Platform AI Experience
UX Patterns & Design System
AI Companion for MoneySuperMarket
Driving the creation and implementation of the AI Companion UX, including UX patterns, language guidelines, and service mapping across MoneySuperMarket's platforms.
Timeline
2025 - 2026
Role
Product Designer
Platform
Multi-Platform
Tools
Figma, FigJam
Overview
Defining the future of AI at MONY Group
I established the foundational framework for how artificial intelligence integrates across the entire MONY Group companies.
This comprehensive system includes mental models, role definitions, UX patterns, language guidelines, and service mapping—ensuring every AI feature aligns with user needs and provides clear, consistent value.
Key Deliverables
UX Patterns
AI Roles Defined
UX Principles
UX Patterns Created
Language Guidelines
Core Principles
01 • Research & Insights
Understanding how AI shapes financial decisions
Through diary studies and user interviews, we explored how consumers integrate AI into shopping, financial planning, and decision-making — revealing critical opportunities for price comparison platforms.
Strategic Opportunities
Become the trusted AI proactive assistant, not a conversational experience
Position AI not as a search box, but as a smart guide that explains options and trade-offs, helping users make confident decisions.
Integrate real-time, reliable data
Combine real-time data feeds with AI summaries to address AI's current weakness in accuracy and up-to-date information.
Extend into financial wellbeing
Develop budgeting and savings simulations, offering "what-if" scenarios that help users model long-term savings from switching products or services.
02 • UX Strategy
A comprehensive framework for AI experiences
I developed a complete UX strategy combining AI roles, interaction patterns, design principles, and language guidelines to ensure consistent, valuable AI experiences across all touchpoints.
AI Roles & Intent
Three distinct roles that define the job AI performs and the value it provides
High Control
Assistant
Removes friction and keeps users moving. Used when progress can be unblocked with minimal interruption.
Typical Outcomes
•
Inline suggestions
•
Smart defaults
•
Contextual hints
Pattern: Embedded
Med-High Control
Analyst
Supports confident decision-making. Used when users need context, comparison, or trade-offs.
Typical Outcomes
•
Price insights
•
Summaries
•
Ranked options
Pattern: Embedded, Focused
Outcome Control
Operator
Takes responsibility for complex tasks. Used when tasks can be delegated end-to-end.
Typical Outcomes
•
Price optimization
•
Requoting
•
Automated updates
Pattern: Immersive
Role Selection Framework
Interaction Patterns
How AI manifests in the interface—from embedded helpers to immersive experiences.
01
Embedded
Best for
Assistant and Analyst roles
"Things just work the way I expect them to"
02
Focused
Dedicated AI space within a journey. Provides time and space to think or review.
Best for
Analyst and Operator roles
"This helps me work through the task with more clarity"
Service Mapping
The AI Mony Platform differentiates itself through Capability and Experience. We believe that an AI is only as good as its integration into the existing service ecosystem. By meticulously mapping our tools to the UX, we ensure the AI isn't a bolt-on feature, but a seamless extension of our service DNA.
03 • Implementation
Bringing the framework to life
Beyond defining the strategic framework, I designed and implemented AI experiences across multiple platforms, creating the actual user-facing products.
ChatGPT Integration
First financial ChatGPT app launched in the UK
Designed the conversational layer for MoneySuperMarket within the ChatGPT ecosystem, ensuring brand consistency and service value in a third-party environment.
Price Optimiser
Operator Role • Immersive Pattern
An AI-powered feature that automatically finds better insurance deals by optimising user details. Takes full responsibility for the complex task of requoting with adjusted parameters, demonstrating the Operator role with an immersive, system-led experience.
Challenge
Users often overlook opportunities to save by adjusting details like job title, mileage, or voluntary excess.
Solution
AI analyses the quote and automatically tests variations to find cheaper options, presenting only meaningful savings.
Impact
Users discover savings without manual effort, building trust through transparent explanation of changes made.
UI Tokens & Components
Created a comprehensive design system specifically for AI features, including standardized tokens, interaction patterns, and reusable components that ensure consistent AI manifestation across the platform.
04 • Impact & Outcomes
A scalable framework for AI across the organization
Framework Adoption
Unified AI strategy across all MONY Group brands
Shared vocabulary for product teams, engineers, and stakeholders
Clear guidelines reducing design and development time for new AI features
Design Excellence
Consistent user experience across web, mobile, and third-party platforms
User-centered AI that prioritizes trust, clarity, and control
Scalable patterns that grow with evolving AI capabilities
Key Learnings
What made this project successful
Start with mental models, not features
By focusing on what users believe AI is doing rather than technical capabilities, we created a framework that remains relevant as technology evolves.
Roles create clarity
Defining Assistant, Analyst, and Operator gave teams a simple decision framework that eliminated ambiguity in product discussions.
Patterns enable scale
Embedded, Focused, and Immersive patterns provided reusable solutions that could be applied consistently across different products and use cases.
Principles guide execution
Accountable, Intentional, and Contextual principles ensured every team member could evaluate AI features against a clear set of criteria.