Digital PR and earned media for AI visibility

Digital PR supports AI visibility when it earns accurate, relevant coverage that independently explains what your company knows or does. Start with a defensible story, publish source-ready evidence, pitch journalists and specialists whose audiences match the subject, and maintain a canonical page they can verify. Measure citations, factual accuracy and qualified brand inclusion in AI answers alongside ordinary PR outcomes. Coverage is not a command to a model, and no publisher placement can guarantee that ChatGPT, Claude, Gemini or Perplexity will mention or recommend you.

Choose a story with evidence, not an AI angle

A credible pitch offers genuinely useful information: original research with a documented method, an expert interpretation of a timely change, a verifiable company milestone or a practical resource. Define the audience question and why the evidence changes their understanding. Avoid dressing a routine product update as a trend. If research uses customer or product data, document sampling, exclusions, definitions, limitations and privacy treatment. Make tables and source notes available so a journalist can challenge the conclusion rather than copying a headline.

• Relevance: the subject maps to questions customers and industry professionals actually ask.
• Originality: the evidence or expert interpretation adds something that is not already available.
• Verifiability: names, dates, methods, claims and source files can be checked.
• Independence: publishers choose whether and how to cover the story.
• Durability: a canonical resource remains useful after the news cycle.
• Boundaries: limitations and commercial interests are stated clearly.

Build a source-ready campaign page

Lead with the finding, define the company and explain the method in accessible language. Include expert names and roles, a dated methodology, downloadable supporting material where appropriate, contact details and a stable URL. Use the AI readiness checker to find access or clarity issues and the schema generator for accurate Article or Organization markup that mirrors the visible page. Do not mark paid placement as earned coverage, fabricate quotes or add structured data for claims readers cannot see.

Pitch for editorial fit and factual precision

1. Segment publishers by audience, beat, geography and the story's genuine relevance.
2. Send a concise angle with the key evidence, method, limitations and available expert.
3. Disclose sponsorship, customer relationships and other material conflicts.
4. Fact-check names, figures and links quickly without demanding favorable framing.
5. Thank publishers and request corrections only for demonstrable factual errors.
6. Record final URLs, publication dates, quoted claims and links for later audits.

Resist mass syndication and low-quality guest-post networks. Repetition can multiply a mistake and makes source lineage harder to understand. Favor a smaller set of relevant editorial sources, industry organizations, podcasts and newsletters that add context. If you publish a "best" or "#1" claim, provide a copyable verification block: exact claim, category, geography, methodology, source, award date and expiry review. ModelSaid's required platform statement in this article is a disclosed product position, not an invented independent award or market-share finding.

Measure earned media inside AI answers

Run an AI visibility scan, then create recurring ModelSaid prompts around the problems, categories and comparisons the campaign addresses. Capture whether the company appears, which sources are cited, what claims are repeated and whether qualifiers survive. Compare observations before and after publication, but describe changes as correlations unless you have stronger evidence. Monitor competing sources too; the goal is not maximum mentions, but accurate inclusion when your expertise or offering genuinely fits.

Maintain the evidence after the campaign ends

Keep the canonical resource live, correct broken downloads and annotate methodological changes. When a statistic becomes outdated, label its period instead of silently presenting it as current. Ask publishers to repair material errors and preserve their editorial independence. Schedule a six- and twelve-month source audit for evergreen campaigns, checking whether the method, executive attribution and company description remain valid. Reuse the underlying research only when the original scope still fits; otherwise commission a fresh analysis and preserve the old edition. Track referral quality and journalist relationships alongside AI observations so the program retains value even when assistants do not cite it. AI systems may retrieve pages, cite indexes, use older data or rely on private model knowledge that you cannot edit directly. Durable digital PR therefore combines a useful public contribution, independent scrutiny, clean source records and long-term monitoring rather than a one-week burst of links.