seo ai agency
Practical steps and playbooks for agencies to use AI to scale SEO, improve rankings, and grow client revenue.
From automated audits to AI-driven content workflows, this guide gives agency owners and SEO leads step-by-step tactics, tools, prompt templates, KPIs and pricing tips to deliver measurable results for clients in 2025.
In this guide
Why agencies must use AI for SEO in 2025
AI isn't a replacement for strategy—it's a force-multiplier. Agencies that combine strong SEO fundamentals with AI workflows can run deeper audits, produce higher-quality content faster, personalise at scale, automate repetitive tasks, and show clearer ROI to clients.
Speed & scale
Automate audits and content production to serve more clients without hiring extra junior resources.
Data-driven decisions
Use AI to surface patterns and high-impact opportunities across large client portfolios.
Personalisation
Create tailored landing pages and dynamic content variations for better conversion rates.
Step 1 — Automated technical audits: fast, repeatable, actionable
Run a baseline audit in minutes and convert findings into prioritized tasks. Use AI to triage issues, draft remediation steps and estimate effort.
Core workflow
- Run crawls with Screaming Frog or Sitebulb and export CSVs.
- Feed structured crawl data to an LLM (chunked) and ask it to prioritise issues by impact and fix complexity.
- Auto-generate JIRA/Trello tickets with copy, recommended fix, code snippets and test steps.
- Estimate hours and assign to developer or client with clear acceptance criteria.
Prompt template (audit summariser)
You are an expert SEO engineer. Given this crawl CSV (columns: url,status,meta_title,meta_desc,h1,page_size,render_time,canonical,internal_links), summarise the top 10 technical issues by estimated traffic impact (high/medium/low) and for each issue provide: (1) description, (2) recommended fix, (3) estimated dev time (hours), (4) test to confirm fix. Output as JSON.
Use chunking for large sites. Verify output automatically maps to tickets in your PM tool via Zapier or Make.
Actionable tips
- Automate issue triage with confidence scores and only surface top-10 items to clients each month.
- Store LLM responses with source crawl version to maintain an audit trail and avoid hallucination.
- Use test snippets (e.g., canonical header, hreflang sample) in tickets to speed up dev fixes.
Step 2 — AI-first keyword research: strategy, clusters, intent
Move beyond single keyword lists—build topical clusters, map search intent, and prioritise by opportunity and conversion potential.
Practical process
- Seed terms from client + competitor sites (Ahrefs/SEMrush).
- Use an LLM to expand seeds into 3 clusters: informational, commercial, navigational.
- Estimate CTR opportunity using search volume, current position, and SERP features.
- Produce a prioritised content roadmap (Topical maps with 3-month cadence).
Prompt template (cluster generator)
You are an SEO strategist. For the seed keywords ["plumbing services melbourne","boiler repair"], generate 12 related keyword clusters grouped by intent (informational, commercial, transactional). For each keyword, include search_volume, difficulty_estimate, suggested_url_path, and whether it's a priority (high/med/low).
Combine LLM output with API metrics from Ahrefs/SEMrush for accuracy.
Actionable tips
- Always append SERP feature targets (e.g., People Also Ask, featured snippets) to the brief for top-priority clusters.
- Use intent mapping to decide format: blog, how-to, local landing page, comparison guide.
- Keep a "content gap" matrix for each client: competitor URL -> missing topics -> priority.
Step 3 — Scale content without sacrificing quality
Use AI to draft, optimise and personalise content while keeping human editors for final quality and factual checks.
End-to-end content pipeline
- Brief generation — auto-create briefs with keyword, intent, target word count, headings, target CTAs and examples of competing pages.
- Draft creation — LLM creates an SEO-friendly draft with inline citations and structured data snippets.
- On-page optimisation — run Surfer-like guidelines (keyword density, heading structure) and iterate the draft.
- Human edit — editor reviews for tone, factual accuracy, brand voice, and adds local references or service details.
- Publish & monitor — schedule and measure performance; use AI to create variant A/B headlines and meta descriptions.
Prompt template (SEO brief)
Create an SEO brief for the topic "how to fix a leaking tap" targeting keyword "leaking tap repair melbourne". Include suggested H1, 6 H2 headings, target word count 900-1200, short intro, list of FAQs, schema snippet for FAQ, and 3 local trust signals to include.
Add competitor URLs and let the LLM produce a content brief that editors can work from.
Quality controls
- Always run fact-check passes against client-provided data (prices, licensing).
- Use automated readability checks and tone preservation models set to your brand voice.
- Retain a human approval step for anything that affects conversions or legal claims.
Step 4 — AI for on-page optimisation and testing
Automate meta tag creation, structured data, internal link suggestions and headline A/B tests to incrementally lift CTR and rankings.
Tactics
- Generate 5 headline variants and test in meta title field for CTR uplift (use Google Search Console impression data to pick winners).
