learn
intermediate
Claude
ChatGPT
Gemini
Multi-platform
How to Use AI for SEO Content Strategy
A practical workflow for using AI to research keywords, plan content, and optimise articles for search across multiple languages and search engines.
11 min read21 February 2026
SEO
content strategy
keyword research
multilingual SEO
search optimisation
A step-by-step process for using AI to handle keyword research, content planning, on-page optimisation, and multilingual SEO
For content marketers, founders, and SEO leads who want to produce search-driven content without hiring an agency or spending all day in spreadsheets
You'll get a working workflow from keyword discovery through to published, optimised content, with tested prompts for each stage
Covers Google, Baidu, and Naver considerations for teams operating across Asian markets
Why This Matters
SEO content strategy has always been tedious. You spend hours in keyword research tools, build a spreadsheet of opportunities, map them to content briefs, write the content, optimise it, and then wait three months to find out if any of it worked. Most small teams and founders skip the research entirely and just write whatever feels right. Most larger teams over-research and under-produce.
AI doesn't change the fundamentals of what makes content rank. You still need to match search intent, cover the topic thoroughly, and earn trust from both readers and search engines. What AI does change is speed. The research-to-brief phase that used to take a full day can happen in two hours. The brief-to-draft phase that took another day can happen in one. That means you can test more topics, publish more frequently, and iterate faster based on what works.
For teams publishing across Asian markets, the challenge multiplies. You're not just doing keyword research in English. You need to understand what people actually search for in Thai, Vietnamese, Japanese, Korean, or Mandarin, and those queries often don't map neatly to English translations. A direct translation of "best project management tool" into Japanese might return a grammatically correct phrase that nobody actually types into Google or Yahoo Japan. AI's ability to work across languages makes multilingual SEO research possible for teams that don't have native speakers for every target market.
Here's the full workflow.
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AI doesn't change the fundamentals of what makes content rank. You still need to match search intent, cover the topic thoroughly, and earn trust from both readers and search engines. What AI does change is speed. The research-to-brief phase that used to take a full day can happen in two hours. The brief-to-draft phase that took another day can happen in one. That means you can test more topics, publish more frequently, and iterate faster based on what works.
For teams publishing across Asian markets, the challenge multiplies. You're not just doing keyword research in English. You need to understand what people actually search for in Thai, Vietnamese, Japanese, Korean, or Mandarin, and those queries often don't map neatly to English translations. A direct translation of "best project management tool" into Japanese might return a grammatically correct phrase that nobody actually types into Google or Yahoo Japan. AI's ability to work across languages makes multilingual SEO research possible for teams that don't have native speakers for every target market.
Here's the full workflow.
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How to Do It
1
### Step 1: Use AI to generate seed keyword clusters, not individual keywords
Don't start with a single keyword. Start with a topic and ask AI to generate clusters: groups of related terms that share the same search intent. This mirrors how search engines actually think about content. Google doesn't rank pages for one keyword. It ranks them for clusters of related queries.
Feed AI your topic, your target audience, and your business context. Ask it to produce 5-8 clusters, each with a primary keyword and 4-6 related terms. Specify the language and market if you're targeting a specific region.
One warning: AI generates keywords based on its training data, not live search volumes. It's good at identifying what people might search for, but it can't tell you how many people search for it. You'll still need to validate volumes using a tool like Ahrefs, SEMrush, or Google Keyword Planner. AI handles the creative expansion. The tools handle the data.
### Step 2: Validate search intent before you commit to any keyword
This is where most AI-assisted SEO goes wrong. People find a keyword with decent volume and start writing without checking what Google actually shows for that query. Search intent determines everything: if the top results for your keyword are all product comparison pages and you're writing an educational guide, you won't rank.
Ask AI to predict the search intent for each keyword cluster (informational, commercial, transactional, navigational) and then verify by actually searching the term. Look at the top five results. What format are they? How long? What angle do they take? This takes five minutes per cluster and prevents you from wasting days on content that never had a chance.
