Case Study 03

AI Across the Entire Delivery Cycle

Enterprise AI Operating Model · Lowe's

A 30-person UX organization was absorbing a structural failure the company kept reading as a design problem. I rebuilt how work entered the system — and turned volatile delivery into a measurable, durable operation.

Organization

Lowe's Companies, Inc.

Fortune 50 Retail

Role

Senior UX Manager

UX · Research · Content

Scope

3 disciplines

One governed model

Adoption

Under 60 days

Enterprise-wide

The Mandate

A mandate without a model is pressure without direction.

Leadership issued a company-wide AI adoption mandate to stay competitive. Tools were provided but no playbook, no use cases, and no implementation direction came with them.

The real exposure wasn’t that the team wouldn’t use AI. It’s that they already were  informally, inconsistently, and without any review. Leadership issued the mandate. I built the model.

No playbook

Tools with no direction

Ungoverned

Informal use already started

No standards

Prompt quality varied widely

No gates

Unvalidated outputs in the cycle

Skeptical

Three disciplines, low trust

Exposed

Risk without a measurable return

The Diagnosis

Governance first. Speed second.

I built the governance before I built the workflows. Ungoverned AI at enterprise scale isn’t innovation, it’s risk without a return. One validated path ran across all three disciplines, with a mandatory human review gate no output could skip.

The Validated Path

Two competing explanations surfaced early. Some believed it was design capability; others believed it was insufficient Product engagement. The data showed symptoms of both but neither explained the pattern.

Only vetted material enters; shared prompt frameworks replace ad hoc requests; synthesis, drafts, and wireframes are generated; a mandatory human gate is the guardrail; and only then does the output re-enter the delivery cycle.

The Intervention

3 structural moves.

Research

From trapped insight to a living repository

Before: 2 researchers for 15+ products. Manual transcript review. Reports in 5–7 days. Insights trapped in personal files. After: structured-prompt synthesis with lead-researcher validation. Reports in 2–3 days. A repository organized by product line.

Content

A custom GPT trained on brand voice

Before: copywriting built manually from scratch. Content designers owned full production of every piece. After: a custom GPT trained on brand voice and UX-content standards. Immediate adoption. Capacity freed for competitive audits.

Design

Sketch-to-wireframe, with a human gate

Before: sketches manually recreated as wireframes. Discovery cycles of 3-5 days. 2-3 alignment rounds before sign-off. 

After: a sketch-to-wireframe pipeline. Iteration compressed to ~2 days. Alignment rounds down to one. No final UI without human review.

The Result

More rigorous work, in less time, with less rework.

Research Report turnaround

5–7 days → 2–3 days

Sprint commitment accuracy

3–5 days → ~2 days

Alignment rounds to sign-off

2–3→ 1

Full adoption across 3 disciplines

→ <60 days

Source: research workflow tracking; sprint analytics; alignment session logs · Lowe’s, 2022–2024

In one tracked sprint, a senior designer delivered three validated prototype options in a single day — compressing a 3–5 day cycle and letting Product decide that sprint, not the next.

Leadership in Action

Building the bridge between speed and integrity.

Built structure before anyone asked for it.

The mandate came with tools and no direction. I designed the governance model first, then built the workflows around it.

Created use cases where none existed.

The team was skeptical because they had no examples. I built the review checkpoints, and repository standards then showed them what responsible AI looked like in practice.

Made adoption safe, so it became easy.

Three resistant disciplines became structured daily adopters within 60 days. The result wasn't compliance, it was capability.

AI accelerates thinking. Governance protects integrity. Leadership builds the bridge between them.