AI‑Assisted Project & Product Management
Researcher & Implementer
Exploratory and ongoing project analysing how AI can support project management and product ownership, from requirements gathering to execution monitoring, keeping sensitive data protected and the final decision on the human side.
Overview
Laboratory of AI-assisted PM/PO practices, studying tools, methodologies and workflows that can be adopted in a scalable way to increase productivity and quality without compromising sensitive data.
Challenge
Ensure confidentiality and compliance: no sharing of sensitive data, respect GDPR and NDAs with pseudonymisation, use only synthetic data, mandate human validation of outputs and log prompts and decisions.
Solution
Exploration of PM/PO use cases:
– Requirements gathering
– User journeys
– Process analysis
– Rapid prototyping
– Task prioritisation
– Resource allocation and scenario comparison
– Increment planning
– Automation of reports and administrative tasks
Results
- Average reduction of 30–50% in time spent on preparatory tasks such as status reports, meeting structure and first drafts of documentation
- Greater clarity in requirements documentation and definition of acceptance criteria
- Improved iteration pace between conception and feedback, shortening validation cycles
- Increased quality and objectivity in solution proposals based on multiple structured scenarios
Technologies and Methods
Detailed Implementation
Requirements Gathering
Structuring interviews, discovery guides and organising inputs.
User Journeys
Designing and validating user journeys and identifying pain points.
Process Analysis & Improvement
Brainstorming solutions, mapping improvements and assessing impact.
Rapid Prototyping
Creating wireframes and flows in Figma to support stakeholder discussions.
Prioritisation (MoSCoW)
Dynamic classification of requirements based on value and urgency.
Scenario Comparison
Presenting multiple options for human decision making.
Increment and Sprint Planning
Structuring the backlog, initial estimates and identifying dependencies.
Routine Automation
Assisted generation of status reports, executive summaries, plans and agendas.
Lessons Learned
- AI tools are excellent catalysts for ideas but require careful context and curation
- Integration with visual tools (Figma, Miro) enhances clarity for stakeholders
- Prompt templates and workflows ensure consistency and reduce cognitive effort
- AI is useful in early discovery and planning stages but does not replace human validation
Next Steps
- Test autonomous agents to automate repetitive tasks (e.g. status reports and sprint summaries)
- Create a library of PM/PO prompt templates tailored to different contexts and project types
- Integrate with the site blog, producing articles on project management, enterprise architecture and prioritisation best practices
- Implement email marketing to share content and automate communication cycles
- Explore metrics to evaluate the ROI of using AI in PM/PO