At some point during this process, someone in your organization is going to say something along the lines of: “But these aren’t real people.”
They’re not wrong. And they’re not entirely right either. How you respond to that objection determines whether your AI-assisted persona work becomes a genuine strategic asset.
Let’s talk about how to get that answer right.
Let’s not be dismissive about this. There’s real research behind it, and it’s worth knowing what you’re actually defending against.
A study from Columbia University of 52 research articles on generative AI for persona development found major evaluation gaps, with only 19.2% following standard persona development approaches. That means most AI persona work happening right now isn’t being validated against the people it claims to represent.
Worse, LLM-generated personas exhibit increasingly positive sentiment and higher subjectivity as more details are added, often portraying idealized individuals with strong community values and minimal life challenges. When the AI is left to its own devices it tends to generate aspirational people. Put-together, thoughtful, environmentally conscious, and nothing like the imperfect and often contradictory humans your marketing actually has to reach.
Research in the International Journal of Human-Computer Studies has rated hallucinations, over-sanitization, and lack of standardization as the top concerns for AI-generated personas, with hallucinations scoring highest at 5.94 out of 7. And there’s a particular type of AI hallucination that’s especially dangerous in persona work: research found that when AI models hallucinate, they tend to use more confident language than when providing factual information and are 34% more likely to use phrases like “definitely,” “certainly,” and “without doubt” when generating incorrect information.
The more wrong the AI is, the more certain it sounds. But a hallucinated persona doesn’t come with a disclaimer. Instead it comes with a name, job title, backstory, and confident summary of its motivations.
According to a Deloitte study, 47% of enterprise AI users admitted to making at least one major business decision based on hallucinated content. So yes, the objection to AI is fair. Now here’s how to address it.
The fix for hallucinated, over-sanitized personas is to treat AI output as a hypothesis rather than a finding. Here’s what that looks like in practice.
I know many AI tools require you to pay for their more advanced features and that can be tough if you have a tight budget, but an AI given only a product description and asked to generate a persona is essentially writing fiction. It has nothing to work from except pattern-matching against whatever it was trained on, which skews heavily toward English-speaking, Western, tech-literate populations. They’re projecting a statistical average filtered through cultural, economic, and geographic bias.
The solution is to give the model actual inputs: CRM data, support ticket themes, search behavior clusters, interview transcripts, social listening outputs. The persona it generates from those inputs is a synthesis of evidence.
This constrains what the AI can draw on when generating outputs, essentially forcing it to answer from supplied sources rather than open-domain memory, reducing guessing. For persona work, this means building a structured knowledge base from your actual research (transcripts, behavioral data, surveys) and generating persona outputs against that base rather than against the model’s training data alone.
Concerns about data quality, algorithmic bias, hallucinations, and lack of emotional nuance can all impact trust in AI systems. Earning that trust back means building validation steps into the workflow:
Here’s the framing that defuses most of the “not real people” objection: synthetic personas aren’t replacements for real people.
Not many people would argue that a pilot is cheating by training in a simulator before flying a real plane. The simulator doesn’t replace real flight. It just makes the real flight safer and more efficient by eliminating certain categories of error before they happen at altitude.
Marketers can use synthetic personas to launch focus groups in seconds to test campaigns, products, and ideas virtually, safely, and at scale before committing resources to real-world execution.
The practical use case is hypothesis generation and pre-screening. Before you spend money fielding a real survey or commissioning a research study, synthetic personas let you test your assumptions, identify gaps in your thinking, and surface the questions worth asking in actual human conversations. Think of them as a rough draft and not the final edit.
Yes, there are domains where synthetic personas are actively misleading. It’s knowing where those boundaries are that separates teams that use this well from teams that don’t.
The marketer of the future will be less of a project manager and more of a curator and validator of AI-driven strategic options. That’s the job now: to know which outputs to trust, which to challenge, and when to put down the tool and talk to an actual human being. Personas will continue to guide marketing for years to come, so shouldn’t we make the process as easy and accurate as possible for ourselves?
At the end of the day, better personas make your marketing look smarter and keep you from making expensive, very public mistakes. AI gives you the power to move faster, test more, and generate insights on demand. It also gives you the ability to be confidently wrong at scale.
Marketers don’t need to hoard the most tools or prompt the fastest to be successful. But they do need to know when the output is nonsense, when to question it, and when to actually talk to a human being. Use AI to sharpen your thinking and not to outsource it.
If your brand isn’t being retrieved, synthesized, and cited in AI Overviews, AI Mode, ChatGPT, or Perplexity, you’re missing from the decisions that matter. Relevance Engineering structures content for clarity, optimizes for retrieval, and measures real impact. Content Resonance turns that visibility into lasting connection.
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