Redesigning enterprise diagnostics into a guided, AI-assisted support experience for AT&T Business customers.
01
PROJECT OVERVIEW
Troubleshooting shouldn't be harder than the problem itself.
AT&T Business customers navigated fragmented diagnostic tools, technical documentation, and disconnected support channels to resolve service issues. The challenge was to create a more intuitive, connected self-service experience.
My Role
I led the research, experience design, and high-level solution architecture for the new troubleshooting framework, partnering with Product, Engineering, ServiceNow stakeholders, researchers, and technical SMEs to shape both the customer experience and the foundation for future support experiences.
DaaS Experience - Before
02
APPROACH & USER RESEARCH
The team's initial hypothesis was that improving AI and diagnostic capabilities would increase self-service adoption.
Before fully incorporating AI though, I wanted to understand why customers weren't using self-service.
RESEARCH METHODS
Customer interviews, Internal agent interviews, Journey mapping, Technical documentation audits
03
THE CHALLENGE
Customers didn't abandon troubleshooting because recommendations were inaccurate.
They abandoned it because they couldn't understand what the system was doing, why it was asking certain questions, or whether it was actually helping. That insight completely changed the direction.
04
THE PIVOT
I Stopped Designing solely AI.
I Started Designing Trust.
Research revealed that the real challenge wasn't AI capability - it was a lack of trust in the self-service experience.
Proposed Journey Map - Happy Path
05
Design Patterns
Content
Content
Content
Designing a Framework for Trust
Instead of iterating on a single interface, I explored multiple concepts that worked together to build confidence throughout the troubleshooting journey.
Visibility
Making system activity understandable through progress indicators, wait states, and feedback loops.
Show clear progress and what's happening
Do
Avoid indefinite waiting
DoN'T
Knowledge in Context
Surfacing relevant documentation inside the troubleshooting journey instead of sending users to a separate knowledge base.
Deliver the right help, in the flow
Do
Avoid context switching
DoN'T
AI-Assisted Guidance
Providing intelligent recommendations with reasoning and next steps that feel actionable and trustworthy.
Provide relevant, transparent guidance
Do
Avoid generic, low-value suggestions
DoN'T
Escalation & Handoff
Ensuring a seamless transition to human support with full context and history preserved.
Pass context and history to the agent
Do
Avoid starting over
DoN'T
Trust at Every Step
Building confidence through clarity, consistency, and transparency at every moment of the journey.
Be clear, honest and actionable
Do
Avoid ambiguous outcomes
DoN'T
06
Results
A clearer path to resolution.
A foundation for what's next.
DaaS reimagined how customers diagnose and resolve service issues, replacing fragmented troubleshooting with guided progress, contextual feedback, and clearer next steps.
Projected Annual Savings
$1.2M–$2.4M
Potential enterprise savings from fewer unnecessary support escalations.
EXPECTED EXPERIENCE IMPACT
Designed to reduce friction at every step.
5–7%
Fewer live support escalations
More issues addressed through self-service
10–20%
Faster diagnostics.
Less time spent identifying problems
20–30%
Higher customer confidence
Greater clarity and transparency
Directional estimates based on benchmark data, early usability testing, and stakeholder input. Charts are illustrative, not measured trends.
THE EXPERIENCE
From uncertainty to guided resolution.
A single diagnostic journey made system status, progress, and recommended actions easier to understand.
THE BIGGER PICTURE
Built to scale beyond a single journey.
Reusable interaction patterns for diagnostics, progress, system feedback, and resolution helped inform AT&T Business's broader Incident Management ecosystem within ServiceNow.
Transparent diagnostic states
Consistent system feedback
Actionable resolution guidance
THE TAKEAWAY
Better diagnostics today.
A stronger foundation for AI-assisted support tomorrow.
By making system information more transparent and resolution guidance more consistent, DaaS established experience patterns that could support more intelligent, connected service interactions.
07
WHAT'S NEXT
A foundation for enterprise AI
This framework was intentionally designed to evolve alongside AT&T Business's growing AI capabilities.
Future iterations could shift from helping customers resolve issues to anticipating them before they interrupt business operations.
Future opportunities
1
2
3
4
Adaptive Guidance
How much guidance should users receive before it becomes distracting?
Confidence Signals
How can the interface communicate uncertainty without reducing trust?
Human Handoff
What information actually helps support agents continue the conversation seamlessly?
Platform Consistency
How can these interaction patterns scale across additional ServiceNow workflows and / or AT&T Business products?
08
REFLECTION
AI doesn't inherently create trust.
Good experiences do.
This project changed the way I think about AI in product design.
The biggest challenge wasn't making AI smarter.
It was understanding where AI added value, and where thoughtful interaction design, clear communication, and human-centered content mattered more.
By designing AI as a guide rather than the destination, we created a framework that customers could understand, teams could scale, and future products could build upon.
