Miro adds workflow AI workspace and product acceleration tools
Miro has launched two major additions: AI Innovation Workspace and Miro for Product Acceleration. The goal is straightforward-help marketing, design, and product teams work faster with more clarity and fewer handoffs.
The company says these releases will "reimagine the product development lifecycle" by connecting strategy to execution and improving quality. As Andrey Khusid, Miro's CEO, put it, AI's biggest upside shows up in team outcomes, not solo productivity.
What's in the AI Innovation Workspace
This suite pushes Miro from a single canvas tool to a workflows platform. It focuses on automation, agent support, and shared knowledge across teams.
- Flows: Visual AI workflows that automate multi-step processes while keeping visibility and control. Think research → synthesis → prioritization → handoff.
- Sidekicks: Conversational AI agents specialized for tasks or processes (e.g., PRD drafting, usability synthesis, backlog grooming).
- Your AI & Knowledge: A collaborative layer that connects to your existing enterprise AI and knowledge sources so teams work from the same context.
- Model Context Protocol (MCP): Connects Miro to other agentic platforms to expand code creation and automation capabilities. Learn more about MCP here.
What's in Miro for Product Acceleration
This is a set of AI-first products meant to streamline the lifecycle from goal-setting to shipped features. It's built to solve common gaps: aligning objectives to roadmaps, validating what to build, and getting more from AI-assisted code.
- Miro Portfolios: Connect goals to initiatives and delivery plans so stakeholders see progress without another status deck.
- Miro Insights: Turn research, feedback, and usage signals into prioritized opportunities backed by evidence.
- Miro Prototypes: Create and test concepts quickly so teams can validate before engineering commits.
- Miro Specs: Generate and refine specs with AI to reduce gaps between product, design, and engineering.
How product teams can use this now
- Pilot a critical workflow: Map one high-friction process (e.g., idea intake → prioritization → PRD) into Flows. Set a 30-day target for cycle time reduction.
- Assign Sidekicks to real roles: Create agents for research synthesis, PRD drafting, and backlog triage. Define what they own, when they hand off, and your acceptance criteria.
- Centralize context: Connect Your AI & Knowledge to your approved sources so specs, research, and decisions pull from the same truth.
- Instrument outcomes: Track lead time, rework, engineering idle time, and decision latency. Review weekly to tune prompts, flows, and guardrails.
- Set governance early: Decide what can be automated, what needs human review, and where approvals live. Keep audit trails visible in the board.
Where this fits in your stack
Treat Miro as the orchestration layer across discovery, planning, and handoff. Use MCP-enabled connections to extend into agentic and code-related tasks while keeping human checkpoints in place.
If you've invested in AI code generation, use Miro Specs and Flows to tighten the loop between requirements, generated code, and validation. The payoff comes from fewer context switches and clearer traceability from goals to commits.
Scale and adoption
Miro reports more than 100 million users and 1,600 employees across 14 hubs, with teams at Ubisoft, Red Hat, Virgin Media O2, and GitHub already using its tools to speed up workflows. The company is co-headquartered in San Francisco and Amsterdam.
Level up team capability
If you're building an AI-enabled product workflow, upskilling the team is the fastest way to reduce thrash. See role-specific options at Complete AI Training: Courses by Job.
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