5 Tasks Product Owners Should Do With AI, and 3 Responsibilities They Better Take Care of Themselves

Overworked Product Owners? No way, they all use AI now and live the easy peasy, lemon squeezy life.

As a Product Owner, you know the job is no walk in the park. Balancing the needs of customers and stakeholders, making tough product decisions, answering every question developers could possibly need to clarify before starting a task, and because there's currently no Scrum Master available – well, you've taken on that role too. Just for now, of course.

Into that reality comes AI, promising to change everything about the way we work. AI is stepping in to make your life a whole lot easier – as the competent and always friendly assistant you were never given before. Well, we don't know what your job looks like. But we guess that's a reality most people are still dreaming about.

Here's a shocking truth you might need to hear: AI is not the solution for everything.

An AI-empowered PO isn't someone doing everything with AI – it's someone who knows when to lean on AI to boost productivity – and when their own expertise is needed.

And there's a second truth we believe in: AI won't replace Product Owners. There is way too much work for that. But let's dream a little: What if you could use AI for the repetitive, maybe even tedious tasks, which gives you more time to focus on the strategic parts of your job: The parts you love, and that no AI can do better than you. The things that set your product apart from its competitors.

In this blog article, we'll break down 5 tasks where AI can be your best friend, saving you time and helping you stay ahead. Then we will show you 3 scenarios that no AI could have solved and that we think require your personal touch. Let's dive in!

5 Tasks You Should Use AI For. Give it a try!

AI is great for tasks that involve structure, analysis, and repetitive work. It thrives on patterns and rules, making it a perfect assistant for the following five areas:

Task 1: Writing Product Documentation

Product documentation can really eat up your time. Whether it's for new features, stakeholder updates, or release notes, you need to be clear and accurate. But let's face it: It's busy work. Good product documentation is necessary, but this won't make or break your product. That's why you should not waste too much of your (always scarce) time on it. Instead of spending hours on each word, let AI do the bulk of the work. It's fast, efficient, and keeps things consistent.

To draft some release notes, you could use a prompt like this:

Prompt to Draft Release NotesCopy
You are an experienced Product Owner responsible for writing clear and easy to understand release notes. Create release notes for our product [Product Name] v [version number]. Use a simple, non-technical language and focus on user outcomes. In the release notes:

1. Categorize the following updates into “New Features”, “Improvements”, “Bug Fixes”, and “Known Issues”:
"""
[List of Updates, e.g. closed Jira issues]
"""

2. Describe the new features, showing which problems it solves for the user.

3. Explain the improvements made to existing features, explaining how the improvements lead to a better user experience.

The output should aim for 150-300 words. Include the release title, a 1-2 sentences high-level overview, the given categories, and a short Call-to-Action.

Of course, AI won't write the perfect documentation on its own, but it can significantly speed up the drafting process, leaving you with more time to add your unique knowledge and personal style afterwards.

Task 2: Analyzing Customer Feedback

Customer feedback is a goldmine of insight. But sifting through it manually can take a long time- Categorizing and analyzing it can take an eternity. You need to identify patterns, prioritize, and ensure that the feedback is actionable. Because this seems like an impossible task, and because POs feel that spending a few hours on it won't make a difference when it would actually require weeks, it is often neglected. AI can help you quickly analyze large volumes of feedback, give you an overview and extract the key insights so you can focus on responding to customer needs instead of getting lost in the data.

Use a prompt like this to get started:

Prompt to Analyze Customer FeedbackCopy
You are an experienced Product Owner tasked with analyzing customer feedback. Analyze the following feedback for our product [Product Name].

1. Categorize the feedback into the following key themes: usability, feature requests, performance and customer support. For each category, provide a brief summary of the main themes and list the most common feedback points.

2. Identify recurring issues within each category. Sort the feedback based on frequency, from “mentioned often” to “mentioned rarely”. Include the source of the feedback, such as customers, user reviews, support tickets etc.

3. Evaluate trends and highlight feedback that could impact the next product iteration. Suggest actionable ways to improve customer retention and engagement.

Provide a detailed analysis in sections for each category. Use bullet points or tables to organize recurring issues and their frequency. Explain the rationale for your recommendations clearly.

