Agentic Capabilities in Slack: How Conversational Context Improves Productivity for Knowledge Workers and Developers

AI agents are only as powerful as the context they can access. See how Slack puts that context to work.

AI agents are moving from pilot to production. Their effectiveness depends on one critical factor: context.

In this IDC white paper, analyst Arnal Dayaratna examines how Slack’s unified architecture gives AI agents the organizational knowledge they need to act with confidence, while giving people a shared place to work alongside them. Slack brings together conversational history, workflow activity, integration signals, and permission-aware access in the same environment where teams communicate and make decisions.

More than half of surveyed developers (52%) report their organizations have adopted AI agents, and 66% have moved them into production. But agents that lack visibility into business constraints, prior decisions, and customer context create risk instead of value. Context determines whether production agents expand capacity or introduce new points of failure.

Download this IDC white paper to learn:

Why conversational context is the defining variable for AI agent success in the enterprise
How Slack reduces coordination overhead for knowledge workers and developers
Why Slack is positioned to become the coordination layer for multiagent work and human oversight

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