AI TraceTrace Foundation, Inc.
Confirmed AI Use
Last verified April 22, 2026·18 sources cited·Reviewed and published by 1 editor·View edit history

AI Usage at a Glance

2Recommendation
1Creative Gen
1Customer Svc
3Data Analysis
1Productivity

Timeline

Mar 26, 2018

Recommendation

Practice documented: Nike uses an AI-powered product recommendation system across its website and apps that analyzes each shopper's browsing history, past purchases, fitness activity, and personal preferences to suggest relevant products in real time. This system operates continuously for users of Nike's digital platforms.

Practice DocumentedView practice →

Mar 26, 2018

Data Analysis

Practice documented: Nike uses a predictive analytics platform, built on technology from its 2018 acquisition of Zodiac, to forecast the future spending behavior and long-term value of individual customers. This system helps Nike decide which customers to target, when, and with what offers.

Practice DocumentedView practice →

May 9, 2019

Recommendation

Practice documented: Nike deployed Nike Fit, an AI-powered foot-scanning feature built into the Nike App, starting in July 2019. The tool uses a smartphone camera to scan a customer's feet and recommends the best-fitting shoe size for each Nike model.

Practice DocumentedView practice →

May 14, 2019

Data Analysis

New evidence: How Nike is boosting its direct-to-consumer business with tech acquisitions

Evidence AddedView practice →

May 14, 2019

Recommendation

New evidence: How Nike is boosting its direct-to-consumer business with tech acquisitions

Evidence AddedView practice →

Dec 9, 2019

Data Analysis

Practice documented: Nike uses an AI-powered demand forecasting system, built on technology from its 2019 acquisition of Celect, to predict which products shoppers will want, in which locations, and at what times. This system helps Nike decide where to position inventory across its global network to reduce waste and improve fulfillment speed.

Practice DocumentedView practice →

Sep 23, 2020

Data Analysis

New evidence: Predictive analytics determine what's in stock at Nike's new Los Angeles warehouse

Evidence AddedView practice →

May 7, 2024

Creative Gen

Practice documented: Nike used generative AI tools in its Athlete Imagined Revolution (A.I.R.) project to create hundreds of concept shoe designs for 13 elite athletes, which were showcased at an exhibition in Paris in April 2024 and again at the 2024 Olympics. Human designers then refined the AI-generated visuals into final prototypes.

Practice DocumentedView practice →

Jul 23, 2024

Creative Gen

New evidence: Creating the Unreal: How Nike Made Its Wildest Air Footwear Yet

Evidence AddedView practice →

Jul 25, 2024

Creative Gen

New evidence: Generative AI helps Nike create custom dream shoes for athletes

Evidence AddedView practice →

Jul 18, 2025

Data Analysis

Practice documented: Nike uses AI-powered sentiment analysis to process customer feedback from social media, review platforms, and direct communication channels, using the results to inform product development and personalized customer service strategies.

Practice DocumentedView practice →

Jul 25, 2025

Customer Svc

Practice documented: Nike deployed NikeAI Beta, a conversational AI shopping assistant, to all iOS Nike App users in the United States in August 2025. The tool lets shoppers describe what they need in plain language — like 'running shoes for a race' or 'gear in my favorite color' — and it returns personalized product matches.

Practice DocumentedView practice →

Aug 4, 2025

Customer Svc

New evidence: NikeAI's beta release comes with lessons for CTOs

Evidence AddedView practice →

Aug 4, 2025

Productivity

Practice documented: Nike deployed two internal AI tools — AgentAutosys and Genius Results — to automate repetitive IT support tasks for its technology operations teams. These tools handle thousands of routine tasks, from detecting and resolving system failures to answering employee IT questions, without human intervention.

Practice DocumentedView practice →

Aug 18, 2025

Recommendation

New evidence: Nike's Martech in 2025: Unified CDP, AI-Driven Personalisation & Composable Stack Strategy

Evidence AddedView practice →

Oct 9, 2025

Customer Svc

New evidence: Ecommerce Trends: How Nike is using AI

Evidence AddedView practice →

Oct 9, 2025

Recommendation

New evidence: Ecommerce Trends: How Nike is using AI

Evidence AddedView practice →

Recent activity

Recommendation SystemVerified

Nike uses an AI-powered product recommendation system across its website and apps that analyzes each shopper's browsing history, past purchases, fitness activity, and personal preferences to suggest relevant products in real time. This system operates continuously for users of Nike's digital platforms.

Nike's recommendation engine draws on data collected across its app ecosystem — including the Nike App, SNKRS, Nike Training Club, and Nike Run Club — and uses machine learning to build individual customer profiles. These profiles incorporate browsing patterns, purchase history, size data from Nike Fit, and fitness behavior. The AI input is aggregated customer behavioral and transactional data; the output is a personalized feed of product suggestions and marketing messages. Nike's VP of Marketing Data confirmed the company built 'a unified customer data platform with underlying ML/AI models that power everything from our journey orchestration to how we personalise digital experiences.' The Zodiac acquisition (2018) added customer lifetime value prediction to inform which customers to target and when.

Nike AppNike.comSNKRS AppNike Training ClubNike Run Club
3 sources · Digital Commerce 360 · Oct 9, 2025Read full entry →
Creative GenerationVerified

Nike used generative AI tools in its Athlete Imagined Revolution (A.I.R.) project to create hundreds of concept shoe designs for 13 elite athletes, which were showcased at an exhibition in Paris in April 2024 and again at the 2024 Olympics. Human designers then refined the AI-generated visuals into final prototypes.

Nike design teams interviewed athletes about their preferences and personalities, then submitted detailed prompts to generative AI models to produce hundreds of visual concepts. These AI images served as 'inspiration points'; human designers then narrowed them down and used 3D printing and computational design to build the final prototypes. The AI input was text prompts based on athlete feedback; the output was visual concept images. Nike has not publicly disclosed which specific generative AI tools were used. The project was described by Nike's own newsroom as a 'co-creation process' and is not a commercially available product for consumers.

Nike A.I.R. (Athlete Imagined Revolution)Nike On Air exhibition
3 sources · Axios · Jul 25, 2024Read full entry →
Customer Service

Nike deployed NikeAI Beta, a conversational AI shopping assistant, to all iOS Nike App users in the United States in August 2025. The tool lets shoppers describe what they need in plain language — like 'running shoes for a race' or 'gear in my favorite color' — and it returns personalized product matches.

NikeAI Beta uses large language models fine-tuned on Nike's product catalog and consumer data to interpret shopping intent expressed in natural language, then recommends matching products. Nike CTO Dr. Muge Erdirik Dogan described it as built using 'best-in-class foundational models' and fine-tuned by domain experts. The tool takes conversational user queries as input and produces product recommendations as output. It was confirmed as a beta product, meaning its long-term general availability status is not yet determined.

Nike App (iOS)
3 sources · Digital Commerce 360 · Oct 9, 2025Read full entry →

All practices by category

8 practices

Cite this record

Trace Foundation. (2026). Nike: documented AI practices (data as of 2026-04-22) [Data set record]. AI Trace. https://www.aitrace.org/r/company/358bd0d1-3e3e-4ce6-ba51-a0d67ec26ded. Accessed September 7, 2026.

Stable link
https://www.aitrace.org/r/company/358bd0d1-3e3e-4ce6-ba51-a0d67ec26ded
Data as of
April 22, 2026
Last verified
April 22, 2026

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