You work with ChatGPT, Claude, or Gemini and sometimes feel like AI can do everything. It writes code, analyzes data, creates business strategies, translates documents. But there are situations where even the best prompt won't give you what you need — and it's not your prompting skills that are the problem, but fundamental limitations of language models.
It's worth knowing when AI simply won't work, so you don't waste time refining prompts that won't deliver anyway. Here are the most common situations where prompts fail.
1. Current data and events beyond training
Problem: Language models are trained on data up to a specific date (e.g., GPT-4 up to April 2024). They don't know what happened after that, they don't have access to the latest information, trends, or legal changes.
Example:
- ❌ "Prepare a cryptocurrency market analysis for 2025 with price forecasts"
- ❌ "What are the latest changes to GDPR regulations in Poland?"
- ❌ "Who won the 2024 US presidential election?"
Why it won't work: The model doesn't have access to current data. It may generate a response, but it will be based on outdated information or — worse — on hallucinations that sound convincing.
How to recognize: If you're asking about something that happened after the model's training date, the answer will be outdated or made up.
2. Precise mathematical calculations and logic
Problem: Language models are great at generating text that looks mathematical, but they often make mistakes in calculations, especially with larger numbers, complex equations, or long calculation chains.
Example:
- ❌ "Calculate the exact project cost: 127 employees × 8 hours × 23 days × rate of $145/hour, plus 15% VAT, minus 8% discount for regular clients"
- ❌ "Solve this system of equations: [complex equations with multiple variables]"
Why it won't work: Models predict the next tokens based on patterns, they don't perform actual calculations. They may generate an answer that looks correct but contains errors.
How to recognize: If the answer contains calculations, always check them manually or use a calculator. Especially suspicious are very large numbers and long calculation chains.
3. Tasks requiring real-world actions
Problem: AI can plan, suggest, write instructions, but it can't perform actions in the real world — it won't send an email, update a database, or click a button in an application.
Example:
- ❌ "Send an email to the client with an offer"
- ❌ "Update order status #12345 in the system"
- ❌ "Reserve a table at the restaurant for tomorrow at 7 PM"
Why it won't work: Language models generate text, they don't perform actions. They can write an email, but they won't send it. They can suggest SQL code, but they won't execute the query.
How to recognize: If the task requires interaction with a system, application, API, or the real world, AI can only prepare instructions or code, but it won't perform the action.
4. Tasks requiring subjective judgment and experience
Problem: AI can suggest, but it can't replace expert judgment in situations that require business context, knowledge of organizational culture, experience in a given field, or intuition.
Example:
- ❌ "Does this candidate fit our organizational culture?"
- ❌ "Is this contract beneficial for our company?"
- ❌ "Which marketing strategy should we choose?"
Why it won't work: AI doesn't know your business context, company history, client relationships, strategic priorities, or internal quality standards. It may give a general answer, but it won't account for the specifics of your situation.
How to recognize: If the decision requires knowledge of context that isn't in the model's training (your company, your clients, your processes), the answer will be too generic.
How to recognize when you're hitting limits?
Here are signals that a task may be beyond AI's capabilities:
- You need current data — if the information changes in real-time or is newer than the model's training date
- You need precise calculations — especially with large numbers or complex equations
- You need real-world actions — if the task requires doing something, not just generating text
- You need subjective judgment — if the decision requires context that AI doesn't know
- You need 100% precision — if an error could have serious consequences
Summary
AI is a powerful tool, but it has its limits. It's worth knowing them so you don't waste time refining prompts that won't work anyway, and to know when you need other tools or approaches.
The best prompts in the world won't help if the task requires something that language models simply can't do — current data, precise calculations, real-world actions, or subjective judgment in a specific context.
If you want to better understand how to create effective prompts in situations where AI can help, also read: The Value of Prompts: Why Quality Matters So Much.