TL;DRRob Hanna of Precision Content says enterprise AI underperforms because organisations treat language like structured data. The real bottleneck is ungoverned documentation, and technical publications teams already have the skills to fix it.
Rob Hanna observes that many enterprise AI initiatives may be losing momentum because organizations continue to treat language like structured data while overlooking the systems that make knowledge reliable. The co-founder and CEO of Precision Content, a technical communications consultancy, says, “Longstanding technical publications teams already possess many of the capabilities needed to establish a scalable content supply chain that supports AI, although those teams aren’t always included in strategic AI discussions.”
Conversations surrounding enterprise AI often focus on increasingly sophisticated models, expanding infrastructure, and new platform capabilities. Hanna observes a different pattern emerging inside organizations. “I’ve seen AI copilots produce inconsistent responses, enterprise search programs struggle to meet expectations, and customer service assistants deliver experiences that leave users wanting greater confidence in the information they receive,” he shares. From his perspective, these outcomes invite a broader discussion about the quality of the knowledge supporting AI instead of focusing exclusively on the technology itself.
