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Ulta Beauty AI Adoption Tracker

Last updated: August 18, 2026

3.7 Good

Overview

Ulta Beauty has emerged as one of the most prominent retailers investing heavily in AI across multiple dimensions of its business operations[1]. The company has centralized previously scattered customer data to build unified profiles, enabling AI-powered personalization across channels in near real-time[2]. This comprehensive AI strategy has helped Ulta achieve a remarkable 95% repeat customer rate while cutting marketing costs and improving campaign efficiency[2]. Under the leadership of CEO Kecia Steelman and Chief Technology and Transformation Officer Mike Maresca, Ulta has positioned AI as central to its transformation strategy, viewing it not just as experimental technology but as foundational to delivering personalized beauty experiences at scale[3].

AI Maturity Index

3.7 /5 Practitioner

Evidence high

  • AI deployed across personalization, virtual try-on, data analytics, and supply chain [news]

Missing Evidence

  • Only 2.6% of job postings mention AI, indicating limited workforce AI integration

Evidence high

  • CTO/CIO Mike Maresca and CEO Kecia Steelman position AI as central to transformation [news]

Missing Evidence

  • Low non-tech AI mention rate (2.2%) suggests limited org-wide AI fluency

Evidence high

  • 95% customer repurchase rate attributed to AI personalization [news]
  • 25-30% IT productivity improvement from AI coding tools [news]

Missing Evidence

  • All evidence present

Radar Comparison

Company Sector Avg

Peer Comparison: Ulta Beauty vs consumer-discretionary

Based on 52 companies in sector

Dimension Ulta Beauty Sector Avg Diff
Adoption 4.0 3.5 +0.5
Proficiency 3.0 3.3 -0.3
Impact 4.0 3.5 +0.5
Overall 3.7 3.4 +0.3

AI Hiring Signals

Ulta Beauty Job Postings Analysis

2.6%
AI Mention Rate
116
Jobs Sampled
3
AI-Related Jobs
High Confidence
Data Quality

Tech vs Non-Tech AI Requirements

Tech Roles (Engineering/Data) 4.3%
Non-Tech Roles 2.2%

Top Departments by AI Mention Rate

HR
9.1%
Engineering/Tech
8.3%
Operations
6.3%

Analysis

AI skills appear in very limited roles at Ulta Beauty, with only 2.6% of job postings mentioning AI. While tech roles lead at 4.3%, non-tech roles show minimal AI requirements at 2.2%, suggesting AI adoption is still concentrated in technical functions.

View Sample Job Postings (6 sources)

Key Metrics

95%
Customer Repurchase Rate
Source: https://pymnts.com/news/retail/2025/ulta-beauty-ai-strategy-95percent-customer-repurchase-rate/
25-30%
IT Productivity Improvement
Source: https://fortune.com/2025/04/23/ulta-beauty-ai-it-systems
44.6 million
Loyalty Program Members
Source: https://fortune.com/2025/04/23/ulta-beauty-ai-it-systems
5
AI Initiatives
Source: Larridin Analysis

AI Initiatives

1

Darwin Enterprise Data Warehouse

July 2025

Active

Google BigQuery-powered analytics platform for data-driven decision making

Built on Google BigQuery, Darwin migrated over 300 datasets and developed 50 core enterprise reports, providing real-time dashboards for store managers and business leaders

2

AI-Powered Customer Personalization System

2025

Active

Centralized customer data platform using AI and ML to deliver personalized recommendations across channels

Ulta deployed advanced artificial intelligence and machine learning models to understand customers, predict their likely next actions, and send personalized recommendations that can change in near real-time based on new customer actions

Machine LearningCustomer Experience
3

AI Agents Development Plan

2025

Active

Plans to deploy AI agents for enhanced employee and customer experiences

Ulta is working on deploying agents to associates to help them engage with customers in-the-moment, pulling up past purchases and making product recommendations. The company expects agents to improve marketing and digital store operations

Customer Experience
4

GLAMlab Hair Try-On with Generative AI

December 2024

Active

AI-powered virtual hair styling and color try-on experience using NVIDIA StyleGAN2

Uses NVIDIA's StyleGAN2 generative AI model to show near-instant, realistic previews of hair colors and styles. The tool takes around 5 seconds to compute the first style and about 1 second for subsequent styles

Machine Learning
5

AI-Enhanced Virtual Beauty Advisor

2024

Active

AI-based skincare virtual beauty advisor that provides personalized product recommendations

The virtual beauty advisor asks dynamically generated questions and presents personalized recommendations. Early results show guests using the AI tool for beauty guidance as well as store details, inventory questions, return policies and loyalty information

Customer Experience

Frequently Asked Questions

Ulta centralizes customer data from emails, loyalty programs, in-store interactions and other sources to build unified profiles. AI and ML models analyze this data to predict customer behavior and deliver personalized recommendations that update in near real-time based on new customer actions.

Ulta's GLAMlab features AI-powered virtual try-on experiences including makeup, skin analysis, and hair styling. The newest addition uses NVIDIA's StyleGAN2 to provide realistic hair color and style previews, taking about 5 seconds for the first style and 1 second for subsequent styles.

Through its Prisma Ventures fund, Ulta has invested in multiple AI-focused beauty tech companies including Haut.AI for skin analysis, Myavana for hair analysis, and Adeptmind for e-commerce AI, allowing them to integrate cutting-edge technologies into their platform.

Ulta reports a 95% customer repurchase rate attributed to AI-powered personalization, 25-30% improvement in IT productivity from AI coding tools, and significant cost reductions in marketing campaigns while maintaining effectiveness.

Ulta is developing AI agents to assist store associates with real-time customer engagement, pulling up purchase history and making product recommendations. They also plan agents for supply chain optimization and distribution center operations.

Related Companies

About AI Tracker

AI Tracker is a research project by Larridin, the AI execution intelligence platform.

Methodology: We analyze earnings calls, press releases, partnership announcements, and product documentation. All assessments are based solely on publicly available information—no private customer data is used.

Maturity Scoring: Each dimension is rated on a 4-tier scale (Nascent → Emerging → Scaling → Leading) based on evidence from public sources. Industry averages are computed as the median across all tracked companies in the sector.

Update cadence: Every 2-3 weeks
Last updated: August 18, 2026