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AI-powered Scrum Master assistant with OpenAI, Slack and Asana integration

ŁukaszŁukasz
4307 views
2/3/2026
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What is This?

This automation simulates Scrum Master role on daily meetings. Essentially it is an AI Scrum Master using different sources of data.

As intelligent support system for Scrum Masters that leverages data from Asana, Slack, and direct developer responses for comprehensive sprint status analysis and identification of areas requiring intervention.

As such it is usable for Scrum Masters (of course) but Scrum Team aswell, Product Owner and possibly Business Owner.

Who is it For?

This automation is designed for Agile teams to support the Scrum Master role by collecting and analyzing data from various sources to identify potential impediments and support the team in sprint delivery.

How Does It Work?

The workflow has four main data entry points, that are launched either on-click or on workdays.

First is collecting project section information from Asana. The automation retrieves project structure, available sections, and their organization, allowing the AI to understand the team's work context.

Second is getting recently modified tasks in the Asana project. The system tracks changes in tasks, their status, assignments, and updates to detect potential delays or issues.

Third is obtaining communication in the team's Slack channel. The flow collects data about recent conversations, discussion threads, and team communication to identify warning signals or areas requiring attention.

Fourth is directly collecting responses from developers about the current sprint - their progress, impediments, concerns, and support needs.

All collected data is passed to an AI model that analyzes it within the Scrum methodology context and identifies:

  • Potential impediments in sprint delivery
  • Areas requiring Scrum Master intervention
  • Recommendations for team support
  • Warning signals regarding Sprint Goal achievement

Output is being pushed to Slack channel so it can be potentially used by another iteration of same flow itself via Slack channel history.

Requirements

  1. You need Asana oAuth credentials
  2. You need OpenAI / alternative AI for processing data
  3. You need to have Slack app with proper permissions
  • channels:history
  • chat:write
  • groups:history
  • im:history
  • mpim:history
  • users.profile:write
  • users:write

Configuration

  1. Set up node "Asana Project and Slack Channel". Provide Asana project ID and Slack Channel ID
  2. (optional) Set up node "Get Scrum Master Answers". There are daily questions/answers that are being sent to channel.

Alternative use

You can get rid of the whole "Ask Users Daily ScrumMaster Questions" part if you don't want to do it simirarly as "daily Scrum standups". In such case whole flow is essentially changed to static analyzer of project status based on Slack and Asana.

Extensions and Customizations

There are many possibilities to extend this automation depending on team needs. For example, you can add integration with additional project management tools, implement different notification schemes based on detected issue criticality, or adjust data collection frequency to match the team's work rhythm.

Disclaimers and Notes

Whole automation has one important assumption: project is run on single Slack channel and on single Asana board. Of cource this can be extended, but is beyond currently designed scope.

Adding new sources for AI to analyze should be fairly easy - just add another branch of data and push it to AI prompt.

This automation represents a proof-of-concept and should not replace an actual Scrum Master. The Scrum Master role extends far beyond data collection and analysis - it requires deep understanding of team dynamics, business context, and interpersonal skills.

As Scrum.org emphasizes, the Scrum Master doesn't need to be present during Daily Scrum, and their role is to ensure the meeting happens, but developers are responsible for conducting the meeting. Mindlessly executing daily questions without proper context analysis can lead to situations where the Scrum Master becomes a team manager instead of a self-organization facilitator.

A real Scrum Master analyzes much more data than what's collected by automation - they observe team dynamics, understand business context, identify deeper root causes of problems, and support the team in developing self-organization skills. AI can be a valuable support tool, but it cannot replace the human intuition, empathy, and experience essential in this role.

The automation should be treated as a tool supporting the Teams's work, providing additional insights and helping identify areas requiring attention, but always under the supervision and interpretation of an experienced Scrum practitioner.

AI-Powered Scrum Master Assistant with OpenAI, Slack, and Asana Integration

This n8n workflow automates the process of creating Asana tasks and notifying a Slack channel based on user input, leveraging the power of OpenAI's AI Agent for intelligent task generation. It acts as an AI-powered scrum master assistant, streamlining task creation and communication.

What it does

This workflow simplifies and automates the following steps:

  1. Manual Trigger: The workflow is initiated manually, allowing for on-demand task creation.
  2. AI Agent (OpenAI Chat Model): An AI Agent, powered by an OpenAI Chat Model, processes an input prompt. This agent is designed to understand the request and generate relevant information for an Asana task.
  3. Edit Fields (Set): The output from the AI Agent is then transformed and set into a structured format suitable for Asana. This likely involves extracting task name, description, and potentially other details.
  4. Loop Over Items (Split in Batches): If the AI Agent generates multiple tasks or items, this node processes them one by one.
  5. Asana Task Creation: For each processed item, a new task is created in Asana with the details generated by the AI Agent.
  6. Merge: The workflow merges the output from the Asana task creation, ensuring all data is available for the next step.
  7. HTML Formatting: The Asana task details are formatted into an HTML message, likely for a richer display in Slack.
  8. HTTP Request: An HTTP request is made, possibly to a custom webhook or API endpoint, to further process or enrich the data before posting to Slack.
  9. Slack Notification: Finally, a message containing the newly created Asana task details is posted to a designated Slack channel, informing the team.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running instance of n8n.
  • OpenAI API Key: For the OpenAI Chat Model.
  • Asana Account: With appropriate API access and credentials configured in n8n.
  • Slack Account: With a Slack App and webhook configured for posting messages, or a Slack API token for the Slack node.
  • HTTP Request Endpoint (Optional): If the HTTP Request node is configured to send data to a custom service, that service needs to be set up and accessible.

Setup/Usage

  1. Import the Workflow: Download the JSON provided and import it into your n8n instance.
  2. Configure Credentials:
    • OpenAI: Set up your OpenAI API Key credential in n8n.
    • Asana: Configure your Asana API credential in n8n.
    • Slack: Set up your Slack API credential or webhook URL in n8n.
  3. Customize Nodes:
    • AI Agent: Review and adjust the prompt for the OpenAI Chat Model to best suit your task generation needs.
    • Edit Fields (Set): Ensure the field mapping correctly extracts and transforms data from the AI Agent's output for Asana.
    • Asana: Configure the Asana node to create tasks in the desired workspace, project, and assignees.
    • HTML: Adjust the HTML template for the Slack message if you require a different format.
    • HTTP Request (Optional): If used, configure the URL and payload for your custom endpoint.
    • Slack: Specify the Slack channel where notifications should be posted.
  4. Activate the Workflow: Once configured, activate the workflow. You can then trigger it manually using the "Manual Trigger" node.

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