Walmart · 2024
My Assistant + Intelligent Operations
Operational work was spread across systems that never explained themselves.
Task preview
Interface recreated for portfolio presentation to protect confidential product information.
My role
Senior UX Designer
Impact
- 30% increase in ai engagement
Scope
- AI interaction model
- Conversational flows
- Product design
- Prototyping
- Cross-functional alignment
Timeline
2024 — 2025
The challenge
Associates were expected to know which system held the answer, and in what order to visit them.
The opportunity
An assistant that reads operational intent and assembles the workflow instead of pointing at it.
What research changed
Intent is rarely a question
Many inputs were tasks in disguise — a question about a delivery usually meant a plan needed changing.
Context beats personalization
Store, shift and role scoped the right answer more reliably than usage history.
Generative output needs edges
Free-form text without structure was read as unreliable, even when it was correct.
Decisions
Decision 01
Generative systems propose; people commit.
- Let the assistant act autonomously
- Require confirmation on every action
- Confirm only high-impact actions
Options considered
- What changed my mind
- In testing, an action taken without a preview was read as a mistake even when it was correct.
- Why
- Operational work is accountable work — the person answering for the outcome should authorise it.
- Tradeoff
- An extra step in every flow, traded for a system people are willing to keep using.
Decision 02
Render answers as structured, typed components.
- Answer in prose
- Answer in typed components
Options considered
- What changed my mind
- Prose forced re-reading; people looked for the same fact in a different place each time.
- Why
- A predictable shape makes an unpredictable system feel dependable.
- Tradeoff
- The assistant can express less than a language model could, and each new answer type needs design.
How it changed
V1
Assistant answers and acts
The system completed the task it inferred.
User signal
Autonomy reduced trust
Associates wanted to see what would change before it changed.
Final
Propose, preview, confirm
The assistant proposes an action and renders exactly what will change; the person commits.
Constraints we designed around
Business requirement
Actions touch operational records, so reversibility and clear authorship were non-negotiable.
Data availability
Not every system exposed the context the assistant needed, so the design had to degrade to a clarifying question rather than a guess.
How might we
How might we turn an operational question into a completed task in a single exchange?
Where it landed
Task previews
The proposed action shows exactly what will change before it happens.
Contextual grounding
Store, role and shift quietly scope every response.
Recoverable steps
Generated actions can be reversed rather than escalated.
Task preview
Outcome
30%
Increase in AI engagement
What I took from it
Engagement rose when we removed capability. Constraint is what made the assistant feel dependable.
Next project
CVS Health
Making pharmacy experiences easier