Case Study 04 · Dell IntelliAssist 2.0 · Dell Technologies

I rebuilt Dell's AI workspace into a full-screen sales assistant.

Evolving Dell's AI support from a cramped chat box into a full-screen workspace where 12+ APIs, source-tagged answers, and the sales portal's tools all sit under one conversation. Ticket volume fell 55%, self-serve adoption hit 85%, and reps finally trusted what the AI said.

Shipped · 2024 AI Tools Enterprise Software Sales Enablement GenAI

IntelliAssist 2.0 landing screen showing the AI chat, prompt suggestions, and integrated sales tiles

IntelliAssist 2.0, the redesigned Dell AI sales workspace

The Challenge

Dell employees were stuck inside a cramped chat window that surfaced shallow AI answers and hid the platform's real capabilities. Checking a single order meant opening four other tabs, then pinging a teammate anyway.

The Solution

IntelliAssist 2.0, a full-screen AI workspace that unifies 12+ APIs, source-tagged answers, and the centralized sales portal into one place. Fewer tickets, more self-serve, and trust in what the AI says.

55%

Ticket volume reduced

across enterprise support

85%

Self-serve adoption

on the new workspace, from pilot telemetry

78%

Faster task completion

in testing, vs. 52% on legacy chat

Role

Lead UX Designerone of two designers · research, IA, interaction, visual

Team

Dell Technologies2 PMs, 8 engineers, 2 designers

Timeline

8 monthsdiscovery through pilot launch, 2024

Tools

Figma · Figma Make · Claude Design · Copilotdesign, prototyping, and AI-assisted build

Note: names, workflow details, and screen interfaces have been recreated to maintain Dell's confidentiality. The approach, decisions, and outcomes are intact. I chose not to password-gate this case study, since gates only add friction for the people I want to reach. For the real product and a walkthrough, reach out.

Snapshot

The short version.

If you only read three paragraphs, read these. Problem, change, and results in about a minute.

Problem

Dell employees worked inside a cramped chat box that surfaced shallow AI answers and hid the platform's real capabilities. Checking a single order meant opening four other tabs, then pinging a teammate. Adoption stalled and support tickets piled up.

Change

I rebuilt IntelliAssist into a full-screen AI workspace that unifies 12+ APIs, source-tagged answers, and the sales portal's tools under one conversation. Reps see where each answer came from, trust what they read, and stay inside one surface.

Results

From pilot telemetry and post-launch surveys: ticket volume dropped 55% across enterprise support, self-serve adoption hit 85% on the new workspace, task completion ran 78% faster vs. 52% on the legacy chat, and 85% of pilot users reported easier access to critical tools.

What & Why

Tiny chat. Wasted AI. Scattered tools.

Three problems showed up at the same time. The chat surface was too small for real work. The AI underneath gave generic answers that no one trusted. And the tools that could have helped were spread across a portal nobody could navigate. The redesign had to fix all three.

The What

A full-screen AI workspace: prompt suggestions, source-tagged answers, and the sales portal's tools sitting right under the conversation.

The Why

The business needed one stable platform to add AI and unify sales tools. Without it, adoption stalled and workflows stayed fragmented.

Research

Low trust, low discovery, high workaround behavior.

Across user interviews, a clear pattern emerged. Employees lacked confidence in the tool, found it slow to navigate, and rarely discovered features on their own. The result was low adoption, fragmented workflows, and delays in customer resolution.

The legacy IntelliAssist AI Result panel showing an order details response with limited context and no follow-up paths

Incomplete answer context

The AI gave surface-level details without supporting context, related information, or follow-up questions. Users couldn't tell what to trust.

"The chatbot gives generic answers. I can't trust it." Sales Representative

Legacy IntelliAssist landing screen with a sparse search input that hid the AI's full capabilities

Buried features, low adoption

The sparse landing screen failed to highlight the AI's full capabilities. Feature discovery was low, and employees defaulted to peer-dependent learning.

"I have to ping a teammate to get the right resource." Project Manager

Dell Technologies Sales Portal home with a wall of self-serve tiles that users routed around in favor of bookmarks

Workarounds replaced the tool

Search was so slow that users had quietly stopped using it. Bookmarks were faster, even when stale. The tool was being routed around, not used.

"I just use bookmarks. Searching takes too long." Data Engineer

Synthesis venn diagram, tiny chat plus wasted AI plus scattered tools converging into a unified workspace

Synthesis, three pain points converging into one unified workspace

Final Design

One workspace, five intentional decisions.

The shipped IntelliAssist 2.0 wraps a full-screen AI chat in a workspace that holds context. Underneath, five interface decisions made the new pattern work for employees who'd been burned by the old one.

Track 01

One workspace instead of six open tabs

Annotated overview of the IntelliAssist 2.0 landing showing where the smart prompt suggestions (1) and familiar self-serve tiles (2) sit on the page

Overview, two coordinated moves on a single landing screen

Prompts that show you what to ask

Role-specific prompt chips at first load kill the blank-page hesitation and quietly surface what the AI can actually do.

Contextual Onboarding · Behavior Design

Smart search input with role-specific prompt chips visible at first load

Kept the familiar cards from the old tool

Reusing the legacy card layout meant reps recognized the new workspace on day one, instead of relearning where everything lives.

