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Factual Content Strategy for AI Search

Factual Content: Elevating Your Content Strategy for AI Search

In a world flooded with information, how can you ensure your content is trusted? The answer lies in factual accuracy.

Learn why this marketing strategy is important updating your content marketing strategy for 2025. When you publish content, your reputation depends on how trusted your statements are. Factual accuracy ensures the helpfulness and reliability of AI generated outputs by anchoring them to real, factual information, preventing AI search from creating fabricated or misleading responses.

Factual information is information that solely, and directly seeks to encompass facts. It contrasts with giving theories, opinion, or personal interpretations. For bloggers, journalists, and trusted authors, prioritizing fact-based content isn’t just about accuracy—it’s about building trust and credibility with their audience.

Table of Contents

Why Factual Content Matters

Factually-correct content helps you build trust and avoid misinformation.

Both facts and opinions matter when it comes to decision-makers making choices. What you say online matters to your potential clients and customers. In the world of AI hulinicatinatctions, you protect your business entity by helping AI bots and humans understand the difference between when you state facts and opinion.

When you thoroughly fact-check your articles before publishing, you demonstrate that you’re serious about your online integrity. You can minimize AI hulinicatinatctions and AI privacy risks by incorporating factual content from trusted sources that supports your opinion. Fact Checking through schema markup offers proof of your sources. However, schema markup for fact-checking simply indicates that you are providing sources for your claims; it does not necessarily “prove” that your sources are correct. It makes your sources known to search engines and users by clearly structuring your information about the claim; readers should assess the sources.

I use Gemini in my Google Workspace and now can see links to related content in responses to my fact-seeking prompts. By clicking the arrow chips next to its response, I dive more into the topic and its sources. If fact, it can also display inline links to relevant emails referenced in responses where the Gmail extension is used.

If a fact-check article is relevant to your query, you might see a preview for it appear in your search engine result pages (SERPs). If your entity gets in these displayed snippets, users can quickly gain context about a specific claim that your make and navigate to your website to learn more.

The Power of Facts: Benefits for Your Content and Brand

Fact-based content wins readers’ trust. It not only can strengthen journalism, but directly builds authority for your brand and domain.

How does fact-based content build turst? It accomplishes this by offering verifiable information that aligns with reality, demonstrating credibility and reliability to your audience and search engines. It is essential for establishing a positive perception of your sources and encourages engagement with your content.

For International Fact-Checking Day, Google posted about four Search features to helps searchers evaluate information. and get key context to make sense of what you’re seeing online. And to give more people access to these tools, It also expanded two “About this image” in Google Search and “more about this page.” I also like using the Google Fact Check Explorer.

People want to know they are consuming content from objective sources.

“Fact Check Explorer helps journalists and fact-checkers dig deeper into a topic. When you search for a topic, you can easily find fact checks that have been investigated by independent organizations from around the world. And now you can use Fact Check Explorer to find out more about an image. Previously in beta, this feature lets you upload or copy the link of an image into the Fact Check Explorer to see if it’s been used in an existing fact check. Journalists and fact-checkers can also use it through the Fact Check Tools API, which gives them the ability to show relevant fact checks for an image on their own websites.” – 4 Ways to use Search to Check Facts, Images and Sources Online

When you focus on facts, you minimize the risk of spreading misinformation and establish yourself as a source of reliable information. This, in turn, has a direct impact on your “Trust” factor, which is critical for success.

AI and Factual Content: Challenges and Solutions

The right content proofing strategy can help you overcome concerns that your content’s expert authors are trusted sources. Gain more readers by offering proof that your content is factual.

“Fact checking has been becoming more popular since the early 20000s, however it has grown in popularity greatly in recent years. As of 2016, there were 113 active fact checking groups across the globe, 90 of which were established post 2010 [1]. With the rise of social
media and “fake news” spreading throughout the web [2], fast and accurate fact checking is now more imperative than ever.” – Using NLP for fact checking

Fact checking relies on trusted sources of evidence

Various research projects into automated fact checking have been the focus of multiple research projects that I’ve followed over the last 10 years. Disclosure of your sources of evidence, and how you grounded your fact checking, the methodologies used, as well as explaining how they have been curated – builds trust. For my research, commonly, I rely on fact databases, the Internet, external sources, in addition to communications with the originator of the claim.

