Artificial intelligence is now deeply embedded in everyday marketing workflows—but new research suggests accuracy hasn’t kept pace with adoption.

According to NP Digital’s AI Hallucinations and Accuracy Report, AI-generated errors are not only common, they’re increasingly slipping into live campaigns. Nearly half of marketers (47.1%) encounter AI inaccuracies several times per week, and 36.5% report that hallucinated or incorrect AI content has already gone public.

The findings underscore a growing tension in modern marketing: AI delivers speed and scale, but without sufficient oversight, that efficiency can introduce serious brand risk.

AI Errors Are Frequent—and Time-Consuming

The report combines two data sources:

• An accuracy analysis of 600 prompts tested across six major large language models (LLMs), including ChatGPT, Claude, and Gemini

• A survey of 565 U.S.-based digital marketers

Together, the data paints a picture of widespread friction between AI output and real-world accuracy.

More than 70% of marketers say they spend one to five hours each week fact-checking AI-generated content, eroding some of the productivity gains AI is supposed to deliver. Despite this effort, errors still escape into production.

“AI has become an incredible tool to accelerate efficiencies, but speed without accuracy creates real risk,” said Chad Gilbert, Vice President of Content at NP Digital. “What makes AI hallucinations especially dangerous is that many of them look believable at first glance.”

When AI Mistakes Go Live

Among marketers who reported publishing inaccurate AI-generated content, the most common issues included:

• False or fabricated facts

• Broken or nonexistent citations

• Brand-unsafe or misleading language

These errors often appear polished and confident, making them harder to detect without careful review. Once published, they can damage credibility, confuse audiences, or expose brands to compliance and reputational risks.

Yet despite these dangers, 23% of marketers say they are comfortable using AI output without human review, a gap between awareness and behavior that the report flags as particularly concerning.

No Model Is Error-Free

NP Digital’s accuracy testing also evaluated how different LLMs perform under scrutiny.

• ChatGPT delivered the highest rate of fully correct responses at 59.7%

• No model consistently avoided hallucinations

• Error rates increased sharply for:

  • Multi-part questions

  • Niche or specialized topics

  • Real-time or time-sensitive queries

The most common hallucination types across all models included:

• Omissions

• Outdated information

• Fabrication

• Misclassification

Crucially, these errors were often delivered with high confidence—making them more persuasive and more dangerous.

Where AI Breaks Down Most Often

The report found that AI struggles most with tasks requiring precision, structure, or technical rigor, including:

• HTML or schema creation

• Full long-form content development

• Reporting and data-driven summaries

These are also the areas where marketers are most likely to trust AI to “just handle it,” increasing the likelihood of mistakes slipping through.

The Real Takeaway: AI Needs Guardrails

The data points to a clear conclusion: AI works best as an assistant, not an authority.

Strong prompts, defined review processes, and human oversight consistently reduce risk. With no single LLM emerging as reliably accurate across use cases, marketers can’t solve the hallucination problem by switching tools alone.

Instead, the report reinforces a mindset shift:

• Treat AI output as a draft, not a final answer

• Match AI tasks to its strengths, not its hype

• Keep humans accountable for what goes live

As AI becomes standard infrastructure in marketing, accuracy—not speed—may be the new competitive advantage.

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