How to Use AI to Practice Accounting Problems Without Letting It Do the Thinking for You
Quick but important note
Every accounting course and instructor has different rules about using AI. Always check your syllabus and follow your instructor’s guidance. The tips below are meant for independent learning and skill building. They are not a shortcut for completing graded assignments. Think of this as a roadmap for practicing and strengthening your own skills with AI as a study partner.
Why Students Struggle With Accounting Problems
If you’ve ever stared at a problem in class and thought, I understand this in class, but I still can’t do it on the exam, you are not alone.
In my experience, students can often follow along with lectures, but when it comes to working problems on their own, the skills that matter most—identifying fixed and variable elements, labeling costs correctly, and putting them into a formula or calculation—are the ones that slip away.
The tricky part is not the math itself. Most accounting is sixth grade algebra with college level words, and overthinking the numbers only makes it worse. The real challenge is independent thinking: being able to set up a problem, label everything properly, and work through it on your own. This is what separates students who succeed on quizzes from students who get stuck.
How AI Can Help and How It Can Hurt
I’ve seen both extremes. Some students don’t know how to use AI at all. They type a vague question and get an answer that is confusing or irrelevant.
Other students rely on AI too heavily. One memorable example: a student in my class took a picture of a problem and asked ChatGPT to solve it in real time while I was explaining it. They were bombarded with information, and they became more confused. This illustrates the point: AI is not magic. If you don’t force context into your prompts and control the output, you are just adding more reading, not building understanding.
The key principle is simple: AI is a tool. Its output is constrained by the knowledge of the person using it. Supplement your own intelligence with AI, do not be artificially intelligent.
A First Day Framework for Using AI to Practice Problems
The most effective way to use AI is to generate practice problems for yourself and then ask it to explain concepts, but only after you have tried the problem independently. Here’s a simple framework you can follow.
1. Provide the Technical Context
Tell the AI exactly what topic you are studying and how it is being taught.
Example:
“I am a college student in a cost accounting course. We are practicing problems that involve identifying fixed and variable costs and applying them to calculations.”
This helps the AI focus and prevents it from drifting into unrelated areas.
2. Ask for a New Practice Problem, Not a Solution
Be explicit that you want a fresh problem for practice.
Example:
“Please create a new practice problem similar in difficulty to an introductory exercise.”
3. Force Structure and Assumptions
Accounting problems depend on assumptions. Include them in the prompt.
Example:
“The problem should include a single product company, a selling price per unit, variable cost per unit, and multiple fixed costs. Do not include taxes.”
4. Set the Explanation Expectation Up Front
Tell the AI who you are and how it should respond if you need clarification.
Example:
“Assume I am a student learning this for the first time. Explain all steps in plain language when I ask follow up questions.”
Bad Prompt and Good Prompt Example
Students often start with vague prompts like:
“Make me a problem.”
This is short and easy, but the AI has no context. It might produce a confusing problem, include topics you haven’t learned, or use unfamiliar terminology.
Here’s a refined version using the framework:
“I am a college student in a cost accounting course. Please create a new practice problem for a single product company called Maya Co. Include a selling price per unit, variable cost per unit, and at least two fixed costs. This is for independent practice, not a graded assignment. Do not include taxes. Assume I will work through it on my own before asking for step-by-step explanations.”
The second prompt is longer, includes assumptions, and sets expectations. That is what makes prompt engineering so powerful.
Running Example: Practice Problem With Maya Co.
Using the refined prompt, the AI might give you:
Selling price per unit: $50
Variable cost per unit: $30
Fixed costs: $2,000 rent, $1,000 insurance
Stop here. Do not ask for a solution yet and work the problem on your own. Label your costs, set up your calculation, and determine the key results. This is where independent thinking matters most.
After attempting it, you can ask the AI to clarify your steps or explain concepts:
“I calculated break even units using my approach. Can you walk through the calculation step by step and explain why each step is necessary?”
“Why do fixed costs not change even when the activity level changes? Explain using the numbers from this problem.”
This makes AI into more of a tutor instead of shortcut.
Deepening Understanding With Scenario Analysis
Once you understand the base problem, you can explore “what if” scenarios with AI:
“What happens to the key calculation if variable cost per unit increases by $5? Explain the math and the intuition.”
“If selling price increases but sales volume drops, how should I think about that in the problem?”
These questions push you from memorization to true understanding.
Conceptual Topics Work Too
You can also use AI to explore conceptual topics:
“I am studying why certain metrics are more useful than others for decision-making. Explain this with a simple example as if I am learning it for the first time.”
Even for conceptual problems, context, assumptions, and explanation expectations matter.
Guidelines for Getting the Most Out of AI
Use AI to generate new practice problems, not to solve assigned homework.
Attempt the problem yourself first. Learning happens here.
Force context into the prompt: topic, assumptions, and course framing matter.
Ask why and how, not just what.
If it feels too easy, you are probably skipping a critical step in building mastery.
Final Thoughts
AI is here to stay in accounting education. Learning to use it effectively is part of becoming a strong student and future professional.
If you treat AI as a thinking partner that responds to the context you provide, it can deepen understanding and confidence. If you treat it as a shortcut, it will quietly steal learning opportunities.
Remember my classroom mantra: most accounting is sixth grade algebra with college level words. Do not overthink the math. Let AI help you practice thinking, not do the thinking for you.