kering
30 articles about kering in AI news
Kering's 80% Opportunity: A Strategic Pivot from Operational AI to Brand Meaning
Kering CEO Luca de Meo frames luxury as a €350B market where Kering only plays in 20%. The article argues that Gucci's decade-long growth has been erased and Balenciaga hasn't recovered from its 2022 scandal because both lost their core brand meaning. De Meo's strategy—proven at Renault—is to define meaning first, then execute operationally.
Kering Shake-Up Reaches Jeweller DoDo as CEO Exits
The Business of Fashion reports that Kering's internal shake-up has extended to its jewellery subsidiary DoDo, resulting in the exit of its CEO. This indicates the luxury conglomerate's restructuring efforts are intensifying across its brand portfolio.
Kering Appoints Pierre Houlès as Chief Digital and AI Officer to Build AI-Enabled Digital Model
Kering has hired Pierre Houlès as its first Chief Digital and AI Officer, tasked with building a unified digital model powered by AI. This signals a major strategic shift to centralize and accelerate digital and AI capabilities across its luxury houses.
Kering Appoints Former Renault Executive Pierre Houlès as Chief Digital, AI and IT Officer
Kering has hired Pierre Houlès, a former Renault executive, as its new Director of Digital, Artificial Intelligence, and Technology. This signals a strategic push to accelerate digital transformation and AI adoption across the luxury group.
Bentley's 'Phygital' Future
Bentley Motors is pioneering a 'phygital' design approach, merging physical and digital processes. The automaker is deploying real-time 3D visualization and AI-assisted tools to enable faster, more collaborative, and data-informed design decisions for its luxury vehicles.
AI Reshapes Luxury Travel—But Human Expertise Remains Essential
A new report highlights how AI is being integrated into luxury travel for personalized itineraries, predictive service, and backend operations. However, the consensus is that AI should augment, not replace, the human expertise and emotional intelligence that define true luxury service.
HARPO: A New Agentic Framework for Conversational Recommendation Aims to
A new research paper introduces HARPO, a hierarchical agentic reasoning framework for conversational recommender systems. It reframes recommendation as a structured decision-making process, directly optimizing for interpretable quality dimensions like relevance, diversity, and predicted satisfaction. The approach shows consistent improvements on recommendation-centric metrics across three datasets.
Agentic AI in Retail: Experts Warn Against Shifting Liability to Consumers
Industry experts warn that the rush to implement agentic AI in retail carries significant risk. If brands attempt to shift liability for AI mistakes onto customers, they could erode hard-won consumer trust and face increased regulatory scrutiny.
Verizon Hospitality Leader Discusses AI's Role in Eliminating Phantom Inventory
A Verizon hospitality leader shared insights on using AI and IoT technologies to tackle phantom inventory—discrepancies between digital stock records and actual physical stock. This is a pervasive and costly issue in retail, directly impacting sales and operations.
BoF Launches 'The Fashion Marketer's Guide to AI' Masterclass
The Business of Fashion (BoF) has announced a new professional masterclass titled 'The Fashion Marketer's Guide to AI.' This indicates a formalized educational push to equip fashion industry professionals with actionable AI knowledge.
When Craft Meets Code: How Luxury Brands Are Drawing the Line on AI
A new report details how luxury houses are implementing AI in back-end and client-facing roles but are establishing clear boundaries to safeguard the human artistry and heritage that define their value.
Ensembles at Any Cost? New Research Quantifies Accuracy-Energy Trade-offs
A comprehensive study of 93 experiments across four datasets reveals the severe energy inefficiency of ensemble methods in recommender systems. While accuracy improves slightly, energy consumption and CO2 emissions can increase by orders of magnitude, forcing a critical cost-benefit analysis for production systems.
ReRec: A New Reinforcement Fine-Tuning Framework for Complex LLM-Based
A new paper introduces ReRec, a reinforcement fine-tuning framework designed to enhance LLMs' reasoning capabilities for complex recommendation tasks. It uses specialized reward shaping and curriculum learning to improve performance while preserving the model's general abilities. This addresses a key weakness in using off-the-shelf LLMs for sophisticated personalization.
CoDiS: A Causal Framework for Cross-Domain Sequential Recommendation
A new arXiv paper introduces CoDiS, a framework for Cross-Domain Sequential Recommendation that uses causal inference to disentangle domain-shared and domain-specific user preferences while addressing context confounding and gradient conflicts. It outperforms state-of-the-art baselines on three real-world datasets.
