Programmatic SEO in the AI Era: Do's and Don'ts

Programmatic SEO still works when each page offers unique, useful data, such as prices, specifications, locations or calculations. Google's spam policies call out scaled content abuse: many pages made mainly to manipulate rankings with little value, including pages mass-produced with generative AI. In the AI era, useful template pages can also become cited sources.

What does Google's policy say?

Google defines scaled content abuse as generating many pages primarily to manipulate search rankings and not help users, typically unoriginal content with little to no value, "no matter how it's created" (Google). Its examples include:

• Using generative AI tools to generate many pages without adding value for users
• Scraping feeds or search results, including through automated transformations like synonymising or translating, to generate pages with little value
• Stitching together content from different pages without adding value

Google also says AI-generated content is not against its guidelines in itself; the problem is content created primarily to manipulate rankings (Google).

When is programmatic SEO valuable?

When is it a problem?

What are the do's?

1. Start with a dataset that's unique or well-structured.
2. Make each page answer a specific question with that data.
3. Add something users can act on: a calculator, booking link, setup guide.
4. Show sources and dates for data.
5. Use structured data that matches the page, such as Product (Google).
6. Link pages logically with hubs and breadcrumbs.
7. Launch in batches and check indexing in Search Console (Google).

What are the don'ts?

• Don't publish pages with no unique data.
• Don't fill gaps with generic AI text.
• Don't create pages for places or products you don't serve.
• Don't publish more pages than you can maintain.
• Don't block crawlers from the data that makes pages valuable.

How do AI engines use programmatic pages?

AI engines retrieve passages that answer a question (arXiv). A page with a precise, current fact, such as "Example CRM's Slack integration supports two-way message sync, set up in 5 minutes", is a good source for a question about that integration. A page with generic filler is not.

What does a good template look like?

Illustrative template for an integration page.

How do you audit existing programmatic pages?

1. Export all template pages and their Search Console data.
2. Flag pages with no impressions over several months.
3. Check how much unique content each page has compared with the template.
4. Improve, merge or remove thin pages; use noindex or canonical tags where appropriate (Google, Google).
5. Re-check indexing and AI citations after changes.

How do you score a template page before launch?

Ask these questions for a sample of 20 pages from the template:

If more than a few pages fail, fix the dataset or template before scaling up. Google advises excluding scaled, low-value content from Search if you host it (Google).

A quick example

Illustrative. A SaaS company has 3,000 "[tool] alternative" pages with near-identical AI text. Most aren't indexed. It removes 2,800, keeps 200 for tools it actually competes with, and adds real comparison tables, migration steps and customer quotes. Indexed pages rise, and several are cited in AI answers about switching.

Checklist

• [ ] Each page has unique, useful data
• [ ] No pages built from swapped keywords alone
• [ ] Sources and dates shown
• [ ] Structured data matches content
• [ ] Pages launched in batches and indexing checked
• [ ] Thin pages improved, merged or removed

Related

• SEO basics for the AI era
• How to write answer-first content

Sources

• Google Search Central, Spam policies for Google web search
• Google Search Central, Google Search's guidance about AI-generated content
• Google Search Central, Introduction to structured data
• Google Search Central, Block search indexing with noindex
• Google Search Central, Consolidate duplicate URLs
• Lewis et al., Retrieval-Augmented Generation, 2020