Slack Unveils Surfaces for Generating Charts Inside Conversations

Slack has unveiled Slackforce Surfaces, a new feature that creates materials and tools directly from conversations. With only text-based instructions to Slackbot, it generates interactive reports, polls, dashboards, explainers, microsites, and more. According to reporting by Emma Roth of The Verge, the system has AI gather the necessary materials from relevant conversations and connected external information. Its defining characteristic is completing visualization and sharing without leaving where the work happens.

In conventional workflows, content agreed upon in conversations had to be transferred to separate tools for aggregation and formatting. Spreadsheets, document creation, and presentation creation existed as steps separate from conversation. Slackforce Surfaces eliminates this separation, enabling generation and use where the conversation takes place. At its core is the idea of treating conversation records as source material.

A Content Generation Platform Complete Within Chat

Use of Slackforce Surfaces starts with a text-based instruction. Users tell Slackbot in words what report or summary view they need. The AI interprets the instructions and automatically assembles the components and display format. It supports multiple formats, including polls, dashboards, explainers, and microsites.

What is generated is not limited to static documents. A key feature is that it includes interactive elements that viewers can operate. It is designed on the assumption of viewer interaction, such as switching figures and displaying by category. It envisions handling materials as an extension of conversation.

As one example, a case was shown visualizing AI token usage with an amusement-park-inspired design. It displays usage by department, such as sales, design, and engineering, as a dashboard. While reflecting the趣向 of the user’s instructions, it enables comparison of figures. It can be described as an attempt to combine decorative appeal with practicality.

System Integrating Related Conversations and

External Information

For gathering materials, relevant conversations and connected apps are targeted. It pulls in information from external connections such as Google Drive and Salesforce. It cross-references decisions, figures, and progress reports contained in conversation records. It serves to consolidate distributed information into a single surface.

Instead of moving data to another tool to interpret it, have Slackbot assemble dashboards, materials, and reports where the conversation is, and address them jointly across the organization

Ryan Gavin, Chief Marketing Officer of Slack, conveyed the above in an email to The Verge. Placing conversation and generation in the same place aims to shorten the time from review to action. His remarks assume joint use across the organization.

As an example of use, a live dashboard showing the customer support queue was cited. Stakeholders other than those in charge can view the same surface and grasp the situation. A case presenting a financial forecast with a weather-themed design was also introduced. It is a use that presents figures pulled from connected sources in expressions aligned with the theme.

Expanding Collaboration Through Sharing

and Pinning

Generated Surfaces can be shared with colleagues. They support pinning to channels, keeping them continuously available for reference. In addition to viewing and operating, annotations can be added. Discussions around the materials can proceed in the same place.

Pinned surfaces function as shared assets of the channel. Members who join later can grasp the current status without tracing the history. Corrections and questions can be indicated directly through annotations. A cycle emerges in which conversation and deliverables feed into each other.

This operation fits well with regular reporting and progress sharing. Leaving reports created each time in channels also creates value as history. Using the polling function, opinion gathering can also be conducted on the same surface. Microsites could potentially be repurposed for internal and external communications.

An Extension of Slackbot Enhancements

This announcement builds on the ongoing improvements to Slackbot. Several months ago, Slackbot was reworked into something close to an AI assistant. It became able to summarize information across multiple channels, organize messages, and assist with scheduling. Its role as an organizer of conversations has been strengthened.

Last month, a channel for collaboratively generating code was added. A format was introduced in which multiple people create together with AI in the same place. Slackforce Surfaces extends this direction to material generation and visualization. The flow of producing actionable deliverables from conversation is gaining strength.

Across the industry, embedding AI into collaboration platforms is advancing. As Stack Overflow for Agents Beta Launch Shows AI Agent Knowledge Sharing indicates, sharing knowledge and連携 with AI agents is a major concern. Designs that treat conversation records as training material and reference information are increasing. Slack’s move can also be seen as in line with this trend.

Permissions and Rollout Overview

The scope of information intake is limited to what users have permitted. Slack explains that it references only information for which AI tools have been granted connections. Conversations and apps without permission are not included as materials. Organizational management policies and individual permission settings are the前提.

All workspaces where Slackbot is enabled are covered. In addition to paid users, free users are also included. It is configured to be available without requiring an additional dedicated contract. It is easy to adopt even for small organizations and groups at the trial stage.

Integration with live data is scheduled to begin in October. At the time of reporting, the framework for generation was shown, with operational use as the next stage. Permission settings and connection configurations need to be confirmed in advance. Establishing operational guidelines will determine the effectiveness of adoption.

Editorial Opinion

In the next 3 to 6 months, we expect some regular reporting and aggregation work to be replaced by conversation-driven processes. Staff will reduce transcription to separate tools and focus on review and revision. In the early stage of adoption, setting up permissions and operational guidelines will determine success or failure.

In 1 to 3 years, we expect artifacts generated from conversation records to move closer to formal business deliverables. Version control and audit対応 for dashboards and explainers will become new challenges. Because the quality of accumulated conversations will affect generation results, how records are kept will be called into question.

Is the transparency of generation grounds sufficient. Even within permissions, displaying sources and retaining edit history will be essential. Responsibility sharing when errors are introduced must also be clarified. Whether convenience and verifiability can be balanced will be the issue.

References

• “Slack can now vibe-code interactive charts and reports inside chats”, by Emma Roth — The Verge, 2026-09-10T21:25:21.000Z (ARR)
• Source URL: https://www.theverge.com/tech/989853/slackforce-surfaces-launch