Stop drowning in workflows: How AI can help product managers ship faster

Summary

In this guide, you will learn:

• How AI transforms product management through accelerated development cycles and better decision-making

• The four-phase AI-powered product framework: Strategy & Discovery, Planning & Prioritization, Design & Development, and Launch & Iteration

• Key AI technologies: Natural Language Processing, machine learning for prioritization, and generative AI for content creation

• How to integrate AI into existing workflows using Miro's collaborative templates and features

• Best practices for responsible AI adoption and real-world results like PepsiCo's 3.6x faster time-to-market

Product development is moving faster than ever before, and the rise of AI has kicked things into hyperdrive. As a product manager, you feel this pressure to accelerate every single day. The challenge isn't just about shipping products anymore; it's about navigating uncertainty with confidence and steering large teams toward a single, strategic vision.

Are you finding it exhausting to track multiple complex workstreams and mediate conflicts between teams that don't even report to you? It’s frustrating when siloed ways of working lead to endless meetings with no clear outcomes, stretching feedback cycles, and delaying launches. This kind of misalignment doesn't just slow you down; it can cause you to lose market share to competitors who are moving faster.

This pressure is felt across the board. According to Miro's research on how knowledge workers really feel about AI, while two-thirds of employees are positive about its potential benefits, almost half (46%) feel their companies are not providing concrete AI initiatives or tools to help them. This gap between employee optimism and employer action is where teams start to fall behind.

We get it, and at Miro, we believe there’s a better way.

A better way of working is possible

Imagine trading chaotic days for streamlined collaboration, where your team is no longer bogged down in process, but focused on delivering customer value. This ideal state—where insights are clear and decisions are data-driven—isn’t a far-off dream. It's a tangible business imperative.

In a report on how businesses are transforming with AI, Microsoft found that for every $1 organizations invest in generative AI, they see an average return of $3.70. This proves that the right AI strategy delivers significant value. You can achieve it by strategically adding AI into your daily workflow. Let's see how this is possible.

Use AI across the entire product lifecycle

Integrating AI isn't about replacing the core skills of a product manager. Instead, think of AI as a powerful assistant that amplifies your ability to strategize, empathize, and communicate. Miro embeds AI directly into your workflows, so you can focus on what matters most without switching tools.

Phase 1: Strategy and discovery - uncover opportunities with AI

A winning product starts with a deep understanding of your customers and the market. But how do you find those golden nuggets of insight in a sea of data? AI can rapidly analyze market trends, competitor moves, and customer feedback to help you spot new opportunities and shape a data-driven product roadmap. Natural Language Processing (NLP) can sift through surveys, reviews, and support tickets to uncover customer pain points and desires at scale.

Miro in action

• Visualize the entire customer experience with our Customer Journey Map Template. Gather all your customer feedback as sticky notes on the board. Then, use Miro AI's clustering feature to instantly group the feedback by keywords or sentiment. This reveals patterns in seconds, helping you pinpoint the most frustrating or delightful moments in the customer journey.

• Create detailed user profiles with our Personas Template. Instead of spending hours reading interview transcripts, paste them onto the board and use Miro AI to summarize the key takeaways. This helps you quickly enrich your personas with direct quotes and evidence-based pain points.

• Truly understand your users' needs with the Empathy Map Template. Once your map is populated with insights, select a key area (like "Pains") and use Create with AI to generate a set of "How Might We" questions. This jumpstarts your brainstorming and ensures you're focused on solving the right problems.

Phase 2: Planning and prioritization - build the right thing

Once you have your strategy, the next challenge is deciding what to build first. It's easy for teams to lose sight of the big picture and get stuck shipping features for features' sake. AI can bring clarity to this process. Intelligent tools can help you prioritize features based on their predicted impact and alignment with your strategic goals. Generative AI can even give you a head start by drafting initial user stories, acceptance criteria, and Product Requirements Documents (PRDs).

With Miro AI, you can use the canvas as your prompt to generate strategy docs and goal suggestions, ensuring your team stays aligned.

Miro in action

• Develop a clear and compelling product strategy with one of our Product Roadmap Templates. Select a group of insights from your discovery phase and use Create with AI to generate a draft of strategic goals or OKRs. This provides a solid starting point for your team to refine and align on. Try also the Tables format to start drafting your Roadmap with the help of AI.

• Organize and prioritize your backlog visually using the User Story Map Template and our flexible Prioritization Template. After brainstorming ideas on digital sticky notes, select a group and let Miro AI instantly convert them into well-formatted user stories. Then, use AI text editing to refine the language for clarity or a specific tone.

• Define the essential features for your initial launch with the Minimum Viable Product (MVP) Template. Use AI Sidekicks to get an ‘expert’ opinion. Ask the "Product Leader" sidekick to review your proposed MVP and provide feedback on its viability or suggest potential risks, acting as an instant sounding board for your ideas.

Phase 3: Design and development - accelerate your execution

Getting from idea to execution requires seamless collaboration between design, engineering, and product teams. AI can accelerate this phase by automating repetitive tasks and optimizing workflows. You can turn rough thoughts into presentable outcomes in just moments, keeping the momentum going.

Miro in action

• Draft and align on comprehensive requirements with our dynamic Product Requirements Document (PRD) Template. Pull your user stories and discovery insights from the board, then use Create with AI to generate the initial draft of your PRD in moments. From there, leverage AI text editing to polish the content for clarity and consistency, ensuring everyone from engineering to marketing is working from the same single source of truth.

• Iterate on early design concepts quickly with our Low-Fidelity Wireframes Template. This is where AI-powered Prototyping shines. Simply type a description of a screen, like "a user login page with fields for email and password," and Miro AI will generate an editable prototype for you. You can even upload a screenshot of an existing interface and have AI convert it into an interactive prototype to outline solutions. Watch this 2-minute walkthrough with Rosalba Giuffrida, Group Product Manager at Miro, to see how she turns static screenshots into testable, interactive prototypes using AI.

