Article

3 Ways AI Supports Product Release Planning

August 21, 2025

|

Emily May

Building product launch plans is more challenging now than ever. With tighter timelines, shifting priorities, and more dependencies, product teams are struggling to keep up. Due to these constraints, without the assistance of technology, product release planning can fall behind.

AI-powered tools support product teams in modernizing their approach to product planning. When used effectively, artificial intelligence has the power to streamline, optimize, and accelerate the product release planning process.

In this article, you’ll learn about three ways to leverage AI for supporting product release planning for improved customer and team outcomes. 

What Is Product Release Planning?

Product release planning is the process of deciding and defining what will be delivered, when it will be released, and how. The plan connects product strategy with execution, ensuring that features are prioritized, timelines are realistic, and teams are aligned.

A product release plan includes:

  • Product roadmap
  • Prioritized backlog 
  • Timeline of value delivery
  • Stakeholder communication strategy

When well executed, a product release plan provides teams with confidence, reduces risk, and improves the customer experience.

3 Ways AI Supports Product Release Planning

This section explores how AI can add clarity and efficiency to the product planning process for improved internal and external results.

1. Roadmap Planning

A person evaluates a branching roadmap with milestones and connected tasks to guide planning decisions.

Every product team can benefit from added support when planning their product roadmap. AI can offer suggestions that highlight the most valuable features to include in a release. It can analyze historical performance, market trends, customer feedback, strategic goals, and more to ensure recommendations are as accurate as possible.

The result? Your team can make fast, data-driven decisions related to the product roadmap that are likely to have positive outcomes.

Benefits of AI for Roadmap Planning:

  • Alignment with strategic goals
  • Predictable release outcomes
  • Fast & confident decision-making

Example: A competitor releases a new feature that quickly gains traction on social media. Your product team considers that your customers may expect the same feature. 

Instead of relying on guesswork, AI scans reviews, forums, social media, and support tickets to collect more information on customer opinions. AI identifies a rising trend in customer comments that express a desire for this feature. 

With this in mind, your team updates the roadmap to address the changing needs of your customers.

Tool Option: Aha! Roadmaps

2. Backlog Prioritization

A person organizes tasks from a backlog into a prioritized board using a visual sorting system.

Backlogs can grow quickly. That’s why backlog prioritization can be a timely task for product teams. AI can support backlog refinement by ranking work according to impact, effort, and urgency.

With predictive analytics, AI can help product managers see what will matter most to their customers. With the right context, your team can spot high-impact work that might have been overlooked.

Benefits of AI for Backlog Prioritizing:

  • Reduced decision fatigue
  • Improved team focus
  • Higher customer satisfaction

Example: A development team’s list of user testing feedback has steadily piled up for months. With limited time and resources, they’re unsure which requests will deliver the most value with the least effort as they prepare to launch the product to the public. 

To narrow down options, the team uses a generative AI model to review and analyze the user feedback. The model quickly sorts the requests by estimated effort and urgency. 

After reviewing the top recommendations, the team agrees on one high-impact item to focus on for their next sprint and what they might want to change in the product roadmap. This strategy enables them to make fast decisions that balance customer value delivery and team bandwidth. 

Tool Option: ClickUp Brain

3. Capacity and Timeline Forecasting

A person stands next to a large calendar, reviewing scheduled tasks to forecast capacity and timelines.

You can have a winning product plan, yet if your team is overextended and timelines are unrealistic, it can still fail. Another way to use AI for product planning is to estimate team capacity and timelines. 

By evaluating estimated velocity, available bandwidth, the product roadmap, and potential risks, AI can help forecast reasonable timelines and capacity needs. Moreover, before making changes to the product roadmap, AI can reveal the impact of those new shifts.

Benefits of AI for Capacity and Timeline Forecasting:

  • More accurate schedules
  • Fewer last-minute surprises
  • Increased stakeholder confidence & well-being

Example: As the product launch date approaches, the marketing team suggests adding a new product feature to create more buzz around the launch. Before moving forward, product leadership weighs the pros and cons of this idea.

Part of their decision-making process includes running the scenario through an AI tool. They learned that the new feature could delay the time-to-market by four weeks or more. The insights also revealed a higher increase in workload than anticipated.

The product team decides not to prioritize the new feature, but to add it to the backlog instead. As a result, the product team is less likely to burn out and stay on track with the promised launch date.

Tool Option: Forecast

Conclusion

Product release planning is time-consuming, and many decisions involve an element of risk. AI tools can help product teams inject foresight into each stage of the planning process–from developing product roadmaps to forecasting team capacity. 

The payoff of enhancing the planning process with AI is tenfold: helping teams adapt quickly, deliver value, and maintain a competitive edge in the marketplace. 

If you want to implement AI into your team’s product release planning, but don’t know where to start, we have a micro-credential course just for you. AI for Product Planning will teach you how to leverage AI for:

  • Developing product roadmaps
  • Prioritizing backlogs
  • Designing release plans with a focus on outcomes

Best of all? You’ll learn all of this in four hours or less, and be ready to apply it in your day-to-day work. 

Learn more about AI for Product Planning today.

Elevate Your Learning

Join our community of agile learners and get the latest news and resources delivered straight to your inbox.

* indicates required
TAGGED AS:
Value Delivery, Foundations of AI, Delivery Management, Delivery at Scale, Expert in Delivery Management, Product Ownership, Agile Product Ownership, Enterprise Product Ownership, Expert in Product Ownership, Agile Testing, Agile Testing, Agile Test Automation, Expert in Agile Testing, Product Strategy, Product Management

About the author

Emily May | ICAgile, Marketing Specialist
Emily May is a Marketing Specialist at ICAgile, where she helps educate learners on their agile journey through content. With an eclectic background in communications supporting small business marketing efforts, she hopes to inspire readers to initiate more empathy, productivity, and creativity in the workplace for improved internal and external outcomes.

Suggested Resources