"Slack believes it has a gold mine of data. According to the company, the conversation data between employees is said gold needed to feed AI with the right context. That data is now available within Agentforce, but also to third parties. In recent years, there has been a race to build the best LLMs and have sufficient computing power to enable AI. The latter has been achieved, and now it is time to collect the right data and context and feed it to AI agents."
"We are therefore seeing many SaaS providers busy cleaning up their data models, structuring them, and building applications differently. Slack believes in the power of conversation data. Conversations between colleagues about ongoing projects can be very valuable and contain data that is never recorded in official documentation. Consider, for example, a special project channel. This is often where agreements are made, the timeline is set, the end product is defined, the requirements are established, and the necessary functionalities are determined."
Slack positions workplace conversation data as a strategic resource for AI agents, arguing that chat channels capture decisions, timelines, requirements, and functionalities often missing from official documentation. Slack is exposing that data through Agentforce and third-party access, and adding a real-time search API plus a Model Context Protocol server to surface context. Many SaaS providers are restructuring data models and applications to supply AI with richer context. Organizations face fragmented data across hundreds of applications and silos, making agent training difficult. Enterprise search can help if disparate applications are connected. AI without contextual data becomes ineffective.
Read at Techzine Global
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