What Is Article Schema Markup?

Article schema is a type of JSON-LD structured data that explicitly tells search engines and AI models that a web page contains an article - along with key metadata like who wrote it, when it was published, when it was last updated, and what organization published it. It is part of the Schema.org vocabulary and one of the most fundamental structured data types for any site that publishes editorial content.

For startups that publish blog posts, learn pages, guides, or any form of written content, Article schema is table stakes. It provides the machine-readable authorship and publication signals that directly support E-E-A-T evaluation and improve your content's eligibility for AI search citations.

What Does Article Schema Look Like?

Article schema is implemented as a JSON-LD script block in your page's HTML. Here is an example of a complete Article schema implementation:

{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "What Is Article Schema Markup?",
  "description": "A guide to implementing Article schema for SEO and AI search visibility.",
  "author": {
    "@type": "Person",
    "name": "Neil Ruaro",
    "url": "https://www.linkedin.com/in/eRuaro",
    "jobTitle": "Founder, Conbersa"
  },
  "datePublished": "2026-02-14",
  "dateModified": "2026-02-14",
  "publisher": {
    "@type": "Organization",
    "name": "Conbersa",
    "url": "https://www.conbersa.ai"
  },
  "mainEntityOfPage": {
    "@type": "WebPage",
    "@id": "https://www.conbersa.ai/learn/what-is-article-schema"
  }
}

Each property serves a specific purpose. The headline tells search engines the article's title. The author block identifies who wrote the content and links to their professional profile. The datePublished and dateModified properties communicate content freshness. The publisher block connects the article to the publishing organization.

What Are the Required vs. Recommended Properties?

Google's documentation for Article structured data defines two tiers of properties:

Required Properties

• headline - The title of the article
• image - A representative image for the article (used in search result displays)

Without these two properties, Google will not process your Article schema at all.

Recommended Properties

• author - The person or organization that wrote the article
• author.name - The author's name
• author.url - A link to the author's profile or page
• datePublished - The original publication date in ISO 8601 format
• dateModified - The date of the most recent update
• publisher - The organization that published the article
• publisher.name - The publisher's name
• description - A short summary of the article

Google calls these "recommended," but in practice they are essential. Omitting author and date properties means giving up the quality signals that differentiate your content from anonymous, undated pages. Every recommended property you include strengthens the structured signal search engines and AI models use to evaluate your content.

How Does Article Schema Support E-E-A-T?

E-E-A-T - Experience, Expertise, Authoritativeness, and Trustworthiness - is the framework Google uses to evaluate content quality. Article schema directly feeds multiple E-E-A-T signals:

Experience and Expertise through author data. The author property with name, URL, and jobTitle creates a machine-readable link between your content and its creator's professional identity. When Google can connect an article to a real person with verifiable credentials, it strengthens the experience and expertise signals. This is why author authority and Article schema work hand in hand.

Authoritativeness through publisher data. The publisher property connects your article to your organization entity. Combined with Organization schema on your homepage, this creates a chain: article belongs to publisher, publisher has these credentials and this reputation. Over time, as you publish consistently on focused topics, this builds topical authority at the organizational level.

Trustworthiness through dates and transparency. The datePublished and dateModified properties signal content freshness and maintenance. A page that shows it was published last month and updated this week demonstrates active maintenance - a trust signal. Google's quality raters are trained to check for content dates, and Article schema makes those dates unambiguous to algorithms.

Google's December 2025 core update penalized content without clear authorship signals by up to 87%. Sites with proper Article schema and identifiable authors saw positive ranking adjustments. The update made it clear that anonymous, undated content is a liability in modern search.

How Does Article Schema Affect AI Search?

AI search engines evaluate structured data when deciding which sources to cite. Article schema helps in several specific ways:

Source credibility evaluation. When ChatGPT Search or Perplexity retrieves multiple pages on the same topic, Article schema helps them determine which source is most credible. A page with a named author, professional credentials, and clear publication date presents stronger credibility signals than an undated page with no authorship information.

Content freshness assessment. AI models use datePublished and dateModified to assess whether information is current. For topics that change quickly - algorithm updates, platform features, market data - an article with a recent dateModified is more likely to be cited than one with no date signal.

Entity disambiguation. Article schema helps AI models understand the relationship between the content, its author, and its publisher. This matters because AI models build internal representations of entities and their expertise areas. Well-structured Article schema contributes to how AI models associate your brand and authors with specific topics.

According to Semrush's 2025 structured data analysis, pages with valid structured data are 2.3x more likely to appear in Google AI Overviews. Article schema is typically the first structured data type a page should implement because it provides the broadest set of quality signals.

How We Use Article Schema at Conbersa

We implement Article schema on every blog post and learn page on our site. Here is our approach:

Automated generation from frontmatter. Our Next.js components read each page's frontmatter - title, author, date, description - and automatically generate the JSON-LD output. This eliminates manual markup and ensures consistency across hundreds of pages.

Author linking to LinkedIn. Every Article schema block includes an author.url pointing to the author's LinkedIn profile. This creates a cross-platform entity connection that strengthens author authority signals for both search engines and AI models.

Combined with FAQ schema. On pages that include FAQs, we implement both Article and FAQ schema together. The Article schema provides the authorship and publication context, while the FAQ schema marks up the question-answer content. Together, they give search engines and AI models a comprehensive structured picture of the page.

Validation on every deploy. We validate all structured data as part of our build process. Invalid schema provides zero benefit and can signal poor technical quality to search engines.

Should You Use Article or BlogPosting?

Schema.org defines a hierarchy: Thing > CreativeWork > Article > BlogPosting. BlogPosting is a subtype of Article, meaning it inherits all of Article's properties and adds blog-specific context.

In practice, Google treats Article and BlogPosting nearly identically. Use BlogPosting for content that lives in a blog section of your site. Use Article for news, editorial, or reference content that is not blog-formatted. If you are unsure, Article is the safe default - it covers the broadest range of editorial content.

Article schema is one of the most straightforward SEO investments you can make. It takes minutes to implement, costs nothing, and provides the structured authorship and publication signals that both traditional search and AI models use to evaluate your content's credibility. For startups building a content presence, implement it on every page from day one and let the quality signals compound.