’t need massive systems or a data team to get started.

Try This:

✅ Pick one clear business pain point → Think about where you’re losing time, money, or momentum. That’s your starting line.

✅ Ask a question that’s data-driven and specific → Instead of “Can AI help with marketing?” ask “Can AI tell me which email subject lines get the most clicks?”

✅ Use tools you already have access to → Platforms like Shopify, HubSpot, Notion AI, and ChatGPT can help you begin testing AI without needing to code.

✅ Set a success metric before you begin → Example: “If this saves 5 hours/week or boosts conversions by 10%, it’s working.”

✅ Be patient, but proactive → AI improves over time, especially as you fine-tune what you’re asking and feed it better data.

Founders in their late 20s or early 30s—especially women—are building businesses in a time of massive change. You're likely juggling growth, funding, identity, and maybe burnout too.

AI won’t solve everything. But it can lighten the load—if you know how to guide it.

It’s like mentoring a super smart intern. The more clearly you direct it, the more value it returns.

Lisa, the founder from the intro, eventually reframed her question. She stopped asking what customers might want and asked, “Can AI help identify which types of customers respond best to new product drops?”

That change helped her double her subscriber retention in one quarter. Same data. Better question.

You don’t need to master AI—you just need to master how to partner with it.

AI is powerful. But with power comes responsibility.

Use it ethically. Check your biases. Respect privacy. The smartest founders don’t just ask good questions—they ask human ones too.

Let’s Keep the Conversation Going

What’s a challenge in your business you think AI could help solve—but you're not sure how to ask the question?

Drop your thoughts, dilemmas, or wild ideas on social. Let’s figure it out together. 👉 #AIForFounders | Let’s connect on LinkedIn, Instagram, or Twitter.