AI for Keyword Research: 4 Prompts That Actually Work

Hey there! I’m a developer who got tired of spending hours on manual keyword research. And you know what? I found a way to delegate this to AI. Spoiler: it’s not magic, but it’s damn close.

The Pain Point: Why Classic Keyword Research Sucks

You know the drill: open Google Keyword Planner, type in a seed keyword, get 200 variations where 150 are complete garbage. Then you spend hours in Excel, filtering, grouping, checking intent… And at the end, you realize you’ve burned half a day on something AI could’ve done in 15 minutes.

Here’s my approach to using AI for keyword research – four prompts I use daily.

Four Prompts for Daily Use

1. Generate Keyword Phrase Ideas (Semantic Core Expansion)

The Prompt:

I work in the [your niche] niche. My main cluster is [base keyword].
Generate 50 keyword phrase variations that users might search for, including:
- Question-based queries
- Comparison queries
- Geo-modified queries
- Modifiers like "best", "how to choose", "reviews"

This is like a brainstorming session with a colleague who knows every possible variation of your query. Except this colleague doesn’t get tired and doesn’t drink your coffee.

2. Generate Long-Tail Keywords (Low-Hanging Fruit)

The Prompt:

For the keyword [main query], create 30 long-tail variations (4+ words) that:
- Have low competition
- Reflect specific user problems
- Are suitable for informational content

Format: [keyword] - [assumed intent]

Long-tail keywords are your ticket to the top without a million-dollar SEO budget. AI generates combinations you wouldn’t even think of.

3. Check Intent (Critically Important Step!)

The Prompt:

Analyze the following keywords and determine their intent:
[list of keywords]

For each, specify:
- Intent type (informational/transactional/navigational/commercial)
- Funnel stage (awareness/consideration/decision)
- Recommended content type

This is what separates amateurs from pros. You can rank for “buy iPhone”, but if your content is a review article, conversion will be zero. AI helps you avoid these pitfalls.

4. Build Content Clusters

The Prompt:

I have a list of keywords: [your list]

Group them into thematic clusters using:
- Pillar content (main page)
- Cluster content (supporting articles)

For each cluster, suggest:
- Pillar article title
- 5-7 supporting articles
- Internal linking structure

This is Google Keyword Planner on steroids – you get not just a list of words, but a ready-made content architecture.

Be Careful! (Or How Not to Step on Rakes)

Check Real Popularity and Competitiveness

AI can generate a genius phrase like “how to properly cook borscht in zero gravity”, but that doesn’t mean anyone’s searching for it. Always verify:

  • Real search volume – use Google Keyword Planner, Ahrefs, SEMrush or my https://www.artintools.net/keyword-research
  • Competitiveness – some “obvious” keywords are so saturated you can only break into the top with Nike’s budget
  • SERP analysis – look at who’s already ranking. If it’s only domains with 90+ authority, maybe look for other options

DON’T Skip Intent Checking!

I’ll repeat this because it’s critical: check intent when generating. AI can suggest a keyword with great volume, but if the intent doesn’t match your content – you’re wasting your time.

Fail example: I once optimized an article for “python tutorial” without checking that most people were looking for basic lessons, while I wrote an advanced guide. Result? Great rankings, zero engagement.

Check Seasonality and Trends

AI doesn’t know that “buy Christmas tree” gets three searches in July and three million in December. Use Google Trends to check seasonal fluctuations. Some keywords look great but only work 2 months a year.

How to Implement This in Your Practice

Beta Testing Our Keyword Research Agent

We’re currently developing an AI agent that automatically:

  • Generates keywords
  • Automatically checks their popularity through keyword tool integration
  • Evaluates competitiveness
  • Builds content clusters
  • Suggests ready-made article topics

Basically, it’s full automation of the process I described above. If you’re interested in participating in beta testing – reach out, we’re taking a limited number of testers.

Create Your Custom GPT

Meanwhile, while the agent is in development, you can:

  1. Create a Custom GPT with your prompts and preferences
  2. Connect MCP (Model Context Protocol) for integration with keyword tools
  3. Set up Actions for automatic metric checking

Technically it looks like this:

  • Custom GPT stores your prompts and niche context
  • MCP server connects GPT with your keyword tool API (Ahrefs, SEMrush)
  • When generating keywords, GPT automatically checks their metrics

It’s like a personal SEO analyst who works 24/7 and doesn’t ask for a raise.

What’s Next?

Keyword research with AI isn’t a replacement for your expertise – it’s an extension of it. You’re still making the final decisions, but now you have an assistant doing all the grunt work.

Try these prompts. Adapt them to your niche. Experiment. And if you find your own cool variations – share them, I’d love to discuss!

Meanwhile, I’m getting back to developing that keyword research agent. Because if something can be automated – I’m automating it

P.S. If you’re still doing keyword research manually without AI – I’m not judging you. But I do feel a bit sorry for you. As someone who was in your shoes a year ago.

P.P.S. The agent we’re building? It’s not just a side project. It’s born from real pain points I experienced working with dozens of clients. Every feature is something I wished existed when I was drowning in keyword spreadsheets at 2 AM. That’s the kind of tool I want to put into the world – one that solves actual problems, not imaginary ones.