AI and Data: without the right questions, you’re left with half the answers

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The promise of AI and the forgotten human

We live in an era where AI seems capable of solving everything — from answering customer queries to predicting trends. But here's an uncomfortable truth: today, AI is only as smart as the person asking the questions. If your questions are shallow, your answers will be too. Worse still, bad questions often lead to misleading conclusions. In short, those who ask poor questions to an AI chatbot don't just get the wrong answers — they risk making costly mistakes.

"A smart AI chatbot without a smart questioner is like a race car without a driver: fast, but dangerous."

No insight without context

AI does deliver quick answers and impressive charts, but often lacks crucial context. Imagine your company suddenly sees a spike in sales. The AI chatbot enthusiastically concludes your business is booming. But what if you’ve just launched an expensive promotional campaign? The AI celebrates your growth, while you’ll be left with disappointing numbers once the short-term boost fades. This is precisely why, beyond AI, it’s essential to invest in strong data analysis and the right tools that help you keep an overview. With good analytical tools, you gain a better understanding of the broader context and can more effectively determine which questions truly matter. AI without a solid analytical foundation and context is like driving with GPS but no visibility of the road: you’re bound to go off course.

Asking questions is an art

Another issue is AI’s lack of critical curiosity. Where we humans naturally feel the urge to ask deeper questions, an AI chatbot is content with the first conclusion it finds. Imagine AI reports: “Customer satisfaction among 20–25 year olds dropped by 15% last quarter, while remaining stable across other age groups.” Full stop. The follow-up question might seem obvious — why this age group? — but without qualitative data or deep contextual insight, it’s impossible to get a meaningful answer. The result? You accept the finding at face value and miss the opportunity to truly understand the underlying cause. A company without curiosity is like a doctor who only treats symptoms, never the root cause. Without human questioning, the real issue stays hidden and continues to grow.

The illusion of certainty

AI also comes with a more subtle risk: the illusion of certainty. Because AI often sounds confident and authoritative, users tend to accept its analyses as fact, without properly challenging them. And yet, we know AI can hallucinate — it can fabricate information entirely, presenting it as truth in a convincing way. Now imagine your company making major strategic decisions purely based on AI recommendations, while no one really understands how these insights were generated — or whether they’re even accurate. It might feel cutting-edge, but it’s essentially like blindly following a guide through unfamiliar territory. The risk? You make decisions with no real control or understanding, based on possibly fictional insights — which is not innovative at all, but incredibly risky.

"AI can sound like an expert, even when it's just making things up."

What AI (still) doesn’t understand

AI also clearly struggles with understanding complex business processes. If your chatbot reports a drop in productivity, it won’t connect that to subtler factors like team motivation issues, internal conflicts, or unclear role definitions. This kind of information often isn’t captured in structured data — it lives in conversations and employee perceptions. Humans sense these nuances, AI does not. Without human interpretation, AI analysis may be limited to surface-level signals that confuse more than they clarify. AI might look at your data, but it doesn't always grasp the story behind it.

No direction, no results

Let’s be honest: AI is amazing, but only if you know how to use it. AI is like a beautiful compass: it points you perfectly north, but if you don’t know where you want to go, you’ll still end up lost. Without human intelligence and the ability to ask the right, critical questions, you’ll end up going in circles — no matter how advanced the technology.

The right foundation makes all the difference

That’s why my advice to every company is simple: don’t just invest in technology — invest in people and in solid data analysis. Make sure your company has a strong foundation of quality data analytics and the right tools, so your team can maintain an overview and keep context in mind. Only then can you ask the right follow-up questions, fully understand the situation, and ensure that AI insights are truly useful and reliable. Don’t be dazzled by AI’s impressive, quick answers — learn to dig deeper, follow up, and verify. Only then will AI become not your liability, but your most valuable partner in decision-making.