That’s a wrap! Hundreds of leaders, innovators, and creators joined us in Brooklyn — with tens of thousands more online — for our biggest Canvas yet, where they discovered new ways for AI and teams to work together.
Let’s take a closer look at ten products we highlighted at the event that deliver on that promise:
1. The AI Innovation Workspace: Bring AI and teams together on the canvas
AI adoption is exploding, with companies making massive investments in scaled platforms and custom models. But many have yet to see the impact of their AI implementations. Why?
Most AI tools are built to improve individual productivity or automate tasks during the later stages of the innovation loop. In fact, 76% of leaders agree that most AI tools focus on individual rather than team productivity.¹ People are able to make quick progress on their solo projects, but work slows down when they sync back with their teams.
That’s what’s missing from the AI revolution: teams. Teams have always been the driving force behind innovation, which is why the real opportunity isn’t AI for individual productivity; it’s AI that meets teams where the work is happening.
That’s why we built the AI Innovation Workspace, to:
- Bring AI and teams together on a collaborative canvas
- Empower teams to make smart decisions and move faster
- Take entire organizations on a journey of transformation
It starts with an AI-first canvas that offers new capabilities to keep teams in the flow of work; help organizations evolve their ways of working; and, ultimately, drive business transformation.
And, of course, it still includes the flexible formats, multiplayer features, and enterprise safeguards that have been powering people from brainstorm to breakthrough for over a decade.
So, let’s answer the obvious question: What are these new AI capabilities and how do they work?
2. Flows: Keep teams in the flow of work with AI automation
We’ve long believed that it should be easier for teams to build the next big thing, faster. One of the most exciting ways we’re enabling this on Miro is with Flows.
You’ve seen AI automation before — but not like this. Flows are visual, multi-step AI workflows that connect the work already living on your canvas. Teams can work together with multiple cursors and simultaneous edits, so that anyone can tweak steps, swap models, or refine prompts to continuously improve the Flow.
Start with templates that convert customer interviews into sprint plans or team brainstorms into scenario planning, choosing the best AI model for each step to get the right output in the right format every time. Then, convert your perfected processes into reusable templates to share across your organization. (Keep an eye out for AI-powered Miro templates, coming soon!)
The result? AI that moves at the speed of your team’s thinking, allowing them to get projects over the finish line faster and giving them time back to focus on the creative work they crave.
3. Sidekicks: Co-create with AI collaborators
Flows aren’t the only way teams can move faster with AI. Sidekicks are conversational agents that understand your canvas context and “yes, and…” your ideas to keep momentum going.
Sidekicks understand all the ideas, research, and plans on your board, using the canvas as the prompt and their expertise on a specific job, task, or process to power your projects further, faster. They structure thinking, give feedback on solutions, and even create things like prototypes, summaries, and technical diagrams so your teams stay focused on the big picture.
Anyone can get started quickly with out-of-the-box Sidekicks for tasks like project kickoffs, competitive analysis, or campaign planning. But if you need a little more nuance, you can build your own Sidekick in minutes by sharing brand guidelines or strategic frameworks; you can even connect your own enterprise system.
4. Your AI & Knowledge: Integrate with your existing AI models
To realize the business impact of AI, organizations must evolve their ways of working. This includes transitioning from siloed AI tools to tools that work with your existing models and knowledge.
That’s why Miro’s collaborative integration layer supports the major AI platforms and models. Organizations can build off of their platform of choice — from OpenAI to Anthropic, Google, and Azure.
What’s more, you can access your own company knowledge through deep integrations with the likes of Amazon Q, Glean, and Gemini Enterprise.
You can also bring your own AI key — so your trained systems are closer to where the work is happening.
5. Model Context Protocol (MCP): Connect the canvas to coding tools
A simple canvas-to-code pipeline is a must-have for maximizing the value of your AI investments so all those PRDs, prototypes, and technical designs become real products faster.
With Model Context Protocol (MCP), other systems can access the power of the AI canvas and the deep context it brings. This means production-ready code delivered from Miro to platforms like Lovable, Cursor, AWS Kuro, Google Cloud Code, OpenAI Codex, and more.
