AI in USE #43 ✨: Precision at Scale
🔍 From personalized coaching to smart sourcing and industrial AI, this issue explores how AI delivers tailored insights and operational scale across sectors.
Welcome to the latest edition of AI in USE, where we bring you the most compelling examples of artificial intelligence transforming industries. This week, we spotlight how AI is powering performance, accelerating talent sourcing, and navigating the complexities of global logistics 🌐⚡
Here’s what’s inside:
💪 WHOOP Coach – Real-time biometrics meet GPT-4 for next-level health and performance coaching.
🤖 Malt’s AI Search – Revolutionizing freelance hiring with intelligent, context-aware talent matching.
🚗 Renault’s AI@SCALE – Tackling the challenge of industrializing AI across a global supply chain.
🏃♀️ WHOOP – Human Performance Optimization
Organization Type: Scale-up
AI Purpose: Augment
Type of AI Model: Generative AI, Supervised learning
AI Application Type: User experience
Targeted Industry: Healthcare, Well-being, Sport, Consumer electronics
Target Group (AI User): Consumers
Use Case Description:
WHOOP transforms continuous biometric data from wearables into actionable insights using artificial intelligence. It combines supervised learning for interpreting raw physiological signals (heart rate, HRV, SpO₂, sleep, etc.) and generative AI via GPT-4 for real-time, personalized coaching. The opportunity addressed is the growing need for proactive health and performance management tools that go beyond step counts or calorie tracking. By integrating AI into the user experience, WHOOP supports high performers, health-conscious individuals, and corporate wellness programs with predictive health alerts, tailored training advice, and recovery optimization — all grounded in real-time data.
Key Features:
• WHOOP Coach (GPT-4): Personalized, conversational health and fitness advice based on your actual biometric data — including recovery score, sleep quality, training load, and more.
Daily Performance Summary ("Outlook"): Provides a morning snapshot of key metrics.
Proactive Coaching Alerts: Sends real-time suggestions
Stress Monitoring: Uses HRV and RHR to detect stress levels and offers guided breathwork exercises to respond.
Continuous Tracking: Monitors heart rate, HRV, respiratory rate, skin temperature, SpO₂, and sleep stages 24/7.
AI-Powered Personalization in Marketing: Delivers hyper-targeted content and engagement strategies to improve user retention.
Results:
Behavioral Impact: Users report improved sleep, training consistency, and stress regulation.
Scientific Validation: AI sleep and recovery models backed by peer-reviewed studies.
Market Validation: $3.6B valuation, backed by SoftBank and high-profile athletes like Ronaldo, Durant, and Mahomes.
Launch Date: 2021 for main AI features, 2023 for Generative AI features
Retrieve the case and more (including their sources) on the AI in USE website
👩🏻💻 Malt – AI Matching
Organisation Type: Scale up
AI Purpose: Automate
Type of AI Model: Generative AI
AI Application Type: Customer care, Sales & Marketing, Operations, User experience
Targeted Industry: Multi-industry, Tech
Target Group (AI User): Recruiters, Developers, Project managers
Use Case Description:
In November 2024, Malt launched AI Search, a flagship feature designed to revolutionize how companies find and engage freelance talent. Moving beyond traditional keyword-based search, AI Search leverages custom neural retrieval models and semantic search to deeply understand the context of a project brief.
The tool acts as an intelligent “sourcing assistant”:
It analyzes the project context, not just keywords.
It automatically generates project briefs.
It produces skill-based shortlists of freelancers.
It proactively recommends additional profiles that may fit the role.
A central innovation enabled by AI Search is the creation of “Superteams”—hybrid teams that combine internal staff with external freelance talent, accelerating execution while maintaining strategic alignment.
Key Features:
Context-aware semantic search using neural models
Shortlist generation tailored to skills and project context
Automated project brief drafting
Dynamic profile suggestions
“Superteam” assembly functionality (internal + freelance talent)
Results:
Freelancer search time reduced from days to seconds
Wider and more accurate talent discovery
Adoption by top-tier clients like Schneider Electric, L’Oréal, and Accor
Supports strategic agility and scalability for talent sourcing and team building
Launch Date: November 2024
Retrieve the case and more (including their sources) on the AI in USE website
🚙 Industrializing AI Across the Renault Global Supply Chain
Organization Type: Corporate
AI Purpose: Predict
Type of AI Model: Supervised learning, Generative AI
AI Application Type: Operations
Targeted Industry: Automative
Target Group (AI User): Supply chain managers
Use Case Description:
Renault’s AI@SCALE initiative is a strategic platform launched in early 2024 to industrialize AI deployment across its global supply chain operations. The goal is to shift from scattered, one-off AI tools to an integrated, scalable platform using supervised machine learning, optimization techniques, and generative AI. The platform identifies high-impact opportunities (e.g. demand prediction, truck routing, supplier risk analysis) and executes them faster using modular tools built on Dataiku. It addresses the need for supply chain resilience, real-time visibility, and cost reduction in a highly volatile post-COVID and EV-transition context.
Key Features:
Built on Dataiku’s enterprise AI platform
25 high-impact AI projects across logistics and sourcing
End-to-end data integration and orchestration
Predictive alerts and real-time simulation
Results:
€45 million expected value generated across supply chain
€10 million delivered in early pilots (Q1–Q2 2024)
Improved forecast accuracy and disruption response time
Launch Date: January 2024
Retrieve the case and more (including their sources) on the AI in USE website
Thank you for being part of the AI in USE community! 🌟
🔗 Visit our website AI in USE to explore the full library of AI use cases and discover how AI is transforming industries across the globe:
✨ We hope these AI use cases spark inspiration!
💬 Let us know which one intrigued you the most—your feedback helps us grow!
Disclaimer: This content was (obviously 😉) built with the assistance of AI.