Three years ago, on November 30, 2022, the official release of ChatGPT marked a turning point in artificial intelligence, propelling AI chatbots (or large language models) into the mainstream.

Since then, progress has been undeniable: LLMs' ability to process complex queries, summarize vast amounts of information and even assist in coding has improved considerably.

Yet, as Statista's Tristan Gaudiat details below, hallucinations, misinterpretations of context and inaccuracies continue to plague even the most sophisticated of currently available models.

A study from the European Broadcasting Union and the BBC reveals that while the rate of inaccurate responses has declined since the end of last year, errors continue to be widespread.

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Data collected between May and June 2025 and analyzed by a cohort of journalists revealed that almost half of the responses (48 percent) from popular chatbots - free versions of ChatGPT, Gemini, Copilot and Perplexity - contained accuracy issues.

17 percent were significant errors, mainly regarding sourcing and missing context.

In December 2024, the rate of inaccurate responses (observed using a smaller answers sample) was significantly higher: 72 percent for all four LLMs. 31 percent were major issues in that case.

Despite gradual improvements, these shortcomings raise critical questions about reliability, especially in high-stakes applications like healthcare, legal advice or education. While AI developers keep pushing boundaries, users must remain aware of the technology's current limitations.