Fact databases catalog and store pre-checked claims, published facts, or world knowledge, including possible augmentation by claims from trustworthy sources. The stored facts are often triplet representations in numeric AI form of fact checked claims.

Triplet representations of factual entities in databases help perform fact checking tasks conducted by researchers. Open sources permit downloading machine learning generated datasets of the Freebase database that relate to the “statistical_region” entity type. We see more use cases that often require more complex representations.

Fact-Checking: How to Ensure Content Accuracy

One of the best ways to ensure content accuracy is to leverage structured data; it supports factual content. Schema markup supports triplet representations of factual entities in databases. These are highly beneficial for fact-checking tasks because they provide a structured way to store and access factual information. This allows for efficient information retrieval and comparison against a claim to verify its accuracy. Basically, this is accomplished by representing facts as “subject-relation-object” triples. Then AI Search systems can easily identify relevant information to assess the truth of a statement.

Personally, for YMYL sites, in particular healthcare content marketing, I find that implementing a ClaimReview element for Search in Article schema can be valued as an essential type of schema markup that helps support E-E-A-T. I’ve found better attraction in search keeping factual claims to 75 characters to ensure that the claim fits in allotted Google Search spaces.

ClaimReview is useful to summarize a fact-check; it notes the person and claim being checked, as well as a conclusion about its accuracy, according to the Claim Review project, which I’ve supported for years. Thankfully, viral content tends to be factual in nature.

The “Enriching ClaimReview for Fact Checkers” 2021 article by Andrew Dudfield (Head of Automated Fact Checking at Full Fact) and Leigh Dodds (an open data expert), states that ClaimReview is one of the “hidden jewels” of the schema hierarchy. This is because it relies on human fact-checkers. I like how they talk about “exploring ways to revise and extend the claim review metadata to provide more detail that might enable further reuse and labeling of content, and further insights into the fact checking process.” [1]

Tighter Regulations in 2025 for Marketers’ Product Claims

In 2025, marketers are likely to face significantly stricter regulations regarding content factualness. There is a stronger focus on verifying information, preventing misinformation, and ensuring transparency. This will require marketers to prioritize fact-checking, source attribution, and clear disclosure practices to maintain compliance.

We’ve already seeing this occuring in the last four years; the legal demands for truthful and accuracte statements are ramping up.

Below is a table with a few examplies of where this has occured in the past four years.

EXAMPLES: Regulators (Federal Trade Commission) Sending Fines for Misinformation
Business Impacted False/Misleading Topic Outcome Source
Facebook Tracking microchips in the COVID-19 vaccine misleading statements The misinformation flagged by fact-checkers was 46 times less impactful than the unflagged content. science.org/doi/10.1126/science.adk3451
Williams Sonoma Misleading “Made in USA” claims on product landing pages The FTC fined Williams Sonoma nearly $3.2 million in 2020. In 2022, Williams Sonoma agreed to pay an additional $3.7 million in civil penalties after continuing to make misleading claims. ftc.gov/news-events/news/press-releases/2024/04/williams-sonoma-will-pay-record-317-million-civil-penalty-violating-ftc-made-usa-order
Albertsons and Vons Overcharged customers and engaged in false advertising communications Paid nearly $4 million to resolve a civil complaint brought by CA prosecutors cbs8.com/article/news/local/albertsons-vons-4m-settle-false-advertising-complaint/509-8999a488-dfcf-48f8-a8b9-26b117968f3d
Simple Health Plans LLC Selling bogus health care insurance ‘benefits’ that in fact left consumers unprotected Fined $195 million by the Federal Trade Commission (FTC) for misleading consumers about their health care plans, effectively selling “sham” insurance ftc.gov/news-events/news/press-releases/2024/02/ftc-obtains-195-million-judgment-permanent-ban-telemarketing-selling-healthcare-products-against
Southern California Medical Center & Universal Diagnostic Laboratories Paid marketers to refer Medicare/Medi-Cal patients to SCMC clinics To pay $10 million to settle DOJ and whistleblower charges of violating the False Claims Act, Anti-Kickback Statute, and Stark Law constantinecannon.com/whistleblower/whistleblower-insider-blog/doj-ends-2024-with-a-flood-of-false-claims-act-successes/
Sitejabber Misrepresented ratings and reviews by consumers who hadn’t yet received products or services FTC ordered anyone whether acting directly or indirectly, in connection with the advertising or promotion of any product, service, or business, must not provide to others the means or instrumentalities to misrepresent, expressly or by implication, that ratings or reviews of a product or service. Fine TBD. ftc.gov/news-events/news/press-releases/2025/01/ftc-approves-final-order-against-sitejabber-which-misrepresented-ratings-reviews-consumers-who-had

