Every time someone says “AI can generate quiz questions now,” my first thought is: Sure. But do you want a good question or just a question?
Let me explain.
Most online exams today—whether it’s a school quiz, a coding challenge, or a competitive Olympiad—are powered by Question Banks. These are large pools of pre-vetted questions. You pick a few from the bank, randomize the order, and boom, you've got a quiz. This works well because the core concepts in most subjects don’t change that often. The periodic table isn't getting a major update anytime soon.
And because of this, Question Banks have become assets in themselves. Teachers buy and sell them. They’re so valuable that entire marketplaces like Teachers Pay Teachers exist just to buy and sell them. Platforms like Equip win deals partly because we have robust, high-quality Question Banks—especially in domains where recruiters lack the time or expertise to craft questions themselves.
A Real Example from Equip
We once worked with a company that was hiring for an analytics-heavy operations role. They wanted to assess Excel skills, data interpretation, and business logic. We pulled in questions from our operations and data Question Banks—but also tweaked the language to use examples from logistics, because that’s what the company did. The hiring manager later told us the questions felt “uncannily aligned” with real job scenarios.
Could AI have generated those questions? Yes. But it would’ve needed a prompt like: “Generate 10 MCQs to test logistics operations concepts using Excel-based data, for Indian candidates with 1-3 years’ experience in supply chain roles, avoiding American sports analogies, and limiting each question to 60 seconds.”
Good luck typing that out without knowing exactly what you’re looking for.
The Prompt is Not Enough
If you're running a casual pop quiz, sure, an AI-generated set will probably do. But if your test has real consequences—job offers, rankings, scholarships—then how the question is framed matters a lot.
You don’t want MCQs with obviously wrong options. You don’t want a physics question referencing baseball if your students have never watched a game. You may need to set a time limit per question, or adjust language complexity to match your audience. All these tiny decisions add up. And AI, powerful as it is, won’t guess your context unless you spell it out in the prompt.
And trust me, writing that perfect prompt with all your nuances is no less work than curating a solid Question Bank.
Question Reuse vs AI-Gen
We’ve observed that about 70% of our customers reuse Equip’s standard Question Banks without customization. These are strong because they’ve been iterated over hundreds of hiring cycles. The other 30% either tweak existing questions or bring their own. Very few use AI to create new questions from scratch, unless they’re experts themselves.
AI is a Power-Up, Not a Replacement
What AI can do really well is help question bank creators. These are folks who already understand the pedagogical principles, the common pitfalls, the curriculum standards. For them, AI becomes a force multiplier. They can now generate drafts, iterate faster, and spend more time polishing instead of starting from scratch.
So no, Question Banks aren't becoming obsolete. They're just evolving. The questions of the future might still be made by humans—but they’ll definitely be AI-assisted.
And that’s a good thing.
It’s tempting to think of assessments as a content problem: generate more questions, faster, cheaper. But the real challenge has always been context. Not what you ask—but why, how, and to whom. AI can help us move faster, but humans can tell if we're moving in the right direction.
In the end, good questions don’t just test what you know. They reveal what you value.