### Step 3: Build a content brief with AI, not just an outline
A content brief is more than an outline. It's the full specification for a piece of content: target keyword cluster, search intent, recommended word count, sections to include, questions to answer, internal links to add, and specific points that competing content misses.
Feed AI the top 3-5 ranking articles for your target keyword (copy-paste the text, don't just give it the URLs unless you're using Gemini with search access). Ask it to analyse what they cover, identify gaps, and produce a brief for a piece that covers the topic more thoroughly or from a better angle. This competitive analysis step is where AI adds real value, because it can process five long articles in seconds and spot patterns a human would take an hour to find.
### Step 4: Write the content using your brief as the constraint
Now write the article, using AI for the draft if you want (see the long-form writing workflow in our separate guide). The brief is your constraint. Every section in the brief should appear in the article. Every question identified should get answered. The target keyword and its variations should appear naturally, not stuffed in.
AI-generated drafts tend to underperform on two things that matter for SEO: specificity and original insight. Search engines increasingly reward content that adds something new, whether that's original data, a genuine expert perspective, or a specific example that nobody else has covered. Use AI for the structure and base copy, then layer in your own expertise.
### Step 5: Optimise on-page elements with AI assistance
Once your draft is complete, use AI to generate the elements that most people either skip or do badly: the meta title (under 60 characters, includes primary keyword), meta description (under 155 characters, includes a reason to click), H2 and H3 headings that incorporate keyword variations, image alt text, and internal link anchor text.
These are small tasks, but they compound. A well-optimised meta description can improve click-through rate by 10-20%, which directly affects rankings. AI is very good at generating multiple options for these elements. Ask for three versions of each and pick the best one.
### Step 6: Handle multilingual SEO as research, not translation
This step applies to teams publishing content in multiple Asian languages. Multilingual SEO is not "translate your English keywords into Thai." It's "find out what Thai users actually search for when they have the same need your English content addresses."
The search queries differ for reasons beyond language. Cultural context changes what people look for. In Japan, search queries tend to be longer and more specific than English equivalents. Korean users searching on Naver expect different content formats than Google users. Chinese users on Baidu use different query structures than English speakers on Google.
Ask AI to generate keyword clusters in your target language from scratch, based on the topic and audience, not as translations of your English keywords. Then validate these with a native speaker or a local SEO tool. This approach takes longer but produces content that actually matches how people in that market search.
### Step 7: Build a publishing calendar based on keyword difficulty and business value
Not all keyword clusters deserve equal effort. Some have high volume but brutal competition. Others have lower volume but perfect alignment with what you sell. Use AI to help you score and prioritise your clusters based on two axes: how hard it will be to rank (based on the competition you've analysed) and how valuable the traffic would be to your business.
Map your top 10-15 clusters onto a quarterly calendar. Alternate between high-difficulty cornerstone pieces and lower-difficulty supporting articles that link to them. This cluster model is how modern SEO works, and AI can help you plan it in an afternoon rather than a week.
---
Don't start with a single keyword. Start with a topic and ask AI to generate clusters: groups of related terms that share the same search intent. This mirrors how search engines actually think about content. Google doesn't rank pages for one keyword. It ranks them for clusters of related queries.
Feed AI your topic, your target audience, and your business context. Ask it to produce 5-8 clusters, each with a primary keyword and 4-6 related terms. Specify the language and market if you're targeting a specific region.
One warning: AI generates keywords based on its training data, not live search volumes. It's good at identifying what people might search for, but it can't tell you how many people search for it. You'll still need to validate volumes using a tool like Ahrefs, SEMrush, or Google Keyword Planner. AI handles the creative expansion. The tools handle the data.
### Step 2: Validate search intent before you commit to any keyword
This is where most AI-assisted SEO goes wrong. People find a keyword with decent volume and start writing without checking what Google actually shows for that query. Search intent determines everything: if the top results for your keyword are all product comparison pages and you're writing an educational guide, you won't rank.