Even better: Context from these systems can flow back into Miro so everything stays in sync even if specs change.
6. Miro for Product Acceleration: Build the right product faster
The AI Innovation Workspace is designed to empower everyone across the organization to flow from early ideas to final outcomes, faster.
But one team in particular has had a front-row seat to AI transformation: product. AI is blurring the lines between product functions — with PMs designing, designers coding, and engineers doing … well, everything — and encouraging teams to reimagine their agile processes and product delivery cycles.
Amid these shifts, we’ve revisited how product teams operate so they can really take advantage of the new technology at their disposal. Our answer? Miro for Product Acceleration, a comprehensive solution for product teams, helping them make smarter decisions about what to build and do it faster.
Its 10 integrated, AI-first products are purpose-built to solve three critical challenges that product teams often face:
- Connecting strategy with execution
- Building the right thing
- Getting the most from AI code generation investments
Let’s dive into a few products in more detail to understand how they help address these obstacles:
7. Portfolios: Connect strategy to execution
At one point or another, all product teams find themselves prioritizing work that’s disconnected from their company strategy and vision. This is frustrating for leaders, who spend weeks obsessing over every detail during the planning cycle, but also for their teams, who want to spend their time on work that contributes meaningfully to the business.
Miro Portfolios helps ensure the products that teams ship are in line with their organization’s objectives by bringing company strategy and portfolio data into the same space where leaders and teams make decisions. It gives leaders the visibility they need to spot issues, plug gaps, and course-correct to keep projects on track, while enabling teams to see exactly how their work ladders up to company OKRs.
8. Insights: Turn customer feedback into a product that delights
It’s not the customer’s job to know what they want. But it is the product manager’s job. And the answer is out there somewhere, buried in support tickets, user interviews, surveys, and review sites.
Miro Insights turns scattered customer feedback into clear signals right where the work happens so product teams can make the right decisions. Rather than relying on gut feeling or the loudest voice in the room, product teams get data-backed intelligence that reveals what customers actually need, and, in turn, run less risk of building features that miss the mark.
9. Prototypes: Explore more and experiment faster
Once you’ve consulted customer insights, the next step in building a product people want is bringing those insights and ideas to life. And the best way to know if you’re building the right thing is to see it and test it before writing a single line of code.
With Miro Prototypes, anyone on the team can turn the sticky notes, diagrams, or doodles from their brainstorm into a clickable prototype in minutes using AI. It’s easily editable, too, meaning teams can explore multiple directions and variations, validate concepts quickly, and converge on the best idea before moving to design or development, without worrying about wasted time or sunk costs.
10. Specs: Keep code in sync with strategy
Your teams have lasered in on the right insight. They’ve got a prototype that people love. All they have to do now is build it. But tracking down requirements from Jira tickets, Slack threads, and Figma files is a time-consuming and imperfect process.
Miro Specs packages the context from your PRDs, prototypes, technical diagrams, and other visual, collaborative work into comprehensive, well-defined technical specifications. It then delivers these specifications straight to AI coding tools, like GitHub Copilot, Cursor, Windsurf, and Claude Code through MCP.
By capturing comprehensive context from discovery and delivering it directly into development, Specs ensures that AI coding tools have everything they need to generate high-quality code that reflects customer needs, strategic intent, and sound technical architecture. This is how teams finally get the ROI they expect from AI coding tools, in the form of faster time to market and value.
Thanks to our community and customers!
There were so many highlights at Canvas 25: A new AI-first canvas. The future of team and AI collaboration. AI that keeps teams in the flow of work.
But the best bit? Celebrating alongside a passionate community that’s now more than 100 million users and 250,000 companies strong.
Next, we’re taking the celebration on the road — see if Canvas is coming to a city near you!
In the meantime, we can’t wait to see how your teams get great done on Miro’s AI Innovation Workspace.
¹ Forrester’s Q3 2025 AI Workflows For Team Innovation Survey [E-65113]