Coresight Research Report: Technology and Resilience as Path to Stronger Retail Margins
Coresight Research has published a report titled 'Supply Chain Insights for Food, Drug and Mass Retail: Technology, Resilience and the Path to Stronger Margins.' The research focuses on how strategic tech adoption can fortify operations and profitability in key retail segments.
Google Ads Details Its Data Infrastructure for AI-Powered Commerce
Google Ads has detailed the critical role of its underlying product data infrastructure in enabling 'agentic commerce'—where AI agents assist shoppers. This foundation is key to making search more natural and understanding shopper intent.
RLSD Unifies Self-Distillation & Verifiable Rewards to Fix RL Leakage
Researchers propose RLSD, a method merging on-policy self-distillation with verifiable rewards to fix information leakage and training instability in language model reinforcement learning.
Loop Tests AI Agent to Streamline Store Operations
Loop is trialing an AI agent focused on store operations automation. This represents a direct move to apply autonomous AI systems to the complex, physical environment of retail stores, aiming to improve efficiency.
Production RAG: From Anti-Patterns to Platform Engineering
The article details common RAG anti-patterns like vector-only retrieval and hardcoded prompts, then presents a five-pillar framework for production-grade systems, emphasizing governance, hardened microservices, intelligent retrieval, and continuous evaluation.
Boll & Branch Deploys OpenClaw AI Agent 'Tess' Across Operations, From Scheduling to Customer Insights
Bedding brand Boll & Branch created an AI agent named 'Tess' using open-source platform OpenClaw. Initially a scheduling assistant, Tess now integrates with Slack, Shopify, and marketing tools to generate customer reports and analyze social trends, supporting the brand's physical retail expansion.
How Personalized Recommendation Engines Drive Engagement in OTT Platforms
A technical blog post on Medium emphasizes the critical role of personalized recommendation engines in Over-The-Top (OTT) media platforms, citing that most viewer engagement is driven by algorithmic suggestions rather than active search. This reinforces the foundational importance of recommendation systems in digital content consumption.
Zero-Shot Cross-Domain Knowledge Distillation: A YouTube-to-Music Case Study
Google researchers detail a case study transferring knowledge from YouTube's massive video recommender to a smaller music app, using zero-shot cross-domain distillation to boost ranking models without training a dedicated teacher. This offers a practical blueprint for improving low-traffic AI systems.
When to Prompt, RAG, or Fine-Tune: A Practical Decision Framework for LLM Customization
A technical guide published on Medium provides a clear decision framework for choosing between prompt engineering, Retrieval-Augmented Generation (RAG), and fine-tuning when customizing LLMs for specific applications. This addresses a common practical challenge in enterprise AI deployment.
MemoryCD: New Benchmark Tests LLM Agents on Real-World, Lifelong User Memory for Personalization
Researchers introduce MemoryCD, the first large-scale benchmark for evaluating LLM agents' long-context memory using real Amazon user data across 12 domains. It reveals current methods are far from satisfactory for lifelong personalization.
Netflix Study Quantifies the True Value of Personalized Recommendations
A new study using Netflix data finds its personalized recommender system drives 4-12% more engagement than simpler algorithms. The research reveals that effective targeting, not just exposure, is key, with mid-popularity titles benefiting most.
The Business of Fashion Poses the Question: Should Luxury Stop Worrying and Learn to Love AI Imagery?
The Business of Fashion directly addresses the luxury sector's central dilemma regarding AI-generated imagery, framing it as a strategic question of adoption versus caution. This signals a critical inflection point for brand identity and creative production.
Federated RAG: A New Architecture for Secure, Multi-Silo Knowledge Retrieval
Researchers propose a secure Federated Retrieval-Augmented Generation (RAG) system using Flower and confidential compute. It enables LLMs to query knowledge across private data silos without centralizing sensitive documents, addressing a major barrier for enterprise AI.
Fractal Emphasizes LLM Inference Efficiency as Generative AI Moves to Production
AI consultancy Fractal highlights the critical shift from generative AI experimentation to production deployment, where inference efficiency—cost, latency, and scalability—becomes the primary business constraint. This marks a maturation phase where operational metrics trump model novelty.
Is AI Antithetical to Luxury? The Business of Fashion Poses the Core Question
The Business of Fashion examines the fundamental tension between AI's scalability and luxury's exclusivity. This is a strategic, not technical, debate for luxury houses deciding how to adopt AI without diluting brand value.
AWS Launches 'The Luggage Lab': A Generative AI Framework for Physical Product Innovation
Amazon Web Services has introduced 'The Luggage Lab,' a new reference architecture and framework using its generative AI services to accelerate the design and development of physical products. This is a direct, vendor-specific playbook for applying GenAI to tangible goods.