GenAI Billing Assistant
Client:
TelcoOne
Role:
UI/UX Designer
GenAI Billing Assistant
Overview
The GenAI Billing Assistant was an exploratory concept developed to redefine how telecom customers interact with their bills.
By combining conversational AI with a dynamic dashboard, the goal was to transform static billing data into an intelligent, human-like experience that could explain charges, predict costs, and guide users toward smarter account management.
As Lead Designer, I was responsible for shaping the vision, interface, and interaction model that demonstrated the future potential of AI-powered customer care.
Problem
Billing is one of the biggest pain points for telecom customers.
Users often struggle to understand charges, promotions, and plan changes which leads to frustration and unnecessary calls to support centres.
Despite modern UI improvements, billing pages remain reactive and static, offering limited help or context when questions arise.
Approach
We aimed to shift the experience from passive viewing to active understanding:
Explored how LLMs could contextualise billing data, explain variances, and identify savings opportunities.
Designed a hybrid interface where chat and visual data coexist, allowing customers to ask questions naturally while seeing real-time responses reflected in their dashboard.
Focused on transparency and reassurance, using tone, motion, and clarity to make complex financial data feel human.
Collaborated with AI innovation and product strategy teams to ensure feasibility for future enterprise integration.
Early Concepts
Before settling on the final direction, several experimental layouts were explored — each testing how far we could push AI-driven interaction inside a billing context.
These early prototypes focused on different approaches to visibility and hierarchy, from fully expanded dashboards to minimal conversational entry points.
While they demonstrated strong visual clarity, user testing and internal feedback revealed the need for a simpler, more focused flow that balanced automation with familiarity.
These explorations helped shape the final concept by proving what worked, what didn’t, and how users naturally wanted to interact with AI inside a traditionally static experience.
Problem
Billing is one of the biggest pain points for telecom customers.
Users often struggle to understand charges, promotions, and plan changes which leads to frustration and unnecessary calls to support centres.
Despite modern UI improvements, billing pages remain reactive and static, offering limited help or context when questions arise.
Approach
We aimed to shift the experience from passive viewing to active understanding:
Explored how LLMs could contextualise billing data, explain variances, and identify savings opportunities.
Designed a hybrid interface where chat and visual data coexist, allowing customers to ask questions naturally while seeing real-time responses reflected in their dashboard.
Focused on transparency and reassurance, using tone, motion, and clarity to make complex financial data feel human.
Collaborated with AI innovation and product strategy teams to ensure feasibility for future enterprise integration.
Early Concepts
Before settling on the final direction, several experimental layouts were explored — each testing how far we could push AI-driven interaction inside a billing context.
These early prototypes focused on different approaches to visibility and hierarchy, from fully expanded dashboards to minimal conversational entry points.
While they demonstrated strong visual clarity, user testing and internal feedback revealed the need for a simpler, more focused flow that balanced automation with familiarity.
These explorations helped shape the final concept by proving what worked, what didn’t, and how users naturally wanted to interact with AI inside a traditionally static experience.
Problem
Billing is one of the biggest pain points for telecom customers.
Users often struggle to understand charges, promotions, and plan changes which leads to frustration and unnecessary calls to support centres.
Despite modern UI improvements, billing pages remain reactive and static, offering limited help or context when questions arise.
Approach
We aimed to shift the experience from passive viewing to active understanding:
Explored how LLMs could contextualise billing data, explain variances, and identify savings opportunities.
Designed a hybrid interface where chat and visual data coexist, allowing customers to ask questions naturally while seeing real-time responses reflected in their dashboard.
Focused on transparency and reassurance, using tone, motion, and clarity to make complex financial data feel human.
Collaborated with AI innovation and product strategy teams to ensure feasibility for future enterprise integration.
Early Concepts
Before settling on the final direction, several experimental layouts were explored — each testing how far we could push AI-driven interaction inside a billing context.
These early prototypes focused on different approaches to visibility and hierarchy, from fully expanded dashboards to minimal conversational entry points.
While they demonstrated strong visual clarity, user testing and internal feedback revealed the need for a simpler, more focused flow that balanced automation with familiarity.
