UXPro – Generative AI UX Process Tool (Pitch & POC with Watsonx)
Year
2025
Role
UX Lead, AI Workflow Strategist & POC Driver
Problem Statement
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Challenges Faced by UX Teams
- Fragmented tools for research, personas, journey mapping, and documentation
- Heavy manual effort in generating UX artifacts
- Timeline pressures leading to skipped UX processes
- Limited stakeholder alignment
- Inconsistent documentation standards
My Role
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As the UX Lead, AI Workflow Strategist & POC Driver, I was responsible for:
- Conceptualizing UXPro as an end-to-end AI-powered UX lifecycle tool
- Defining the product vision, value proposition, and enterprise positioning
- Designing the complete UX workflow architecture (Research → Strategy → Documentation → Reporting)
- Creating structured prompts and frameworks for Generative AI outputs
- Collaborating with Watsonx teams to validate technical feasibility
- Developing the Proof of Concept (POC) flows and artifact generation structure
- Designing sample outputs including personas, journey maps, prioritization grids, and system-generated reports
- Presenting the pitch to stakeholders and leadership for validation and buy-in
Project Overview
UXPro was envisioned as a
Generative AI-powered UX Process Tool designed to streamline and
automate the end-to-end UX design lifecycle. Initiated within IBM Blue Studio as a
strategic pitch and Proof of Concept (POC) leveraging Watsonx, the
tool aimed to unify fragmented UX workflows into a single intelligent system.
Although UXPro was not fully productized, a working POC demonstrated how AI could generate structured UX documentation such as user stories, personas, empathy maps, scenario maps, competitive analysis, prioritization grids, and system-generated reports (as reflected in the sample Ux-Pro.pdf output).
The vision was to create a centralized platform where research, ideation, analysis, design strategy, documentation, and feedback loops could coexist within one AI-assisted ecosystem.
Although UXPro was not fully productized, a working POC demonstrated how AI could generate structured UX documentation such as user stories, personas, empathy maps, scenario maps, competitive analysis, prioritization grids, and system-generated reports (as reflected in the sample Ux-Pro.pdf output).
The vision was to create a centralized platform where research, ideation, analysis, design strategy, documentation, and feedback loops could coexist within one AI-assisted ecosystem.
Project Goal
- Automate and structure the full UX process using Generative AI
- Reduce time spent on repetitive documentation tasks
- Enable data-driven UX decision-making
- Improve stakeholder alignment through structured outputs
- Provide measurable ROI through efficiency and quality improvements
Proof of Concept (POC) Achievements
- Generated personas, empathy maps, and scenario documentation automatically
- Structured competitive analysis reports
- Created system-generated UX documentation in PDF format
- Demonstrated reduction in manual documentation effort
Constraints (for the POC)
- Time-boxed to a pitch/POC; no full production-grade product roadmap yet.
- Must reuse IBM watsonx Assistant / watsonx.ai capabilities rather than custom model hosting.
- Initial output format fixed as a multi-page PDF/PPT-like “UX PRO System Generated” report with sections such as:
- Project Overview
- User Story
- Market Analysis
- Persona
- Empathy Map
- As-is / To-be Scenario Map
- Prioritization Grid
- Wireframe
- UI
- Design Handoff
- Project Measures
UXPro end‑to‑end flow
Input Stage
Upload project requirements, interview transcripts, market data, and analytics.
Answer configuration prompts on goals, target segments, regions, and constraints.
AI orchestrates data parsing and normalization for consistent use across outputs.
Answer configuration prompts on goals, target segments, regions, and constraints.
AI orchestrates data parsing and normalization for consistent use across outputs.
Research Stage
Generate user stories and market analysis summaries with embedded charts.
Cluster data to propose target audiences and draft editable personas.
Create empathy maps (Says, Thinks, Does, Feels) from quotes and behaviors.
Cluster data to propose target audiences and draft editable personas.
Create empathy maps (Says, Thinks, Does, Feels) from quotes and behaviors.
Analysis Stage
Build as-is scenario maps showing current steps, pain points, and emotions.
Identify needs and pain points to inform solution directions.
Produce prioritization grids plotting ideas by impact vs. effort.
Identify needs and pain points to inform solution directions.
Produce prioritization grids plotting ideas by impact vs. effort.
Design Stage
Draft to-be scenario maps aligning improvements to user and business goals.
Suggest low-fidelity wireframes for key screens based on patterns.
Generate UI concepts and design handoff specs with flows and components.
Suggest low-fidelity wireframes for key screens based on patterns.
Generate UI concepts and design handoff specs with flows and components.
Measure Stage
Define qualitative/quantitative metrics like NPS, conversion, and engagement.
Set up feedback analysis dashboards with sample charts for iteration.
Output a unified "UX PRO System Generated" report tracing everything to inputs.
Set up feedback analysis dashboards with sample charts for iteration.
Output a unified "UX PRO System Generated" report tracing everything to inputs.
Key Users
- Business continuity personals
- NGO teams
- Geo leaders
- Travelers
- Supply chain companies
Core Pain Points
- Fragmented Tool Ecosystem
- Manual Documentation Overload
- Inconsistent UX Quality & Standards
- Delayed Stakeholder Alignment
- Skipped UX Phases Under Time Pressure
- Limited Research Synthesis Support
- Low UX Maturity in Some Teams
- Lack of Measurable UX Impact Metrics