This is the customer feedback: 
"""
[Customer Feedback]
"""

Task 3: Writing User Stories

Writing user stories is essential, but it doesn't have to be a time-consuming or complicated process. AI can help you draft clear, concise, and structured user stories based on the requirements you already have. By letting AI handle the writing, you can ensure consistency and clarity without spending too much time on each story.

Prompt to Write User StoriesCopy
You are an expert requirements engineer. Your goal is to help Product Owners write clear, actionable user stories. Follow these steps:

1. Enter into an interview mode and ask what type of user story I want to create (e.g., for a new feature, an existing feature…).

2. Gather details step by step by asking one relevant question at a time. Wait for an answer before proceeding.

3. After having gathered all important information, use it to create a user story using this format:
    -	As a [type of user], I want [goal] so that [benefit].
    -	Acceptance Criteria [with subcriteria if needed] that show the specific conditions that must be met for the user story to be considered complete.

Ask questions a senior developer would ask and keep the output aligned with standard user story best practices.

With this prompt, AI uses your expertise and creates a user story draft for you. Of course, you need to revise it and make sure it aligns with your idea. But it speeds up the process and provides a great basis to refine the task with your team.

Task 4: Creating Test Cases

Creating test cases can be a meticulous process, but it's necessary to ensure your features work as expected. AI can help you by drafting test cases based on your user stories and requirements, covering various scenarios and edge cases to ensure thorough testing. Here's how you can prompt AI to generate test cases:

Prompt to Generate Test CasesCopy
You are a QA specialist with expertise in creating detailed and thorough test cases. Based on the following user story, draft test cases in the Given-When-Then format that cover all relevant scenarios.

1. Scope: Ensure the test cases include: 
    -	Positive scenarios: What should work when used as intended.
    -	Negative scenarios: What happens when used in unexpected ways.
    -	Edge cases: Less common or extreme situations that could still occur.

2. Structure: Format the test cases as a table with these columns:
    -	Test Case ID: Unique identifier for the test case.
    -	Steps: Detailed steps to execute the test case.
    -	Expected Result: The outcome that determines if the test passes.
    -	Status: Placeholder for Passed/Failed status during testing.

3. Generate 5-7 test cases per user story and ensure clarity and precision in the instructions.

This is the given user story:
"""
[User Story]
"""

Task 5: Prepare Feature Prioritization

Feature prioritization can be overwhelming with so many competing factors to consider: business value, customer demand, technical feasibility, and more. And before you disagree with using AI for feature prioritization: We don't think you should use AI to get a list of randomly sorted features. Deciding what to tackle first is an important decision, that no AI should make for you.

However, AI can help by analyzing your feature list based on pre-defined criteria, allowing you to make faster, more informed decisions. It's all about the prompt, and for this task we suggest you try a chain-of-thought reasoning prompt like this:

Prompt for AI Guided Feature PrioritizationCopy
You are an experienced Product Manager skilled in feature prioritization. Your task is to analyze the potential of the following features for our next release of [Product Name]. Our overall goal is to [Goal, e.g. increase engagement]. Think step-by-step to ensure a clear and reasoned analysis:

1. Understand the Criteria: Evaluate each feature based on:
    -	Business Value: How much strategic or financial impact the feature has.
    -	Customer Demand: How frequently customers request or need this feature.
    -	Technical Feasibility: How complex or resource-intensive it is to implement.
    Make suggestions for each category. 

2. Analyze Features Priority: Guide me through the process of prioritizing features like a smart colleague would. Ask one smart question, that helps me to rank the given features based on the provided evaluation, wait for my answer, then ask the next question. You can ask for specific customer feedback or use very specific "either / or" questions to find out more about the features and which factors determine the priority. Together, we need to assign a certain value to each category for each feature (1-5). Use this structure:
    -	Business Value: Provide a score or a brief assessment.
    -	Customer Demand: Explain the level of demand.
    -	Technical Feasibility: Assess the effort required.

3. Prioritize features: Use the assigned value to assign a rank to each feature. Present the results in a table and include a brief explanation that outlines your reasoning.

