Can You Use AI to Write Content for Your Business? The Evidence You Need to See
AI writing tools promise to scale content production quickly and cheaply. But recent studies reveal alarming error rates that make AI-generated content risky for any business where expertise and accuracy matter. This article examines the evidence showing where AI fails, why Google's algorithms can detect AI content, and what businesses should do instead.
📚 Research Source: This article references data and findings from Search Engine Journal's comprehensive YMYL research study examining AI performance across health, finance, and legal content.
The Problem With AI-Generated Content
AI writing tools like ChatGPT and other large language models work by predicting the most statistically probable next word. This approach creates content that sounds plausible but often contains significant errors that most readers can't spot.
The statistics are sobering. A Stanford study from February 2024 tested GPT-4 with advanced retrieval systems and found that 30% of individual statements were unsupported by evidence. Nearly 50% of responses contained at least one unsupported statement. When Google's Gemini Pro was tested, only 10% of responses were fully supported.
These aren't minor discrepancies. In one documented case, GPT-4 gave treatment instructions for the wrong type of medical equipment. That kind of error could harm people during emergencies.
📊 AI Error Rates Across Industries
Where AI Fails Most Dramatically
Testing across different industries reveals consistent patterns of AI failure, particularly in fields where accuracy matters most.
Financial Advice
Money.com tested ChatGPT on 100 financial questions in November 2024. Only 65% of answers were correct. Twenty-nine percent were incomplete or misleading. Six percent were outright wrong. The system sourced answers from unreliable personal blogs, failed to mention important rule changes, and didn't discourage risky investment strategies like trying to time the market.
Legal Information
Stanford's RegLab study tested over 200,000 legal queries and found hallucination rates ranging from 69% to 88% for state-of-the-art models. AI hallucinates at least 75% of the time on court holdings. The AI Hallucination Cases Database tracks 439 legal decisions where AI produced completely fabricated content in actual court filings.
Health and Medical Content
When Men's Journal published its first AI-generated health article in February 2023, Dr. Bradley Anawalt of University of Washington Medical Center identified 18 specific errors. He described "persistent factual mistakes and mischaracterizations of medical science," including equating different medical terms, claiming unsupported links between diet and symptoms, and providing unfounded health warnings.
The article was "flagrantly wrong about basic medical topics" while having "enough proximity to scientific evidence to have the ring of truth." That combination is dangerous. People can't spot the errors because they sound plausible.
Why Google Prioritizes What AI Can't Provide
In December 2022, Google added "Experience" as the first pillar of its content evaluation framework, expanding E-A-T to E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness). This change directly targets AI's fundamental limitation.
Google's guidance now asks whether content "clearly demonstrates first-hand expertise and a depth of knowledge (for example, expertise that comes from having used a product or service, or visiting a place)." AI can produce technically accurate content that reads like a textbook. What it can't produce is practitioner insight that comes from real experience.
The difference shows clearly in the content. AI might define a medical condition accurately. A specialist who treats patients with that condition daily can answer the real questions people ask: What does recovery actually look like? What mistakes do patients commonly make? When should you see a specialist versus your general practitioner?
That's the "Experience" in E-E-A-T. A demonstrated understanding of real-world scenarios that only comes from actually doing the work. This connects to what we've discussed about why raw, authentic content converts better than polished productions lacking genuine insight.
The Homogenization Problem
Even when AI gets facts right, it creates another critical problem. UCLA research documents what researchers term a "death spiral of homogenization." AI systems default toward population-scale mean preferences because large language models predict the most statistically probable next word.
Oxford and Cambridge researchers demonstrated this pattern. When they trained an AI model on different dog breeds, the system increasingly produced only common breeds, eventually resulting in what they called "Model Collapse." The AI couldn't maintain diversity.
A Science Advances study found that "generative AI enhances individual creativity but reduces the collective diversity of novel content." Writers individually benefit, but collectively produce a narrower scope of content.
For businesses where differentiation provides competitive advantage, this convergence is damaging. If three contractors use ChatGPT to generate service descriptions for the same topic, their content will be remarkably similar. That offers no reason for Google or potential customers to prefer one over another.
Google's March 2024 update specifically targeted "scaled content abuse" and "generic or undifferentiated content" that repeats widely available information without new insights. This algorithmic change directly penalizes the kind of sameness AI naturally produces.