Change Management · Mental Model

Full IntelliAssist 2.0 landing showing the search input with prompt suggestions above the self-serve tile grid

Track 02

Full-screen interface for contextual efficiency

Annotated overview of an IntelliAssist 2.0 result page showing the collapsible sidebar (1), follow-up prompts (2), and sources panel (3)

Overview, the full-screen workspace with sidebar, follow-ups, and sources in view

An escape hatch when the AI falls short

A collapsible sidebar lets reps self-navigate to the old tools, a familiar fallback that made committing to the new surface feel safe.

User Control · Flexibility · Fallback UX

Collapsible left-rail sidebar showing self-serve resource tiles like GenAI Sales Support and Order Tracking Hub

A way out of a dead-end answer

Follow-up chips and a "search instead" option let reps reframe a query when the AI misses, instead of hitting a blank wall.

Intent Refinement · Conversational UX

Follow-up question chips and a search-instead input shown below an AI response

Every answer shows its source

Visible sources and related links let reps check where an answer came from, which is what actually built trust in the AI.

Transparency · AI Explainability · Trust Design

Right-rail panel showing the source for the AI response with related articles listed underneath

The Shipped Design

IntelliAssist 2.0, end to end.

The five decisions added up to one workspace. A full-screen AI surface that holds context, surfaces prompts, attaches sources, and keeps the legacy self-serve tools one click away. This is the shipped state, the same view a Dell sales rep sees on day one.

The shipped IntelliAssist 2.0 workspace at full width showing the unified AI chat, prompt rail, sources, and self-serve tiles in one view

01. Landing, the unified workspace at first open

IntelliAssist 2.0 answering How to gain access to ESP with steps, key resources, sources, related articles, and a search-instead area below

02. Knowledge query, ESP access with sources, related articles, and a search-instead fallback

IntelliAssist 2.0 answering an order status query with an AI suggestion card, expandable order details, timeline, shipment, and cancellation accordions

03. Order status query, structured response with expandable details and a direct source link

"This tool transformed how our teams operate. Finally, the right resources are at their fingertips, exactly when needed."

Director, Operational Intelligence · IntelliAssist 2.0 launch retrospective

Impact

Three measurable shifts post-launch.

Due to tight launch timelines, we validated critical workflows with pilot users, iterating rapidly on feedback like confusing navigation and unclear AI responses. The numbers below come from pilot telemetry and post-launch surveys.

Workflow streamlining

Cut redundant tasks

40%

Centralizing AI chat, self-serve tiles, and sales tools cut redundant tasks like order tracking by 40%, letting employees focus on high-value work.

Platform consolidation

Eliminated daily platform-switching

72%

Integrated sales portal resources eliminated daily platform-switching for 72% of pilot users, freeing up time for higher-impact work.

AI adoption

Feature discovery up, friction down

55% / 85%

Feature discovery rose by 55%. 85% of users reported "easier access to critical tools" once the new workspace was live.

Learnings

What I'll take into the next AI project.

The constraints on this project (tight deadlines, leadership-driven requirements, ambiguous AI capabilities) weren't problems to solve. They were the conditions of the work. Three things I learned about designing inside them.

Business needs and user needs aren't opposites

Strict leadership requirements often mirrored hidden user needs, like faster workflows.

Treat constraints as guardrails, not roadblocks. Find the user need inside the business ask.

Limited time means ruthless prioritization

With tight deadlines, I prototyped only critical flows first like order tracking, then iterated post-launch.

Agility and quality coexist if you're honest about what to cut.

Compromise is strategy, not failure

Letting go of "perfect" features like custom animations freed time to solve bigger issues like AI response accuracy.

Progress beats perfection. Choose where to invest the polish.

Key Decision

Full-screen, not a bigger panel.

The legacy chatbot was a collapsible side panel. The obvious fix, and the one most stakeholders asked for, was to make the panel wider. I pushed back on that.

Why I chose full-screen

A panel is always secondary. A full-screen surface says: this is the tool.

If reps can keep the panel closed and still do their job, they will. Full-screen forced a commitment: open IntelliAssist or don't. That commitment eliminated the half-in, half-out usage pattern where reps would open the panel, distrust the answer, and call a teammate anyway. Ticket volume dropped 55% not because the AI got smarter, but because there was no easy exit to the old behavior.

What I traded away

Some reps wanted the panel back. Here's why I held the line.

Three pilot reps requested a "compact mode" during testing. My concern was that compact mode would become the default and reproduce the low-commitment usage we were trying to break. I proposed a collapsible source drawer instead: visible proof that answers are traceable, available without exiting the surface. That addressed the underlying need (transparency) without reopening the escape hatch.

Retrospective

What I took from this.

Two layers of impact that don't show up in the metrics. The work that shaped how I designed it, and the patterns the team kept using after I shipped.

Impact on me

Designing for AI trust is its own discipline.

Adoption didn't move when the AI got smarter. It moved when reps could see where each answer came from. Source-tagging, prompt suggestions, and recovery paths did more for behavior than any single model improvement. That changed how I scope every AI feature now.

14 enterprise-sales interviews shaped the workspace IA
5 prototype rounds with the pilot cohort before launch
What didn't work: running early iteration on surveys because telemetry came late. Two pilot rounds flew partially blind
What I'd do differently: invest in observability before the first pilot, not after the second

Impact on process

The patterns the next AI team picked up.

IntelliAssist 2.0 was the first full-screen AI surface at Dell. The patterns we shipped became the reference for every team that followed, so the next AI projects didn't have to rediscover what worked.

Source-tagged answer pattern adopted across Dell's enterprise AI surfaces
Prompt-suggestion grid added to the internal sales design system
Pilot feedback loop (telemetry plus surveys) reused on the next two AI launches