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demand forecasting

30 articles about demand forecasting in AI news

Impact Analytics Wins 'Demand Forecasting Solution of the Year' for Second

Impact Analytics secured the 2026 'Demand Forecasting Solution of the Year' award from SupplyTech Breakthrough, marking its second straight win. The recognition highlights AI's growing role in retail inventory and pricing optimization.

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How AI is Impacting Five Demand Forecasting Roles in Retail

AI is transforming demand forecasting, shifting roles from manual data processing to strategic analysis. The article identifies five key positions being reshaped, highlighting a move towards higher-value, AI-augmented work.

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Beyond Simple Predictions: How Frequency Domain AI Transforms Retail Demand Forecasting

New FreST Loss AI technique analyzes retail data in joint spatio-temporal frequency domain, capturing complex dependencies between stores, products, and time for superior demand forecasting accuracy.

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Google Open-Sources TimesFM: A 100B-Point Time Series Foundation Model for Zero-Shot Forecasting

Google has open-sourced TimesFM, a foundation model for time series forecasting trained on 100 billion real-world time points. It requires no dataset-specific training and can generate predictions instantly for domains like traffic, weather, and demand.

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New Research Identifies Data Quality as Key Bottleneck in Multimodal Forecasting

A new arXiv paper introduces CAF-7M, a 7-million-sample dataset for context-aided forecasting. The research shows that poor context quality, not model architecture, has limited multimodal forecasting performance. This has implications for retail demand prediction that combines numerical data with text or image context.

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New Research: How Online Marketplaces Can Use Demand Allocation to Control Seller Inventory

Researchers propose a model where a marketplace platform, by controlling the timing and predictability of order allocation to sellers, can influence their safety-stock inventory and their choice to use platform fulfillment services. This identifies demand allocation as a key operational lever for digital marketplaces.

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TimeSqueeze: A New Method for Dynamic Patching in Time Series Forecasting

Researchers introduce TimeSqueeze, a dynamic patching mechanism for Transformer-based time series models. It adaptively segments sequences based on signal complexity, achieving up to 20x faster convergence and 8x higher data efficiency. This addresses a core trade-off between accuracy and computational cost in long-horizon forecasting.

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Shein's Xcelerator Program: Opening Its On-Demand Supply Chain to Competing Brands

Shein is offering smaller labels access to its proprietary on-demand manufacturing and global logistics network through its 'Xcelerator' program. This creates a strategic dilemma for brands: gain speed and scale, but potentially empower a formidable competitor.

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Google's TimesFM Foundation Model: A New Paradigm for Time Series Forecasting

Google Research has open-sourced TimesFM, a 200 million parameter foundation model for time series forecasting. Trained on 100 billion real-world time points, it demonstrates remarkable zero-shot forecasting capabilities across diverse domains without task-specific training.

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Microsoft, Google Shift to Range-Based AI Capacity Planning at DC World 2026

At Data Center World 2026, Microsoft and Google revealed they've shifted from point forecasts to range-based planning for AI workloads, with weekly reviews and modular infrastructure to absorb demand volatility.

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OpenAI Forecasts $121B in AI Hardware Costs for 2028

OpenAI is forecasting its own AI research hardware costs will reach $121 billion in 2028, according to a WSJ report. This figure highlights the extreme capital intensity required to compete at the frontier of AI.

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Kronos AI Outperforms Leading Time Series Models by 93% on Candlestick Data

Researchers from Tsinghua University released Kronos, an open-source foundation model trained on 12 billion candlestick records from 45 exchanges. It reportedly achieves 93% higher accuracy than leading time series models for price and volatility forecasting, requiring no fine-tuning.

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Google's TimesFM: 200M-Param Foundation Model for Zero-Shot Time Series

Google released TimesFM, a 200M-parameter foundation model for time series forecasting that works without training on user data. It's now available open-source and as a product inside BigQuery.

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Beyond Blue Books: How Real-Time Market Intelligence AI is Transforming Luxury Asset Valuation

duPont REGISTRY Group's deployment of real-time AI analytics for luxury vehicles demonstrates a scalable model for dynamic pricing, authentication, and market forecasting of high-value collectibles. This approach directly translates to luxury retail for limited editions, vintage items, and exclusive collections.

