6 AI Prompt Templates for Product Managers

As product teams navigate increasingly complex challenges, many are turning to AI to streamline workflows and unlock new insights. These practical AI prompt templates and examples demonstrate how product managers can leverage AI (not be replaced by it) and become a force multiplier for critical tasks—from documenting requirements to synthesizing research.

An Overview of Prompting Best Practices

Just like with any technology, knowing how to use the tool effectively helps achieve the best outputs. To get the most out of AI, product managers have to learn how to prompt––it’s not just about having the templates. Follow these key prompting best practices:

• Make Implicit Context Explicit: AI doesn't know your background or objectives unless you share them. Provide clear, comprehensive context about your specific scenario rather than using vague requests.
• Leverage Examples: Include relevant examples to guide the AI's understanding and reduce the need for extensive context. Share templates or successful formats you want the AI to follow.
• Embrace Iteration: Treat AI interactions as collaborative conversations, refining your prompts based on initial responses. 
• Include the 6 Key Components: Structure effective prompts using:

1. Task: What you want the model to perform
2. Context: Background information and specific objectives
3. Examples: Concrete samples of desired outputs
4. Persona: The role you want the AI to assume
5. Format: Your desired output structure
6. Tone: The emotional or professional tenor of the output

With these habits in mind, product managers can add both rigor and flexibility to their AI usage.

6 Key Product Management Functions AI Can Streamline

Let's explore six essential product management functions where AI can significantly reduce manual effort while improving quality and consistency. From documenting requirements and synthesizing research to analyzing competitors, prioritizing roadmaps, communicating with stakeholders, and developing user personas—AI can transform hours of tactical work into minutes of strategic refinement.

Product Requirements Document (PRD) Generation

PRD generation can be tedious and time-consuming––an obvious use case for AI. After performing in-depth discovery, leverage AI to draft a PRD for you to perfect. To get the best results and save time on documentation, make sure to include your company’s PRD template with your prompt. And, of course, AI is not a substitute for deep research. The quality and amount of information you put in determines the success of your output.

PRD AI Prompt Template:

Generate a comprehensive PRD for a new [feature type] that addresses [specific problem]. Act as a senior product manager at [your company name] which specializes in [industry/vertical]. Include sections on [list required sections]. Our target customers are [customer description] who face challenges with [specific pain points].

PRD AI Prompt Examples: 

PRD Prompt Example 1:

Generate a comprehensive PRD for a new contactless guest experience platform that addresses traditional friction points in the hotel journey. Act as a senior product manager at StayWell Hotels which specializes in upscale business and leisure accommodations with a digital-first approach. Include sections on competitive benchmark analysis, guest persona needs, mobile key technology requirements, digital concierge functionality, room customization features, IoT device integration, guest preference engine, staff notification system, payment processing requirements, and implementation roadmap with property rollout strategy. Our target customers are tech-savvy business and leisure travelers who face challenges with check-in queues, communicating preferences and requests, and accessing hotel services without unnecessary face-to-face interactions.

PRD Prompt Example 2:

Generate a comprehensive PRD for a new real-time travel disruption assistant that addresses flight delay and cancellation stress. Act as a senior product manager at SkyConnect Airlines which specializes in passenger-focused digital experiences across our international route network. Include sections on business case, passenger journey impact, persona-specific use cases, real-time notification system, rebooking algorithm requirements, alternative travel suggestions logic, compensation voucher integration, cross-platform functionality, offline capabilities, and loyalty program integration. Our target customers are frequent business travelers and family vacationers who face challenges with last-minute itinerary changes, understanding their options during disruptions, and accessing support when airport staff are overwhelmed.

User Research Synthesis

By quickly synthesizing user feedback from multiple sources, AI can help product managers uncover actionable insights and prioritize feature development based on genuine user needs rather than assumptions. Note that you may need to take extra time formatting the source material for clarity and that there will be limitations on how much data you can upload depending on the tool you’re using. 

User Research AI Prompt Template:

Analyze these [number] [data type: interview transcripts/survey responses/user feedback comments]. Identify the top [number] [insight type: pain points/feature requests/user needs], unexpected insights, and potential opportunities. Prioritize findings based on [criteria] and format as a [desired output format] with [specific elements to include].

User Research AI Prompt Examples: 

User Research Prompt Example 1:

Analyze these 25 in-home observation session transcripts of users interacting with our voice interface. Identify the top 6 interaction failure points, unexpected insights about conversational patterns, and potential opportunities for natural language improvements. Prioritize findings based on frequency of occurrence and impact on user trust scores, and format as an actionable insights report with conversation flow diagrams, success/failure metrics by command category, and specific dialogue enhancement recommendations for our next quarterly release.

