Invisible AI errors pose a growing threat to business trust

New data from Testlio has revealed an increase in reliability issues in enterprise artificial intelligence deployments, with 82% of errors attributed to hallucinations and accuracy errors.

The results point to what Testlio calls “invisible errors,” where AI systems provide false or fabricated information while appearing to function without errors.

Invisible errors

Testlio gathered these insights from thousands of tests of enterprise AI products over a six-month period. The data shows that most errors in enterprise AI systems are not due to visible crashes or error messages, but rather to AI models generating misinformation that is often not recognized until consequences occur. Such problems are harder to detect than traditional software errors, which are usually more obvious and reproducible.

Companies using chatbots, retrieval-augmented generation (RAG) systems, and other AI-powered solutions sometimes face results that range from sometimes inaccurate…