Ask AI to predict the search intent for each keyword cluster (informational, commercial, transactional, navigational) and then verify by actually searching the term. Look at the top five results. What format are they? How long? What angle do they take? This takes five minutes per cluster and prevents you from wasting days on content that never had a chance.
### Step 3: Build a content brief with AI, not just an outline
A content brief is more than an outline. It's the full specification for a piece of content: target keyword cluster, search intent, recommended word count, sections to include, questions to answer, internal links to add, and specific points that competing content misses.
Feed AI the top 3-5 ranking articles for your target keyword (copy-paste the text, don't just give it the URLs unless you're using Gemini with search access). Ask it to analyse what they cover, identify gaps, and produce a brief for a piece that covers the topic more thoroughly or from a better angle. This competitive analysis step is where AI adds real value, because it can process five long articles in seconds and spot patterns a human would take an hour to find.
### Step 4: Write the content using your brief as the constraint
Now write the article, using AI for the draft if you want (see the long-form writing workflow in our separate guide). The brief is your constraint. Every section in the brief should appear in the article. Every question identified should get answered. The target keyword and its variations should appear naturally, not stuffed in.
AI-generated drafts tend to underperform on two things that matter for SEO: specificity and original insight. Search engines increasingly reward content that adds something new, whether that's original data, a genuine expert perspective, or a specific example that nobody else has covered. Use AI for the structure and base copy, then layer in your own expertise.
### Step 5: Optimise on-page elements with AI assistance
Once your draft is complete, use AI to generate the elements that most people either skip or do badly: the meta title (under 60 characters, includes primary keyword), meta description (under 155 characters, includes a reason to click), H2 and H3 headings that incorporate keyword variations, image alt text, and internal link anchor text.
These are small tasks, but they compound. A well-optimised meta description can improve click-through rate by 10-20%, which directly affects rankings. AI is very good at generating multiple options for these elements. Ask for three versions of each and pick the best one.
### Step 6: Handle multilingual SEO as research, not translation
This step applies to teams publishing content in multiple Asian languages. Multilingual SEO is not "translate your English keywords into Thai." It's "find out what Thai users actually search for when they have the same need your English content addresses."
The search queries differ for reasons beyond language. Cultural context changes what people look for. In Japan, search queries tend to be longer and more specific than English equivalents. Korean users searching on Naver expect different content formats than Google users. Chinese users on Baidu use different query structures than English speakers on Google.
Ask AI to generate keyword clusters in your target language from scratch, based on the topic and audience, not as translations of your English keywords. Then validate these with a native speaker or a local SEO tool. This approach takes longer but produces content that actually matches how people in that market search.
### Step 7: Build a publishing calendar based on keyword difficulty and business value
Not all keyword clusters deserve equal effort. Some have high volume but brutal competition. Others have lower volume but perfect alignment with what you sell. Use AI to help you score and prioritise your clusters based on two axes: how hard it will be to rank (based on the competition you've analysed) and how valuable the traffic would be to your business.
Map your top 10-15 clusters onto a quarterly calendar. Alternate between high-difficulty cornerstone pieces and lower-difficulty supporting articles that link to them. This cluster model is how modern SEO works, and AI can help you plan it in an afternoon rather than a week.
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What This Actually Looks Like
The Prompt
I sell a project management tool for small and mid-sized teams in Southeast Asia. My target audience is operations managers, team leads, and founders at companies with 10-200 employees. Generate 6 keyword clusters related to project management software. Each cluster should have: - 1 primary keyword (the main term I'd target with a piece of content) - 5-6 related keywords and long-tail variations - The likely search intent (informational, commercial, or transactional) - A one-sentence content angle: what kind of article would rank for this cluster Focus on terms with commercial or informational intent. Skip branded terms (I'm not trying to rank for competitor names). Market: English-speaking Southeast Asia (Singapore, Philippines, Malaysia primarily).