User Research Prompt Example 2:

Analyze these 12 longitudinal customer journey diaries from IT teams implementing our enterprise software over a 90-day period. Identify the top 4 transition challenges, unexpected insights about cross-team dependencies, and potential opportunities for improved customer success touchpoints. Prioritize findings based on time-to-implementation impact and customer effort scores, and format as a service blueprint with critical moments of truth, process bottlenecks, and recommended process improvements that our Customer Success team can implement within 60 days.

Competitive Analysis

With the vastness of the internet, AI can rapidly gather and synthesize competitive intelligence from various sources, providing a comprehensive, objective view of the competitive landscape without the confirmation bias that often affects manual analysis. This enables product managers to make more strategic decisions about positioning, feature development, and go-to-market strategies based on a thorough understanding of competitors' strengths and weaknesses. However, this can be impacted by the recency of an AI model’s data (as of March 2025, ChatGPT’s is trained on data from up to June 2024). Consider uploading your own compiled research materials to supplement AI’s data. 

Competitive Analysis AI Prompt Template:

Conduct a comprehensive competitive analysis of [your product]'s top [number] competitors in the [specific market segment]. Compare [specific aspects to compare] and highlight [specific insights needed]. Provide a [analysis framework: SWOT/competitive matrix] for each competitor and recommend potential [strategic recommendations needed] for our product.

Competitive Analysis AI Prompt Examples: 

Competitive Analysis Prompt Example 1:

Conduct a comprehensive competitive analysis of EditPro's top 4 competitors in the prosumer video editing software market. Compare rendering performance, template libraries, effects capabilities, and subscription models. Highlight gaps in competitor cloud collaboration features and identify which AI-powered editing features are resonating with creator audiences. Provide a SWOT analysis for each competitor and recommend potential feature prioritization and pricing tier strategies for our product to effectively compete against Adobe Premiere Pro, Final Cut Pro, DaVinci Resolve, and Filmora while maintaining our speed advantage.

Competitive Analysis Prompt Example 2:

Conduct a comprehensive competitive analysis of PeopleFirst's top 5 competitors in the mid-sized business HR management system market. Compare employee onboarding workflows, performance review capabilities, compliance management features, and mobile accessibility. Highlight competitor weaknesses in handling hybrid workforce management and identify emerging trends in employee wellness tracking. Provide a competitive matrix for each competitor with implementation timeline and TCO comparisons and recommend potential vertical-specific enhancements and implementation support strategies for our system to strengthen positioning against Workday, BambooHR, ADP Workforce Now, Gusto, and Zenefits.

Roadmap Prioritization

AI can objectively evaluate multiple competing priorities against complex criteria, helping product managers make more balanced decisions that align with both business goals and customer needs. By processing large amounts of data points and identifying non-obvious correlations between features and outcomes, AI reduces the cognitive bias that often plagues prioritization discussions. Customize this prompt template to the specific metrics relevant to your company right now whether that’s revenue impact, customer impact, or a blend of the two. 

Roadmap Prioritization AI Prompt Template:

Given the following feature requests and their impact scores: [list features with metrics], suggest a prioritization framework based on [criteria 1] and [criteria 2]. Consider our quarterly goals of [goals] and resource constraints of [constraints]. Recommend the top [number] features to focus on first with justification.

Roadmap Prioritization AI Prompt Examples: 

Roadmap Prioritization Prompt Example 1:

Given the following feature requests and their impact scores: [1. In-app messaging (user engagement score: 8.2/10, development complexity: medium), 2. Dark mode support (user engagement score: 7.1/10, development complexity: low), 3. Offline mode (user engagement score: 8.7/10, development complexity: high), 4. Social sharing integration (user engagement score: 6.5/10, development complexity: medium), 5. Biometric authentication (user engagement score: 7.9/10, development complexity: medium)], suggest a prioritization framework based on user retention impact and technical feasibility. Consider our quarterly goals of reducing churn by 5% and increasing daily active users by 20%, and resource constraints of a 6-week development cycle with one cross-functional team. Recommend the top 2 features to focus on first with justification for why they will deliver the highest user value with our current technical capabilities.

Roadmap Prioritization Prompt Example 2:

Given the following feature requests and their impact scores: [1. Telehealth integration (patient satisfaction impact: 8.5/10, regulatory complexity: high), 2. Medication adherence reminders (patient satisfaction impact: 7.8/10, regulatory complexity: low), 3. Health data visualization (patient satisfaction impact: 7.2/10, regulatory complexity: medium), 4. Care team messaging (patient satisfaction impact: 8.1/10, regulatory complexity: medium), 5. Appointment self-scheduling (patient satisfaction impact: 8.7/10, regulatory complexity: medium)], suggest a prioritization framework based on clinical outcome improvement and implementation feasibility. Consider our quarterly goals of improving patient engagement by 25% and meeting updated HIPAA compliance requirements, and resource constraints of limited QA resources and a 90-day validation cycle. Recommend the top 2 features to focus on first with justification for how they balance patient experience improvements with our compliance obligations.

