Miro now integrates AI agents onto your team's whiteboard.

      There is a certain type of frustration that arises from providing an AI tool with the same context your team spent three days creating on a whiteboard. You transfer the sticky notes into a prompt, paste the description of the diagram, and attempt to clarify the relationships between ideas that were evident when arranged spatially on a canvas, only to see the subtleties diminish into a simplistic paragraph. The visual thought process that made the brainstorming session effective disappears the moment you step away from the board.

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      Miro, a visual collaboration platform utilized by over 100 million individuals across 250,000 organizations, has been rapidly developing a solution to this issue. In January 2026, it introduced AI Workflows: a system of AI agents that operate directly on the canvas where teams already engage, utilizing everything on the board as context. There’s no copying, no starting prompts from scratch, and no need to switch between tools. The AI perceives what your team sees. In March 2026, Miro also acquired Reforge, a company specializing in product strategy and growth education, indicating its intention to combine AI collaboration tools with the frameworks teams need for effective use.

      Why many AI tools do not succeed with teams

      The divide between individual AI efficiency and team AI efficiency has emerged as a significant tension in enterprise software. According to Miro’s research, 75% of global business leaders believe most AI tools overly concentrate on individual tasks, while 82% desire solutions that enhance team productivity. This aligns with the daily experiences of most knowledge workers: an AI assistant that helps draft a document is useful, yet it cannot substitute for the collaborative process of aligning a cross-functional team on what the document should convey from the outset.

      Many AI tools function in isolation. You prompt them individually, receive outputs in isolation, and then spend extra time aligning those outputs with your team. Traditionally, the canvas—the area where ideas visually and collaboratively develop—has been devoid of AI. Miro’s strategy is that integrating AI directly into that shared environment entirely transforms the dynamic.

      Sidekicks and Flows: AI operating on the board

      The two primary components of Miro’s AI Workflows are Sidekicks and Flows.

      Sidekicks are conversational AI agents that reside on the canvas. They do not need carefully crafted prompts since they inherently comprehend the multimodal context surrounding them: sticky notes, diagrams, documents, images, tables, and the spatial relationships of all these elements. Think of them as collaborators who arrive already having absorbed all the information presented in the room. You can tailor Sidekicks with particular skills and knowledge bases, allowing a product team’s Sidekick to understand its domain differently from a marketing team’s.

      Flows are multi-step visual workflows that link AI actions while ensuring human involvement at each stage. For instance, a product team might create a Flow that takes a set of user research notes, organizes them by theme, generates insight summaries, and produces a draft product brief, all within the same canvas where the original research is located. The team can intervene, redirect, or refine at any step. Early users report that they have reduced their innovation cycles from weeks to hours, with total delivery costs decreasing by more than 50%.

      The synergy between Sidekicks and Flows is more significant than either feature on its own. Sidekicks manage the conversational and contextual work, while Flows handle the repeatable, multi-step processes. Together, they transform a collaborative whiteboard into something akin to an AI-augmented operating system for team thinking.

      What teams are actually creating with it

      The fastest-growing use cases typically follow a trend: chaotic collaborative input being transformed into organized, shareable output.

      Product teams utilize Flows to turn brainstorming sessions into prioritized roadmaps. Design teams link Miro’s canvas with Figma via the new prototype export feature, allowing architecture diagrams and wireframes to directly translate into design files. Engineering teams are leveraging Miro’s MCP server (currently in beta, developed in collaboration with Anthropic, AWS, GitHub, Google, and Windsurf) to integrate boards with AI coding tools like Cursor, Claude Code, and GitHub Copilot. Consequently, system architecture diagrams on the canvas become the foundation for AI-generated code that accurately reflects the intended design, as the coding agent can visualize the board.

      Workshop facilitators are drawn to Miro Engage, a beta tool aimed at engaging passive attendees as active participants during meetings, all-hands events, and training sessions. Furthermore, the new AI Slides feature allows anyone to generate a presentation deck from board content, meaning the outcomes of a working session can become a stakeholder presentation without the usual time-consuming reformatting.

      These are not hypothetical scenarios; they represent how teams at organizations such as PepsiCo, ASOS, and Deloitte are already employing the platform.

      The pricing considerations

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