Enterprise AI adoption faces infrastructure and expertise challenges

As organizations transition from simple AI assistants to autonomous AI agents, the need for robust context infrastructure is becoming a critical business priority. While 84% of developers report using or planning to use AI tools, many enterprises struggle with fragmented knowledge spread across structured systems, unstructured documents, and human judgment. Without centralized and aligned context, AI agents may generate confident but incorrect responses.

Mid-market companies face similar hurdles in scaling AI. Although these firms are often more agile than large enterprises, research indicates that 90% of mid-market companies exploring AI remain in early stages or have experienced stalled pilots. To move beyond experimentation, businesses must address expertise gaps, establish solid data and technology foundations, and implement proper governance guardrails.