Far more damaging than the fine itself is the potential for ongoing revenue loss from a tarnished brand reputation. This article helps you discover practical, actionable strategies to enhance your content’s ranking potential in AI-driven search results with factual and true statements. “Stretching” the truth puts you at risk of decreased sales and customer loyalty. Maintain a positive brand image to avoid such detrimental impacts on revenue, especially in the context of optimizing content for AI search algorithms.

Understanding the FTC’s stance on misinformation

  • Truthful Advertising: The Federal Trade Commission (FTC) requires that all advertising and marketing claims be truthful and not misleading. This includes not just explicit statements but also implied claims and omissions of important information.
  • Substantiation: Marketers must have a reasonable basis for all claims they make. This means having sufficient evidence to support any assertions about the effectiveness, quality, or benefits of a product or service.
  • Disclosure: Marketers must clearly and conspicuously disclose any material connections between themselves and an endorser, influencer, or reviewer. This includes sponsored content, affiliate relationships, and paid reviews.
  • Health and Safety: Special care is required when making claims related to health, safety, or nutrition. These claims often require robust scientific evidence.
  • AI and Automation: The FTC is also paying attention to AI-generated content and holds marketers responsible for the accuracy and truthfulness of content, even if it was generated by AI.

You may be asking, “what does Google have to say on this topic?”

Google Search guidance about AI-generated content

Google uses “Consensus” when the truth of a statement is unclear

Search engines score a content piece by Boolean, meaning, they try making a “wrong” or “true” determination. When this isn’t an easy assessment due to multiple truths, too broad of an answer, or grey area, it is called an “uncertain inference.” In this case, Google may give the content piece a percentage of truth score (example: 30% 70%).

When this occurs, you can improve on your content’s trust factor by updating your content to better align with the consensus. Search engines prefer to display answers from site’s that have gained trust on a specific topic. This is why gaining topical authority in your niche is important.

For example, answering the question “What is the best SEO strategy?” will always be largely opinion based. It depends on the niche, experience, location, brand authority, competition, and many more factors. If you are answering this question and come afar field from the general consensus, your statement may be less trusted by a search engine.

In the healthcare niche, the topic of “best treatment options for a specific condition” is almost always opinion-based, as different healthcare providers may have varying perspectives on the most effective treatment approaches depending on their individual experience, clinical research interpretation, patient preferences, and which treatment options are available in that geolocation.

One aspect of your content creation strategy is to consider being in the “safe zone” by aligning with the consensus. It is often considered less risky to side with the majority viewpoint, as it provides a sense of security and avoids potential conflict or criticism for taking a divergent stance.

“How will Google address AI content that potentially propagates misinformation or contradicts consensus on important topics?

These issues exist in both human-generated and AI-generated content. However content is produced, our systems look to surface high-quality information from reliable sources, and not information that contradicts well-established consensus on important topics. On topics where information quality is critically important—like health, civic, or financial information—our systems place an even greater emphasis on signals of reliability.” – Google Search’s guidance about AI-generated content

Using AI Without Losing Credibility: The Importance of Factual Grounding

Factual grounding in AI content generation refers to the process of ensuring that the information produced by AI models is based on verifiable, real-world facts, rather than fabricated or speculative claims. It involves connecting the AI’s output to trusted sources and evidence, preventing it from generating misinformation or “hallucinations.” Essentially, it’s about anchoring AI-generated text to reality; it will always need human review and editing.

Marketers are held responsible for product claims

Federal law says that ad messages must be truthful, not misleading, and, when appropriate, backed by scientific evidence. As we can see in the above table, the FTC enforces these truth-in-advertising laws and is holding marketers accountable for what they publish.

On April 13, 2023, FTC Warns Almost 700 Marketing Companies That They Could Face Civil Penalties if They Can’t Back Up Their Product Claims.
The full list of 700 Marketing companies recieving notices that outline specific unlawful acts and practices is listed online. I find it stricking that many relate to the healthcare niche: Abbott Laboratories, Alaska Spring Pharmaceuticals Inc., Bayer HealthCare LLC, Doctor’s Signature Sales and Marketing International Corp., NeoCell LLC, Gemini Pharmaceuticals, Inc., Infirst Healthcare Inc., Medtech Products Inc., and many more.