These explorations helped shape the final concept by proving what worked, what didn’t, and how users naturally wanted to interact with AI inside a traditionally static experience.
Solution
The concept featured an AI-powered conversational dashboard where customers could:
Ask natural questions like “Why is my bill higher this month?” or “How can I reduce roaming costs?”
View instant, contextual explanations tied directly to their data.
Receive proactive insights — such as plan recommendations, savings alerts, or upcoming charge predictions.
Seamlessly act on AI suggestions (e.g., change plans, manage AutoPay, or request support) — all from one interface.
Results
The result was a new billing paradigm: from confusion and calls-to-care to clarity and self-service.
Although still at concept stage, the GenAI Billing Assistant became a strategic showcase of innovation within Amdocs.
It sparked conversations across design, product, and AI teams about how generative models could transform billing UX.
Used in sales demos and client presentations to illustrate Amdocs’ forward-thinking approach to customer care.
Helped define design standards for conversational interfaces and hybrid data dashboards across future AI initiatives.
Positioned the design team as leaders in envisioning next-generation billing experiences.
Conclusion
The GenAI Billing Assistant represents a shift in how people could interact with their bills — from confusion and static data to clarity through conversation.
It reimagines billing as a dialogue, not a document — where users can ask, understand, and act instantly.
This project showed how thoughtful design and emerging AI can turn complex information into something intuitive, human, and genuinely helpful — setting a foundation for how digital experiences may evolve in the years ahead.
Solution
The concept featured an AI-powered conversational dashboard where customers could:
Ask natural questions like “Why is my bill higher this month?” or “How can I reduce roaming costs?”
View instant, contextual explanations tied directly to their data.
Receive proactive insights — such as plan recommendations, savings alerts, or upcoming charge predictions.
Seamlessly act on AI suggestions (e.g., change plans, manage AutoPay, or request support) — all from one interface.
Results
The result was a new billing paradigm: from confusion and calls-to-care to clarity and self-service.
Although still at concept stage, the GenAI Billing Assistant became a strategic showcase of innovation within Amdocs.
It sparked conversations across design, product, and AI teams about how generative models could transform billing UX.
Used in sales demos and client presentations to illustrate Amdocs’ forward-thinking approach to customer care.
Helped define design standards for conversational interfaces and hybrid data dashboards across future AI initiatives.
Positioned the design team as leaders in envisioning next-generation billing experiences.
Conclusion
The GenAI Billing Assistant represents a shift in how people could interact with their bills — from confusion and static data to clarity through conversation.
It reimagines billing as a dialogue, not a document — where users can ask, understand, and act instantly.
This project showed how thoughtful design and emerging AI can turn complex information into something intuitive, human, and genuinely helpful — setting a foundation for how digital experiences may evolve in the years ahead.
Solution
The concept featured an AI-powered conversational dashboard where customers could:
Ask natural questions like “Why is my bill higher this month?” or “How can I reduce roaming costs?”
View instant, contextual explanations tied directly to their data.
Receive proactive insights — such as plan recommendations, savings alerts, or upcoming charge predictions.
Seamlessly act on AI suggestions (e.g., change plans, manage AutoPay, or request support) — all from one interface.
Results
The result was a new billing paradigm: from confusion and calls-to-care to clarity and self-service.
Although still at concept stage, the GenAI Billing Assistant became a strategic showcase of innovation within Amdocs.
It sparked conversations across design, product, and AI teams about how generative models could transform billing UX.
Used in sales demos and client presentations to illustrate Amdocs’ forward-thinking approach to customer care.
Helped define design standards for conversational interfaces and hybrid data dashboards across future AI initiatives.
Positioned the design team as leaders in envisioning next-generation billing experiences.
Conclusion
The GenAI Billing Assistant represents a shift in how people could interact with their bills — from confusion and static data to clarity through conversation.
It reimagines billing as a dialogue, not a document — where users can ask, understand, and act instantly.
This project showed how thoughtful design and emerging AI can turn complex information into something intuitive, human, and genuinely helpful — setting a foundation for how digital experiences may evolve in the years ahead.
