Most AI tools solve for individual productivity. You ask ChatGPT a question, get an answer, and bring that answer back to your team. But what happens when five team members each have their own AI-generated insights from separate conversations? You end up with fragmented context, misaligned assumptions, and meetings spent reconciling what AI told each person individually.
Miro calls this the "single player AI experience" problem - where individuals work with AI agents in isolation and then return to teams with different context and conclusions, hampering team alignment.
Their solution Miro offers - put AI where teams already collaborate - on the shared visual canvas.
Miro embeds agentic AI directly into the visual workspace where innovation already happens. The canvas itself becomes the prompt. This multiplayer AI approach means cross-functional teams can work with AI simultaneously on the same canvas, maintaining context and momentum throughout the innovation journey.
What makes this powerful is that Miro AI can generate content from scratch, use existing visuals on the board as context, and output in multiple formats - docs, tables, diagrams, prototypes - all within a collaborative environment where the entire team can see, question, and iterate together.
I work with a large enterprise client on AI strategy and governance. During our workshops, stakeholders from diferent teams each bring different perspectives and priorities. Without shared context, we'd spend hours aligning on definitions alone.
We start our sessions by capturing concerns, requirements, and use cases on sticky notes across the board. Then I use Miro AI to help us gain clarity. I'll select a cluster of sticky notes about data privacy concerns and ask Miro AI to summarize the key themes and identify potential conflicts. The AI reads the visual context - not just text, but relationships between ideas, how they're grouped, what's been prioritized.
When we struggle to articulate a complex governance principle, I'll select our rough notes and ask Miro AI to rephrase them into clear policy language. The team sees the output immediately, reacts to it together, and refines it collaboratively. We're not taking AI-generated text offline to clean up - we're iterating in real-time with everyone's input.
This way, the canvas itself becomes the prompt - we don't waste time explaining our thinking, but instead build on the work that's already there. By the end of a three-hour session, we've moved from scattered concerns to a structured AI governance framework with clear principles, decision criteria, and implementation roadmap - all documented on the same board where we brainstormed.
This matters because while many organizations are seeing productivity and efficiency gains by adopting AI tools for individual employees, they often overlook the greater value that comes when AI amplifies how teams collaborate and solve problems together.
Miro AI includes two core capabilities that enable this team intelligence:
AI Sidekicks - AI agents that act as conversational teammates and thought partners, observing context, noticing patterns, challenging assumptions, and suggesting improvements to actively help teams work through problems. You can use pre-built specialists or create custom Sidekicks with your company's knowledge and ways of working.
AI Flows - Visual AI workflows that transform canvas content through connected, multi-step processes, turning ideas into comprehensive deliverables like prototypes, documents, or diagrams.
Start with one use case that recurs weekly and has clear inputs and outputs. Pilot with a small group, measure time saved and quality.
AI's biggest opportunity isn't replacing individual work - it's amplifying how teams collaborate. When AI sits where teams already work, with shared context visible to everyone, it transforms from a productivity tool into team intelligence.
The AI Innovation Workspace is currently in beta and available across all Miro plans. Watch the video below to see these capabilities in action.