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Google's TimesFM: The Zero-Shot Time Series Model That Works Without Training

Google has open-sourced TimesFM, a foundation model for time series forecasting that requires no training on specific datasets. Unlike traditional models, it can make predictions directly from historical data, potentially revolutionizing forecasting across industries.

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Albertsons Launches AI Supply Chain Tool With Computer Vision

Albertsons launched a patent-pending AI supply chain tool using computer vision to reduce food waste and improve inventory across 2,200+ stores.

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Amazon Now Expands 30-Minute Delivery to 8 More US Cities

Amazon expands Amazon Now 30-minute delivery to 8 new cities, targeting tens of millions by end of 2026. Prime members pay $3.99 per order.

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Grocery Dive Asks: Is Agentic AI the Next Frontier for Grocers?

The article examines agentic AI's potential for grocers in inventory, personalization, and store operations, weighing benefits against implementation challenges like data integration and safety.

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Why Production AI Needs More Than Benchmark Scores

The article argues that high benchmark scores are insufficient for production AI success, highlighting the need for robust MLOps practices, monitoring, and real-world testing—critical for retail applications.

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Castore and GXO Detail 'Sustainable Scale' Strategy at Drapers Supply

At the Drapers Supply Chain Summit, Castore CSCO Adrian Harris detailed how the rapid-growth sportswear brand is shifting focus from breakneck expansion to 'sustainable scale' with logistics partner GXO. The partnership is central to operationalizing sustainability in Castore's supply chain.

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Guerlain Launches First Paid Influencer Campaign After Viral TikTok

Guerlain reports the Vanille Planifolia extrait became its #1 best-selling product for five months after organic TikTok videos, leading to the brand’s first paid influencer campaign. Sales tripled despite the $660 price, and the fragrance sold out multiple times.

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Why AI and luxury retail go hand-in-hand — The Drum article explores the synergy

A new article from The Drum examines how artificial intelligence can enhance luxury retail experiences without diluting brand prestige. The exact arguments and examples are not accessible from the snippet.

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Chief AI & Technology Officer Role Gains Traction in Luxury Sector

The luxury sector is formalizing AI leadership by establishing Chief AI and Technology Officer positions. This move reflects the industry's transition from ad-hoc AI initiatives to integrated, strategic technology governance at the highest level.

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AI Turned Thrift Into a Profitable Fashion Machine

The article details how AI technologies are being deployed in the thrift and resale fashion industry to automate critical operations like pricing, authentication, and inventory management, turning a traditionally labor-intensive sector into a scalable, data-driven profit engine.

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Airbnb's Engineering Blueprint for a Petabyte-Scale

Airbnb engineers detail the construction of a massive, internally operated metrics storage system. The system ingests 50 million samples per second, manages 1.3 billion active time series, and stores 2.5 petabytes of data, overcoming challenges in tenancy, shuffle sharding, and observability at scale.

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Mind Games Fragrance Achieves 56% Growth Without a Hero SKU

Mind Games, a chess-inspired luxury fragrance brand, achieved $28.9M in 2025 US sales with 56% YoY growth despite having no dominant hero SKU. 65% of sales come from 14 different scents, targeting young male collectors. The brand is projecting $120M in global retail sales for 2026.

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Forbes Reports on Luxury Brands' Quiet AI Adoption

A Forbes article examines the strategic, often non-public, integration of AI by luxury brands. The focus is on practical applications in customer experience, operations, and design, marking a shift from experimentation to embedded utility.

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Redis Launches 'Redis Feature Form,' an Enterprise Feature Store for

Redis announced the launch of Redis Feature Form, a new enterprise feature store designed to manage and serve machine learning features in production. This move positions Redis to compete in the critical MLOps infrastructure layer, helping companies operationalize AI models more reliably.

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Logile to Showcase AI-Powered Connected Store Operations at Retail

Logile, a provider of AI-powered workforce solutions, announced its participation in Retail Technology Show 2026. The company will showcase its Connected Store Operations platform, emphasizing the industry trend toward integrating labor planning, task management, and store execution.

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The Graveyard of Models: Why 87% of ML Models Never Reach Production

An investigation into the 'silent epidemic' of ML model failure finds that 87% of models never make it to production, despite significant investment in development. This represents a massive waste of resources and talent across industries.

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