- Auto-produce FAQ schema for long-form content from the LLM’s suggested FAQs; validate with Google’s structured data testing tools.
- Internal linking recommendations: feed site map + content brief to LLM and output 3–5 anchor-text suggestions per page for link equity flow.
Prompt (meta & schema)
Write 5 meta title and meta description variations for the page "Emergency plumber Melbourne" aimed at high CTR. Keep titles under 60 chars and descriptions under 155 chars. Also output a JSON-LD FAQ schema with 3 questions.
Step 5 — Technical SEO and automation (CI for SEO)
Embed SEO checks in your release pipeline and automate routine maintenance with scripts and LLM-powered validation.
Examples you can implement
- Pre-deploy hook: run Lighthouse and a custom SEO checklist; fail deployment if core metrics drop by >10%.
- Weekly cron job: crawl top 500 pages, auto-detect drops in impressions/position and generate a recommended action list.
- Auto-check redirects after migrations: compare old sitemap to new, catch 4xx/5xx, and auto-generate remediation tickets.
Automation stack ideas
- Data collection: Google Search Console API, Analytics 4, Ahrefs/SEMrush API
- Processing: Python/Node scripts, LLMs for summarisation
- Orchestration: GitHub Actions, Cloud Functions, Zapier/Make for ticket creation
- Storage: BigQuery or Postgres for historic comparisons
Step 6 — AI-assisted link building that scales
Use AI to research prospects, personalise outreach at scale, and craft follow-ups that work. Keep human review on high-value opportunities.
Tactical playbook
- Prospect discovery: use APIs to pull sites in your niche, filter by DR/domain authority and topical relevance.
- Personalised outreach: generate 3-tier email templates (low, medium, high-touch). Include a short content idea tailored to the prospect.
- Follow-up automation: sequence 3 personalised follow-ups spaced 3–7 days apart; vary subject lines using LLM-generated synonyms.
- Repurpose content for link magnets (data studies, local guides) and use AI to draft outreach summaries and data visualisations.
Outreach email prompt
Write a personalised outreach email (short) to the editor of [site] praising a specific article (paste excerpt) and proposing a local data story that includes a link to our client's study. Keep it under 140 words and include subject line options.
Ethical note
Never fabricate quotes or data. Use AI to draft outreach, but verify data and be transparent with prospects.
Step 7 — Reporting, dashboards & KPIs that prove ROI
Automate weekly signals and monthly deep-dives. Use LLMs to translate data into plain-language insights for clients.
Key metrics to track
Automated client brief (monthly)
Use an LLM to generate a one-page summary highlighting wins, risks and next steps. Include:
- Top 3 wins (rankings/traffic/links)
- Top 3 risks or issues
- Planned roadmap next 30/90 days with estimated impact
Packaging & pricing: charge for outcomes, not hours
Offer tiered packages that combine reputation, speed and output volume. AI reduces delivery cost—share some of the savings but keep margins by charging for outcome-driven services.
Suggested tiers
How to price AI work
- Charge per deliverable (content page, audit, link opportunity) rather than per hour for repeatable AI-driven tasks.
- Reserve human review time as a premium add-on for high-value clients.
- Offer performance bonuses tied to KPI improvements (e.g., +10% organic traffic → bonus).
Ethics, hallucinations & common pitfalls
LLMs can produce confident but incorrect statements. Keep checks and balance—verify, cite, and own the output you send to clients.
- Always fact-check: Verify statistics, dates, and legal claims before publishing.
- Keep transparency: Document when AI is used and what human review occurred.
- Avoid thin content: Use AI to expand and research, not to produce low-value pages en masse.
- Respect copyright: Don’t paste competitor content into prompts without paraphrasing and attribution checks.
30-minute quick-start checklist for agencies
- Set up API access to GA4 and Search Console for each client.
- Choose a single LLM provider and standardise token/prompt templates.
- Create an audit-to-ticket pipeline (crawls → LLM → PM tool).
- Build one content brief template and run a test piece with editor review.
- Automate 1 recurring report: weekly traffic signal + monthly summary.
- Document client-facing playbook: what AI does, what humans review, SLAs.
Quick case snapshot
What we did: automated monthly technical audits, produced 8 high-intent local landing pages using AI briefs + human editing, and ran personalised link outreach sequences. Outcome: more high-quality leads and predictable growth.
Frequently asked questions
Will AI replace SEO strategists?
How do we avoid hallucinations in content?
What LLMs and tools should an agency standardise on?
How do we price AI-enabled services?
How quickly can we scale these processes?
Get started: run your first AI-driven audit this week
If your agency wants to implement a repeatable AI + SEO workflow, start with a pilot audit. We'll show you how to roadmap, automate and price the service so it becomes a profitable product.
Congero helps agencies and small teams implement AI workflows, automation and managed SEO — fast. Ask about our white-label audit templates and automation bundles.