Prompts to Try
Prompt 1: Competitive Content Gap Analysis
I'm planning content for the keyword "[PRIMARY KEYWORD]". Here are the top 5 currently ranking articles for this term. Analyse each one and tell me: 1. What topics and subtopics does each article cover? 2. What questions do they answer? 3. What's missing? Are there angles, subtopics, or questions that none of these articles cover well? 4. What format patterns do you see? (Word count range, use of images/tables, heading structure) 5. Based on the gaps, write a content brief for an article that would cover this topic more thoroughly than any of these. The brief should include: recommended word count, section-by-section outline, questions to answer, and 2-3 specific angles that would differentiate our piece. Article 1: [PASTE FULL TEXT] Article 2: [PASTE FULL TEXT] Article 3: [PASTE FULL TEXT] Article 4: [PASTE FULL TEXT] Article 5: [PASTE FULL TEXT]
What to expect: A structured gap analysis showing where existing content falls short, followed by a detailed brief. Claude handles this well given its large context window for processing multiple long articles simultaneously. ChatGPT also works but may need you to split longer articles across messages.
Prompt 2: Multilingual Keyword Expansion
I'm doing SEO for [MARKET - e.g., Japan, Thailand, Indonesia]. My product is [ONE SENTENCE DESCRIPTION]. Generate 5 keyword clusters in [LANGUAGE] that reflect how users in this market actually search for solutions like mine. Do NOT translate English keywords. Instead, think about: - How do [MARKET] users phrase these searches natively? - What terms, abbreviations, or loanwords are common in this category in [LANGUAGE]? - Are there platform-specific search behaviours to consider? (e.g., Naver in Korea, Baidu in China, Yahoo Japan) For each cluster: - Primary keyword in [LANGUAGE] with romanisation/pinyin - 4-5 related terms - Search intent - One-sentence content angle appropriate for the local market Output in a table format with both [LANGUAGE] and English translations for each term.
What to expect: Keyword clusters that reflect native search behaviour, not translated English queries. Quality varies by language. Japanese and Korean outputs are generally strong. Thai and Vietnamese are reasonable but should always be verified by a native speaker. Chinese outputs work well for Simplified Chinese but check whether the terms are Baidu-friendly or skewed toward Google usage.
Prompt 3: On-Page SEO Element Generator
Here is my completed article targeting the keyword cluster "[PRIMARY KEYWORD]" with related terms: [LIST RELATED TERMS]. Generate the following, optimised for this keyword cluster: 1. Three meta title options (under 60 characters each, primary keyword included, compelling enough to earn clicks) 2. Three meta description options (under 155 characters each, includes primary keyword, has a clear value proposition) 3. Suggested H2 headings that incorporate keyword variations naturally (not stuffed) 4. Alt text for 3 images I'll include in the article (describe what the image would show, include relevant keywords naturally) 5. Three internal link anchor text suggestions for linking to this article from other pages Article: [PASTE ARTICLE]
What to expect: Ready-to-use on-page elements. Pick the best option from each set. These are the small optimisations that most people skip but that compound over time. Works well across all major AI tools.
Common Mistakes
Using AI-generated keywords without checking actual search volume.
AI is good at guessing what people might search for. It cannot tell you whether anyone actually does. Every keyword cluster needs validation in a real SEO tool before you commit time to writing content for it. Skipping this step means you might produce a well-optimised article for a term that gets 20 searches a month.
Translating English keywords instead of researching natively.
If you're targeting the Japanese market and you translate "best CRM software" directly, you might get a grammatically correct phrase that Japanese professionals never type into a search bar. Native keyword research means starting from the user's perspective in that language, not from your English content plan.
Optimising for keywords without checking search intent.
A keyword with 10,000 monthly searches is worthless to you if the search intent doesn't match your content format. If every top result for your keyword is a product listing page and you're writing a guide, you're fighting the algorithm rather than working with it. Check the actual results page before you write.