• Break down large-scale projects into manageable pieces with the Work Breakdown Structure Template. After outlining the major project phases, use Create with AI to brainstorm all the potential tasks and sub-tasks required for each phase, ensuring nothing gets missed.

• Visualize and streamline your development process with the Value Stream Map Template. As you map out your process, use an AI Sidekick like the "Agile Coach" to ask for suggestions on how to reduce waste or improve flow between stages, getting contextual advice directly on your board.

Phase 4: Launch and iteration - drive growth with AI

Your work isn't done when the product ships. The launch is just the beginning of a continuous cycle of learning and improvement. AI can help you personalize marketing messages for a smarter launch and analyze post-launch data to understand feature adoption, identify friction points, and guide your next steps.

Miro in action

• Run effective post-launch reviews with our Retrospective Template. Once the team has added their feedback on sticky notes, use Miro AI-powered clustering to instantly group them into themes like "What went well," "What didn't," and "Key learnings." This surfaces insights immediately and makes your retrospectives more efficient and action-oriented.

• For Product Marketing Managers, use Create with AI to accelerate your go-to-market plan. You can use the Go-To Market Presentation template and, based on your product's value proposition on the board, ask AI to draft different marketing messages tailored for a blog post, social media, and customer emails. Then, use

  AI text editing to adjust the tone or translate the content for different regions, all within one workspace.

• Decide on the best course of action for future iterations using the Start, Stop, Continue Template. After analyzing post-launch data and gathering customer feedback, use Miro AI to summarize the key findings. Then, present these summaries to your team to facilitate a data-driven discussion on what to prioritize next.

Getting started with AI in your product workflow

Ready to dive in? Here are a few practical tips to help you get started without feeling overwhelmed.

• Start small: You don't need to transform your entire workflow overnight. Pick one or two areas where you feel the most friction and experiment with an AI tool to solve that specific problem.

• Focus on the "why": Be clear about what you want to achieve. Are you trying to synthesize customer feedback faster? Or perhaps you want to reduce the time spent on planning meetings? Having a clear goal will help you choose the right approach. As the team at WebMD discovered, improving discovery practices at scale led to 60% more product improvements per quarter.

• Embrace responsibility: As you integrate AI, always be mindful of ethical considerations like data privacy and potential bias in algorithms.

How PepsiCo ships products 3.6x faster with Miro

For a global company like PepsiCo, uniting teams across different continents to plan and deliver a new product is a massive challenge. The complexity can lead to delays, miscommunication, and a slow time-to-market, making it difficult to innovate at the speed the market demands.

Imagine if you could unite your global teams in a single, visual workspace, creating a blueprint for complex innovation that everyone can follow. This is exactly what PepsiCo achieved by using Miro. They brought their cross-functional teams together to plan and deliver a new product, which resulted in bringing it to market 3.6x faster.

By centralizing their workflow on Miro, they didn't just speed up their process; they inspired a completely new way of working. The results speak for themselves: 80% of their users agreed that Miro helped improve their work productivity. As Koen Burghouts, VP of Innovation & Emerging Brands at PepsiCo, put it, "Miro inspired a different way of working on our team. We now take this as our best practice and our blueprint for complex innovation". This story shows that with the right collaborative platform, even the most complex projects can be streamlined for incredible results.

The future of AI in product management is collaborative

AI is not a silver bullet, but it is a powerful catalyst for change. The future of product management will be defined by a partnership between human creativity and artificial intelligence. Your strategic thinking, empathy, and communication skills will become even more critical, and AI will be the tool that amplifies your impact.

At Miro, we're committed to building an innovation workspace that supports this future. We see AI as a way to handle the routine tasks so that you and your team can focus on what you do best: solving complex problems and creating products that customers love. It's about AI help, not hype.

Ready to see how a more visual and collaborative approach can transform your product development process? Start building on Miro with a free account today and explore how our AI-powered features can help you and your team achieve more.

FAQs

What are the main risks or challenges when implementing AI in product management?

Key considerations include data privacy and security, potential algorithmic bias in decision-making, over-reliance on AI without human judgment, and the learning curve for teams adopting new tools. It's important to start small, maintain human oversight of AI recommendations, ensure diverse data sources, and establish clear guidelines for responsible AI use in your organization.

What's the ROI of implementing AI in product management workflows?

Microsoft-sponsored IDC research indicates that organizations see an average return of $3.70 for every $1 invested in generative AI. Beyond financial returns, teams experience faster decision-making, improved customer insights, reduced manual work, and enhanced cross-team collaboration. WebMD, for example, saw 60% more product improvements per quarter after implementing continuous discovery practices with Miro.

How do I convince stakeholders and leadership to invest in AI for product management?

Focus on measurable business outcomes rather than AI features. Present specific use cases relevant to your organization's pain points, such as reducing customer feedback analysis time from days to hours, or increasing feature prioritization accuracy. Start with pilot projects that can demonstrate quick wins and measurable ROI. Use the Microsoft IDC data showing $3.70 return per dollar invested as supporting evidence, and consider conducting a small proof-of-concept to show tangible results before requesting larger investments.

What are the most common mistakes teams make when implementing AI in product workflows?

Common pitfalls include: trying to implement too many AI tools at once instead of focusing on specific pain points, over-relying on AI without maintaining human oversight and critical thinking, not training team members on how to effectively use AI tools, expecting AI to replace strategic thinking rather than enhance it, and failing to establish clear processes for validating AI-generated insights. Start small, measure results, and gradually expand AI usage as your team builds confidence and expertise.

Author: Miro Team

Last update: August 8, 2025