AI knowledge: context over retrieval
Organisations are treating AI as core infrastructure for knowledge work, but multiple sources argue that retrieval alone is insufficient—context, freshness and explicit ownership are needed for useful results. The discussion spans summit reporting and practical guides that contrast retrieval‑augmented generation with broader 'context management' and stress governance and information hygiene. (economictimes.indiatimes.com) (lead.app) (happeo.com) (datahub.com) (securitybrief.com.au)
Companies are finding that an artificial intelligence search box is not enough to run knowledge work. The newer argument is that systems also need current documents, clear owners, and rules for what counts as trusted context. (economictimes.indiatimes.com) (datahub.com) The Economic Times said on April 15 that its Future of Knowledge Work Summit 2026 comes as Indian companies move from artificial intelligence pilots to “core business functions,” with leaders in Bengaluru focusing on what works in enterprise deployment. The event was announced earlier this month as a one-day summit on artificial intelligence, data intelligence, and automation. (economictimes.indiatimes.com 1) (economictimes.indiatimes.com 2) Retrieval-augmented generation is the standard pattern behind many enterprise chat tools: the system searches outside documents at question time and feeds selected passages into the model. DataHub wrote on April 15 that this is “one technique,” while “context management” is the layer that makes retrieved material discoverable, governed, and consistent. (datahub.com) Lead.app made the same point in operational terms on April 15. It said teams need the right document, owner, or past decision in the moment, not just more search results from folders, chats, and outdated wikis. (lead.app) Happeo’s guide on information overload says the failure often starts before the model answers anything. It points to missing structure, weak findability, and no regular review cycle, which leaves outdated and accurate documents sitting side by side until employees stop trusting the knowledge base. (happeo.com) That has turned “freshness” into a management problem, not just a software feature. Lead.app says useful systems need a source of truth and content hygiene, while Happeo says every team needs clear ownership and review so workers can tell which version is current. (lead.app) (happeo.com) Governance is moving up to the board level as companies wire these tools into operations. KPMG and INSEAD launched AI Governance Principles for Boards on April 14, saying boards need oversight of strategy, technology and security, workforce accountability, trustworthy artificial intelligence, and the board’s own use of the technology. (kpmg.com 1) (kpmg.com 2) KPMG said its latest Global AI Pulse Survey found nearly three quarters of boards are perceived to have only moderate or limited artificial intelligence expertise. INSEAD said boards are now expected to show how artificial intelligence is procured, deployed, and monitored, with clear lines between machine decisions and human judgment. (kpmg.com) (insead.edu) The practical shift is simple: retrieval answers “what can the model pull in,” while context management answers “what should the company trust.” As artificial intelligence moves from pilot projects into daily operations, that second question is becoming the harder one to ignore. (datahub.com) (economictimes.indiatimes.com)