Letting AI write the whole article without adding original insight.
Search engines are getting better at identifying content that adds nothing new. An AI-drafted article that summarises what's already ranking will struggle to outrank the sources it's summarising. Use AI for structure and efficiency, then add your own data, examples, perspective, or expertise.
Treating SEO content as a one-time project.
Publishing an article and moving on is half the job. Content that ranks well typically gets updated every 6-12 months with fresh data, new sections, and improved structure. Build update cycles into your calendar. AI makes updates faster because you can feed it the existing article and ask it to identify what's outdated or what competitors have added since you published.
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Tools That Work for This
Claude- Best for content brief generation and competitive gap analysis. The large context window lets you paste in multiple full-length competing articles and get meaningful analysis. Strong for multilingual keyword brainstorming in Chinese and Japanese.
Gemini- The Google Search integration makes it genuinely useful for checking what's currently ranking and pulling in fresh competitive data. Good for on-page optimisation tasks where current SERP context matters.
Ahrefs / SEMrush- These aren't AI tools, but they're non-negotiable for keyword validation. AI generates the ideas. These tools tell you whether those ideas have traffic behind them. No substitute for this data.
Surfer SEO- Useful for on-page optimisation scoring against competing content. Combines well with AI-generated drafts to check keyword density, heading structure, and content length against what's currently ranking.
PromptAndGo.ai- If you're building a library of SEO research prompts and running them regularly across different markets and languages, storing and iterating on those prompts in one place keeps your workflow consistent.
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Frequently Asked Questions
Google's stated position is that they care about content quality, not how it was produced. In practice, AI-generated content that's thin, repetitive, or adds no original value gets filtered out. Content that uses AI for efficiency but includes genuine expertise, original data, or a useful perspective performs well. The risk isn't in using AI. The risk is in publishing AI output without adding anything to it.
Not for keyword data. AI can generate keyword ideas and predict search intent, but it has no access to real search volume, keyword difficulty scores, backlink data, or SERP features. You need both: AI for the creative and analytical work, SEO tools for the data. They're complementary, not competing.
Use AI to generate keyword clusters in the target language (see Prompt 2), then validate with a native speaker and a local SEO tool. For Baidu specifically, tools like Baidu Index provide search trend data in Chinese. For Naver, the Naver Search Advisor tool provides Korean keyword data. AI gets you 70% of the way. Local tools and human review close the gap.
Quarterly for your core keyword clusters. Search behaviour shifts as markets evolve, new competitors enter, and terminology changes. In fast-moving categories like AI and fintech, refresh monthly. AI makes re-running your research prompts fast enough that quarterly refreshes take hours, not days.
Quality and topical coverage matter more than raw quantity. For most B2B companies, 4-8 well-researched, well-optimised articles per month builds meaningful organic traffic within 6-12 months. Publishing 20 thin articles is worse than publishing 5 thorough ones. Use AI to maintain quality at a higher publishing frequency, not to sacrifice quality for speed.
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Next Steps
Start with one keyword cluster. Run the competitive gap analysis prompt against the current top 5 results. Build a brief. Produce one article that's better than what's currently ranking. Track its performance for 8-12 weeks before scaling to a full content calendar. SEO rewards patience and consistency over volume.
For the content production side of this workflow, see [INTERNAL LINK: How to use AI to write long-form articles]. If you're repurposing SEO content across platforms after publication, [INTERNAL LINK: How to use AI to repurpose content across platforms and formats] covers the distribution strategy.
Want to customise these prompts for your specific use case? PromptAndGo.ai can optimise any prompt for your platform and audience.
For the content production side of this workflow, see [INTERNAL LINK: How to use AI to write long-form articles]. If you're repurposing SEO content across platforms after publication, [INTERNAL LINK: How to use AI to repurpose content across platforms and formats] covers the distribution strategy.
Want to customise these prompts for your specific use case? PromptAndGo.ai can optimise any prompt for your platform and audience.