I’m manage sites using a blend of expert human author creativity and AI efficiency. In every situation, we have extra people checking for accuracy in all statements before publication. Read my article on Healthcare Content Strategy for E-E-A-T and YMYL Criteria.

What to Look for in a Fact-Checked AI Writer

The term “Fact-Checked AI Writer” is emerging as businesses realize the need for accuracy when using AI content generation. Essentially, this is someone who goes beyond just generating text; they actively verify the information produced by AI to ensure it’s factual and reliable. For your organization, this means you’ll need clear processes to ensure anyone writing content, with or without AI, is prioritizing accuracy.

When hiring a freelance or in-house AI writer, here are key aspects to evaluate:

  • Experience: Look for a writer with a demonstrable track record of fact-checking or research-based writing, and ask for samples.
  • Transparency About AI Use: Require that they openly disclose which AI tools they are using. This ensures you can track the sources and methods of content generation.
  • Fact-Checking Process: Ask them to explain, in detail, their fact-checking methods. Look for writers who use reputable sources and understand fact-checking techniques. Ask how they were human reviewed and edited.
  • Judgement and Critical Thinking: AI can generate text quickly, but the human writer needs to be able to critically review and refine AI’s output using their judgement. Look for someone with a proven track record of editing and refining content to make it more accurate and useful.

Why Is This Important?

AI is a great tool, but it is not a replacement for the writer who understands accuracy. As AI becomes more prominent, businesses need to employ writers who are not just capable of working with AI, but also understand the importance of ensuring factual accuracy and creating helpful content.

“The output of generative AI often requires considerable reworking in order to appear to be labor-saving. Copywriters are hired to edit and “re-humanize” poorly written, AI-generated text while being paid less for doing similar work they had done in the past under the rationale that they contribute less value. Workers are expected to take on responsibilities assumed to be seamlessly delegated to AI. An industry-wide survey report from AP News examining journalists’ adoption of generative AI found that in some cases it functioned, as one journalist respondent put it, much like self-service checkout, in that staff journalists are increasingly expected to do extra editing or proofreading work that would have otherwise gone out to contract freelancers.” – The Critical AI Report, December 2024 Edition [3]

So how does a content writer, using any form of AI, ensure that what they publish will prove up factually in AI answers?

Tools & Techniques: Practical Steps for Fact-Checking

The medical industry commands the most need for fact finding resources – Facts Leaderboark in Kaggle

Okay, so we’ve established why fact-checking is crucial. Now, let’s get practical. This section will equip you with the specific tools and techniques you need to verify information and ensure your content is grounded in facts. Whether you’re an experienced writer or new to the process, you can build a robust fact-checking system.

Factual content in AI answers

The tools you choose to use for your content writing are very important.

When Google was recently questioned about Gemini’s fact-check measurements, the company pointed out its December 2024 release of the FACTS Grounding benchmark. Its purpose is to check Large Language Model (LLM) responses to make sure “that are not only factually accurate with respect to given inputs, but also sufficiently detailed to provide satisfactory answers to user queries.”

The launch of FACTS comes out of partnership between Google DeepMind and Google Research for evaluating the factual grounding of LLMs.

“The FACTS Grounding benchmark evaluates the ability of Large Language Models (LLMs) to generate factually accurate responses grounded in provided long-form documents, encompassing a variety of domains. FACTS Grounding moves beyond simple factual question-answering by assessing whether LLM responses are fully grounded to the provided context and correctly synthesize information from a long context document. By providing a standardized evaluation framework, FACTS Grounding aims to promote the development of LLMs that are both knowledgeable and trustworthy, facilitating their responsible deployment in real-world applications.” – FACTS Leaderboard

With AI Overviews displaying quick answers, many sites have dropped in Google Search, while others see gain because they’re better prepared and included in AI Overviews. They are increasingly helping people find answers to their search queries.

As companies learn how to use generative AI apps, grounding your work will help you monitor your factual and trust scores.

The power of Knowledge Graphs’ factual database

In response to people’s concerns, researchers are developing powerful tools to help navigate the digital AI landscape. One of these tools is called a “knowledge graph.” A Google Knowledge Graph is a database of facts that are linked together in a structured way. The tech giant and other similar platforms/tools seek to help people find and analyze fact-checked claims.