Stakeholder Communication

AI can craft clear, concise updates that translate technical details into business value, ensuring consistent messaging across different stakeholder groups without requiring extensive rewrites. By automatically focusing on the most relevant information for each audience type, AI helps product managers maintain transparent communication without spending hours crafting and tailoring different messages.

Stakeholder Communication AI Prompt Template:

Write an [communication type] for [specific audience] summarizing [specific topic/update]. Emphasize the [business impact/strategic implications/progress against goals]. Keep it [tone: concise/detailed/technical] and focus on [specific aspects to highlight]. Include [any specific sections or data points].

Stakeholder Communication AI Prompt Examples: 

Stakeholder Communication Prompt Example 1:

Write a project brief for cross-functional team leads summarizing the shift in our Q3 roadmap priorities following the competitive analysis findings. Emphasize the strategic implications for each department's resource planning and timeline adjustments. Keep it structured and actionable and focus on the rationale behind the reprioritization decisions. Include a responsibility matrix, updated milestone dates, and specific documentation on how these changes align with our annual strategic objectives and market positioning.

Stakeholder Communication Prompt Example 2:

Write an email announcement for existing enterprise customers summarizing the upcoming platform security enhancements releasing next month. Emphasize the business impact on their compliance requirements and data protection capabilities. Keep it detailed yet accessible and focus on the implementation steps required on their end. Include specific sections on SSO improvements, data retention policy changes, and a FAQ addressing common migration questions with step-by-step preparation instructions for their IT administrators.

User Persona Development

AI can synthesize patterns from customer data, market research, and behavioral analytics to create multi-dimensional personas that reflect real user segments rather than stereotypes. This allows product managers to design features based on authentic user needs and behaviors, moving beyond superficial demographic information to create truly user-centered products.

User Persona AI Prompt Template:

Generate [number] user personas for a [product type] designed for [target market]. Base these personas on [data sources: customer feedback/industry research/behavioral data]. For each persona, include [specific elements: demographics/goals/pain points/behavioral traits/day in the life]. Ensure these personas represent [specific user segments] and highlight how they would interact with [specific product features].

User Persona AI Prompt Examples: 

User Persona Prompt Example 1:

Generate 3 user personas for a habit-building wellness app designed for busy professionals. Base these personas on our app store reviews, engagement analytics, and qualitative feedback from our user research sessions. For each persona, include age range, career stage, health goals, current wellness routine, key motivators, obstacles to consistency, app usage patterns, social support context, and content consumption preferences. Ensure these personas represent different fitness levels and wellness priorities, and highlight how they would interact with our milestone tracking, community features, and personalized coaching components.

User Persona Prompt Example 2:

Generate 4 user personas for a supply chain management platform designed for mid-sized manufacturers. Base these personas on stakeholder interviews, industry research on manufacturing challenges, and workflow analysis from our site visits. For each persona, include organizational role, decision-making authority, key responsibilities, performance metrics, cross-department interactions, technical background, compliance concerns, and reporting requirements. Ensure these personas represent the full procurement-to-production ecosystem including procurement specialists, inventory managers, production planners, and logistics coordinators, and highlight how they would interact with our inventory forecasting tools, supplier management features, and real-time production tracking capabilities.

Breaking Down Complex AI Tasks: The Chunking Approach

If the above prompts feel dense, that’s because they are. All of the above tasks are complex and require effort (which is why AI is so appealing). Consider breaking requests into smaller chunks to achieve better results if you find that attempting everything at once doesn’t yield the output you’re looking for. Here are a few approaches: 

• Zero-Shot vs. Few-Shot Prompting
• Zero-shot: Asking the AI to perform a task without examples
• Few-shot: Providing 1-3 examples to guide the AI's understanding
• Chain of Thought Prompting 
• Breaking complex tasks into logical steps that guide the AI through your reasoning process.
• Eg: “Prioritize our roadmap following these steps: 1, 2, 3”

By implementing these chunking strategies alongside the prompt templates, you can make AI a reliable part of your workflow.

Working Smarter, Not Harder with AI

Product managers face countless demands on their time—from documentation and analysis to stakeholder management and strategic planning. By incorporating these AI prompt templates into your workflow, you can automate routine tasks, uncover deeper insights, and create more consistent communication.

The key is using AI as a thought partner rather than a replacement for critical thinking. When you provide detailed context and specific requirements, these prompts can produce remarkably useful first drafts that you can refine with your product expertise and domain knowledge.

At Productboard, we've seen how thoughtful AI implementation can give product teams back precious hours in their day while improving the quality of their deliverables, especially when it comes to enhancing voice-of-customer programs with scaled feedback analysis. 

Try these prompts with your favorite AI assistant and discover how they can enhance your product management practice while freeing you to focus on what matters most—building products that truly solve customer problems.