Key Takeaways
- Salesforce has launched over 30 new AI features for Slackbot, repositioning it as an autonomous work assistant with cross-application capabilities and deep CRM integration.
- Enterprise collaboration platforms are rapidly evolving from simple assistants to agentic AI systems capable of orchestrating multi-step workflows and proactively managing tasks across enterprise infrastructure.
- The next generation of collaboration AI prioritises seamless context sharing across CRM, meeting platforms, and project management tools — reducing manual oversight and embedding AI directly into daily workflows. Salesforce has quietly raised the stakes for enterprise collaboration, launching more than 30 new AI features for Slackbot that push it well beyond a chat assistant into something closer to an autonomous workflow engine. The move is part of a broader race among Microsoft, Google, and Zoom to transform their platforms from communication tools into intelligent operational layers — systems that don’t just support work, but actively orchestrate it.
Slack’s Agentic Slackbot 2.0 Redefines Workflows
Powered by Anthropic’s Claude, the upgraded Slackbot introduces reusable AI skills and connects to external tools via a new Model Context Protocol (MCP) — enabling it to operate across a user’s entire desktop, not just within Slack itself. In practice, that means Slackbot can now listen to meetings on Zoom or Google Meet, summarise decisions, generate action items, and log them directly into a CRM system without any manual intervention. New memory functions allow Slackbot to retain user preferences across sessions, making it progressively more useful over time. The ambition here is clear: Slack wants to become the central interface through which enterprise workers interact with all their tools, reducing the need to switch between applications to get things done. For a deeper look at securing these kinds of agentic systems, see our guide on how to secure AI agents against unexpected actions.
Microsoft Teams Copilot Evolves with Advanced Admin Controls
Microsoft is taking a more measured approach, pairing Copilot capability upgrades with stronger administrative oversight. A new dashboard in the Teams Admin Center gives organisations improved visibility into AI feature adoption — covering speaker attribution, voice isolation, and face-based room experiences — which matters considerably when managing AI deployments across large, distributed workforces. Copilot is also gaining support for custom dictionaries, improving transcription accuracy for industry-specific terminology. Intelligent meeting recaps are being enhanced with video-based summaries, timestamped links to key moments, and auto-generated action items. Meanwhile, Microsoft’s broader Microsoft 365 Copilot roadmap includes role-based agents — such as a Sales Agent designed to function as a daily command centre for deal management — positioning Teams as an AI-powered productivity platform rather than simply a communications hub.
Google Workspace Gemini Deepens Contextual Integration
Google is advancing Gemini’s integration across Workspace with a focus on continuity and context. Updated capabilities allow Gemini to carry understanding across conversations and apps — helping users resume tasks, manage scheduling in Gmail, and access in-meeting assistance across more languages in Google Meet. Alongside these productivity features, Google has detailed its ongoing efforts to defend against indirect prompt injection attacks in Workspace — a threat vector where malicious instructions are embedded in data processed by large language models. As Gemini takes on more agentic capabilities within Workspace, that security work becomes directly relevant to enterprise risk. Organisations deploying AI at this level of integration should be paying close attention to how production AI environments are secured as these threat surfaces expand.
Zoom AI Companion 3.0 Unleashes Agent Builders and Workflows
Zoom is repositioning its platform as a “system of action” — a phrase that signals a deliberate shift away from meetings-as-product toward workflow automation as the core value proposition. AI Companion 3.0, expected by mid-2026, will introduce no-code agent builders that allow users to automate multi-step tasks, convert meeting content into deliverables, and interact with third-party tools without writing a line of code. A new “AI canvases” feature will let users create and edit documents, spreadsheets, and presentations directly from conversation context. Zoom has also rolled out agentic AI features across Zoom Workplace, Zoom Phone, and Zoom CX, embedding workflow automation into both communications and contact centre interactions. The strategic intent is to reduce friction at the point where conversation ends and execution begins.
Agentic AI Orchestration Platforms Emerge as Enterprise Hubs
The individual feature updates from Slack, Microsoft, Google, and Zoom point toward a larger structural shift: the emergence of collaboration platforms as agentic AI orchestration layers. Rather than acting as passive tools, these platforms are being built to set goals, make decisions, and execute multi-step tasks across CRM, ERP, project management, and knowledge base systems — with minimal human intervention. Slack’s MCP integration is a concrete example of how this coordination logic is being built into the platform layer itself, routing work to the appropriate agent or application within a user’s ecosystem. The commercial rationale is straightforward: if a platform can function as the unified automation layer for an enterprise, switching costs become substantial and stickiness increases significantly.
Intelligent Meeting Summaries Drive Post-Meeting Productivity
Every major platform is investing heavily in AI-powered meeting intelligence, and the competitive differentiation is moving well beyond basic transcription. Slack can now capture meeting output and push action items directly into CRM systems. Microsoft Teams generates video-highlighted recaps with timestamped links to key decisions. Zoom’s AI Companion categorises discussions, assigns task owners, and sets deadlines from voice and call content automatically. In hybrid work environments — where meeting participation is often asynchronous — these capabilities have measurable operational value: faster catch-up, clearer accountability, and less time spent on follow-up administration. The direction of travel is toward AI that participates in meetings as an active context-capturer, not just a passive recorder.
Data Security and Governance as AI Collaboration Foundations
Deeper AI integration into collaboration platforms creates a proportionally larger attack surface, and the leading vendors are responding — though with varying degrees of transparency. Google’s published work on mitigating indirect prompt injection in Workspace is notable precisely because it acknowledges the threat explicitly rather than treating security as a marketing checkbox. Microsoft’s voice and face enrollment dashboard in the Teams Admin Center gives administrators direct control over sensitive biometric data tied to AI features — a meaningful governance capability as regulatory scrutiny of biometric data increases. Across the sector, enterprise-grade compliance frameworks — SOC 2, ISO 27001, role-based access controls, and auditability — are becoming baseline requirements rather than differentiators. For organisations evaluating these platforms, security and governance architecture should be assessed with the same rigour as feature capability. Stay ahead of the curve with daily enterprise AI coverage at Auton AI News.
Originally published at https://autonainews.com/slacks-30-new-ai-features/