How Google Verifies Expertise
Google doesn't just look at content in isolation. The search engine builds connections to verify that authors have the expertise they claim. For established experts, this verification is robust. Professionals with publications, certifications, speaking engagements, and professional affiliations all have verifiable digital footprints.
This creates patterns Google can recognize. Your writing style, terminology choices, sentence structure, and topic focus form a signature. When content published under your name deviates from that pattern, it raises questions about authenticity.
Building genuine authority requires consistency. Reference past work and demonstrate ongoing engagement with your field. Link author bylines to detailed bio pages. Include credentials, areas of specialization, and links to verifiable professional profiles.
Most importantly, have experts write or thoroughly review content published under their names. Not just fact-checking, but ensuring the voice, perspective, and insights reflect actual expertise.
What This Means for Your Business
The Risk of AI Content
AI error rates between 30% and 88% depending on topic means significant portions of AI-generated content contain mistakes readers can't spot. These errors damage credibility and could harm customers who rely on your information.
Google's Detection Systems
Google's algorithms specifically reward experience and penalize generic, undifferentiated content. AI naturally produces the exact type of content Google's updates target for demotion in search rankings.
The Differentiation Problem
When competitors use the same AI tools, everyone produces similar content. You lose the competitive advantage that comes from unique insights, specific expertise, and authentic voice that customers actually value.
What Customers Actually Want
People don't visit your website to read textbook definitions they could find on Wikipedia. They want to connect with practitioners who understand their specific situation. They want to know what questions other customers ask. What typically works. What to expect. What red flags to watch for.
These insights come from years of actually doing the work, not from training data scraped from the internet. When a contractor says "the most common mistake homeowners make is..." that carries weight AI-generated advice can't match.
Readers can tell when content comes from genuine experience versus when it's been assembled from other articles. The authenticity matters for trust. In industries where people make important decisions about their homes, businesses, or properties, they need confidence that guidance comes from someone who has actually navigated these situations before.
This principle applies across all industries we serve. Whether it's marketing strategy for plumbing businesses or websites for commercial contractors, genuine expertise beats AI-generated generic content every time.
💡 The Right Way to Use AI
You can use AI as a tool in your content process. You can't use it as a replacement for human expertise. AI can help organize knowledge, structure insights, and make expertise more accessible. But the actual knowledge, insights, and experience must come from real people who do the work.
The value in business content comes from knowledge that can't be scraped from existing sources. It comes from the contractor who knows what questions customers ask before every project. The specialist who has guided clients through complex decisions. The professional who has seen which solutions actually work in real-world conditions.
The Strategic Choice
Organizations producing content face a decision. Invest in genuine expertise and unique perspectives, or risk algorithmic penalties, reputational damage, and content that fails to differentiate your business.
Google's addition of "Experience" to E-A-T in 2022 specifically targeted AI's inability to have first-hand experience. The Helpful Content Update penalized "summarizing what others have to say without adding much value," which is an exact description of how large language models function.
When AI error rates range from 30% to 88% depending on the topic, the risks outweigh the benefits. Experts don't need AI to write their content. They need help organizing their knowledge, structuring their insights, and making their expertise accessible. That's a fundamentally different role than generating content itself.
The businesses that treat content as a volume game, whether through AI or content farms, face an increasingly difficult path. The ones who treat content as a credibility signal and invest in genuine expertise have a sustainable model that actually serves customers while performing well in search.
Expertise Can't Be Automated
The evidence is clear. AI produces content with error rates between 30% and 88% depending on the industry. Google's algorithms specifically reward experience and penalize the generic, undifferentiated content AI naturally produces. When everyone uses the same tools, content becomes indistinguishable, eliminating competitive advantage.
The value in business content comes from insights you can't get anywhere else. It comes from professionals who know what questions customers actually ask. Who understand what solutions work in real conditions. Who can spot the mistakes others make and help customers avoid them.
AI can assist in organizing that knowledge and structuring those insights. But it can't replace the expertise itself. Businesses positioning themselves for long-term success invest in genuine expert content that serves customers and differentiates their business. Those relying on AI to scale generic content production are building on a foundation that both Google's algorithms and customer expectations are actively working against.
You can use AI as a tool. You can't use it as a substitute for actual expertise. That distinction determines whether your content builds credibility or undermines it.