These are the features to be prioritized:
"""
[List of Features]
"""

Adapt the prompt to consider criteria important in your company or team. You can use AI to support you in high-level prioritization, such as deciding which new features to implement in the next quarter and setting sprint goals. Or you can start with a specific sprint goal, and let the AI help you decide which stories or tasks align best with your goal.

Of course, there are many more tasks you could use AI for. Feel free to adapt the prompts to generate your expected output – or write and optimize your own prompts.

3 Scenarios AI Could Not Have Handled (Like You)

But as we said, not everything should be handed over to AI. As capable as AI is, some tasks require a human touch. We collected three scenarios, where a good Product Owner will outperform AI. They require deep human understanding, intuition, and foresight that go beyond data processing.

Scenario 1: Staring at the Roadmap, a.k.a. Making Key Product Decisions

You're staring at a roadmap with more features for the next quarter than your team could possibly deliver in three years. The CEO wants the moon, the developers want sanity, and the customers just want the app to stop crashing.

The facts are clear: there's a lot of potential, but not enough capacity to do everything at once. The room falls silent. All eyes are on you. Taking a deep breath, you break down the situation. You share the trade-offs in simple, no-nonsense terms, explaining how certain features could be delayed or adjusted to focus on what really makes the product. Together, you rearrange some priorities. Slowly, heads nod.

Making key product decisions demands balancing conflicting priorities and anticipating long-term consequences. An AI can't unify team perspectives into a single vision. Only a human PO can weigh strategic vision against reality, bring together different perspectives, and make the tough calls that create clarity and alignment across the team.

Scenario 2: Being Held Off by Sales in the Hallway, a.k.a. Building Relationships with Stakeholders

It's 5:48 PM and you're finally on your way out when the Head of Sales corners you in the hallway, gripping his coffee mug tightly. “We need this feature yesterday. It's costing us deals!” he says, arms crossed, clearly stressed.

Instead of brushing him off, you lean against the counter and listen to him vent. After a few minutes, you ask calm, pointed questions: “Which deals? How often does this happen? What's the real blocker here?” You also gently explain why the team's focus is elsewhere. His grip around the mug loosens, and by the time you've drawn a coffee for yourself, he's nodding and even brainstorming with you about how to prioritize the feature without compromising other goals.

Building trust with stakeholders happens in small moments like this, where communication not only strengthens a relationship but leads to alignment and smooth collaboration.

Scenario 3: Just Being One of Them, a.k.a. Building a Product Culture

It's Friday afternoon, and the team gathers for a retrospective. Someone shares a funny GIF about the last sprint's mishaps, and the room erupts in laughter. But the mood shifts again, and the question arises: “What can we do better next time?”

As the Product Owner, you could easily jump in with answers or start pointing fingers at the process. But instead, you lean back and share what you learned from your own mistakes this sprint. The team opens up. By the end of the retro, the team isn't just thinking about ways to improve – they own the product together focusing on how to deliver value to customers.

A strong product culture isn't built by having a Product Owner. It is built by a Product Owner who shows the team what it means to take ownership of the product's success. While AI can assist with the how, it can't define the what or inspire the why. And that's why it won't motivate your team to truly take ownership.

Don't read this. Do it: Your Next Steps to Become a Real AI-Empowered Product Owner

Relying on AI for decision making or product culture would be like asking your coffee machine to give a motivational speech – it's just not built for it. On the other hand, we should definitely not cut teams off from coffee.

So, what does that mean? We dream of you having more Product Owner superhero moments like in the scenarios mentioned earlier. So start using AI where it makes sense. Focus on the creative and strategic aspects of your job, and let the AI do the busy work for you.

But we have some bad news for you, though: Reading this blog post won't make you a better Product Owner. You need to put what you have just learned into practice. So, ask yourself the following three questions:

• What tasks do I want to spend more time on because they require my focus and expertise?
• What repetitive tasks do I spend the most time on that AI could handle faster and more efficiently?
• How can I efficiently implement AI in my daily work, so that it supports me in the best possible way?

If you can't yet imagine what it would be like to have AI supporting you in your day-to-day work, check out our Product Copilot. It is an AI for Product Owners that integrates with your issue tracker and helps you with your most urgent tasks – leaving you free to focus on what really makes your product.