The honeymoon phase of generative AI is officially over, and enterprises are finally waking up to a harsh reality: 87% of IT leaders admit that poor data readiness is completely blocking their AI initiatives from reaching production. Shirshanka Das, co-founder and CTO of DataHub, explains that the industry's obsession with tuning prompts and juggling the latest foundational models is missing the forest for the trees, as even the most advanced AI agent will hallucinate disastrously if it's fed garbage organizational context. To bridge this massive "perception-reality gap," organizations must stop treating context engineering as a niche AI task and instead elevate context management into a centralized, crowdsourced infrastructure layer that finally gives these digital employees the trustworthy memory they need to actually do their jobs.