Google has first reviewed reputable fact-checking organizations. It then stores the claims made along with information about the authors, dates, sources, and even the entities (people, places, organizations) mentioned in content claims.

Why is this important to you?

The explosion of AI content is making readers more critical of the information they encounter online. You can help them identify you as a reputable source.

Recommended tools for checking facts:

  • Google’s DataGemma grounds LLMs to ensure more factual results.[4]
  • FACTS Grounding text embedding model in Kaggle.
  • AI Content Checker for ChatGPT – Originality.ai
  • You can fact check in NotebookLM.
  • Fact-checking from JinaAI let you provides a statement and search for references that support or contradict it.
  • Fact-Check Insights puts the power of a global database of fact-checks at your fingertips.

Once we recognize the importance of proving up as a source of reputable content, how do we move forward with factually grounding our LLMs?

Future of Factual Content in an AI World

The growing importance of factually grounding LLMs for generative IR systems is growing in recognition.

There is a growing awareness of the critical need to ensure these responses are factually accurate by “grounding” them in reliable data sources. I was intrigued by an article that Dawn Anderson recommended a key read on this topic. Full funnel marketing relies on trust at each point of influence.

Building brand impressions is becoming more important than web traffic metrics. When you surface in generative IR systems, your answers need to be recognized for correct knowledge.

This means establishing domain competence.

Driving high website traffic simply isn’t enough going forward. Businesses need to focus on actively building a strong brand perception and being established as credible experts within their industry. This is particularly true when interacting with AI systems like generative AI where accurate information is crucial for a positive brand impression.

“For the purposes of evaluating a generative IR system, there is much to consider. Retrieval Augmented Generation represents a coalition of IR and generative systems to accomplish a task. It is necessary to consider evaluation of these component systems in concert as well as individually. It is also necessary to establish the domain of competency of generative IR systems. A challenge with the output of a generative system is that it always expresses an answer with apparent condence. There is great value in knowing the knowledge domain that a system is competent in. How do we establish and communicate that competency? In a related topic, we don’t know how an LLM is achieving its answers. A research challenge is to establish a methodology for building condence in the output of LLMs.” – Future of Information Retrieval Research in the Age of Generative AI [5]

In 2025, effective healthcare marketing strategies stand at a pivotal moment of transformation, where technological innovation offers unprecedented opportunities to improve patient education and engagement. However, the success of these advancements hinges on our ability to address critical challenges.

In 2025, an array of new laws are slated to take effect on issues like artificial intelligence. Currently, some states are taking the lead in filling gaps from the lack of federal legislation on AI. Illonios and California have already begin to regulate uses of AI with the aim of mitigating the potential harms of the rapidly growing technology. [6]

CONCLUSION: Publishing With Integrity

Trusted brand sources are winning online. If you are publishing healthcare question answering content, being factual is critical. Ready to build trust with factual content in 2025? Contact us for a free consultation on strengthening your SEO strategy.

Call 651-206-2410. Start the year ahead with a strong SEO Strategy using AI and Factual Content

 

Resources:

[1]Andrew Iliadis, et al, “One schema to rule them all: How Schema.org models the world of search,” Feb 2023, https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24744

[2] Aiha Nguyen and Alexandra Mateescu, “Generative AI and Labor: Power, Hype, and Value at Work,” Dec 2024, https://datasociety.net/wp-content/uploads/2024/12/DS_Generative-AI-and-Labor-Primer_Final.pdf

[3] Brian Merchant, “The Critical AI Report, December 2024 Edition,” Dec 2024, https://www.bloodinthemachine.com/p/the-critical-ai-report-december-2024

[4] Prem Ramaswami and James Manyika, “DataGemma: Using real-world data to address AI hallucinations,” Sept 2024, https://blog.google/technology/ai/google-datagemma-ai-llm/

[5]James Allan, , et al, “Future of Information Retrieval Research in the Age of Generative AI,” Dec 2024, https://arxiv.org/pdf/2412.02043

[6] Isabella Ramirez, ”
New laws for 2025: AI safeguards,” Dec 2024, https://www.nbcnews.com/politics/politics-news/new-laws-2025-ai-safeguards-legacy-admissions-transgender-health-care-rcna185031

Jeannie Hill:
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