forecasting
30 articles about 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.
New Research: Fine-Tuned LLMs Outperform GPT-5 for Probabilistic Supply Chain Forecasting
Researchers introduced an end-to-end framework that fine-tunes large language models (LLMs) to produce calibrated probabilistic forecasts of supply chain disruptions. The model, trained on realized outcomes, significantly outperforms strong baselines like GPT-5 on accuracy, calibration, and precision. This suggests a pathway for creating domain-specific forecasting models that generate actionable, decision-ready signals.
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.
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.
Smarter Shopping: Forecasting the Future of AI Agents in Retail
The Wall Street Journal reports on the emerging role of autonomous AI agents in retail, forecasting their potential to transform shopping by handling complex, multi-step tasks. This signals a shift from passive chatbots to active, goal-oriented assistants.
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.
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.
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.
TimeGS: How Computer Graphics Techniques Are Revolutionizing Time Series Forecasting
Researchers have introduced TimeGS, a novel AI framework that treats time series forecasting as a 2D rendering problem. By adapting Gaussian splatting techniques from computer graphics, the approach achieves state-of-the-art performance while maintaining temporal continuity.
StaTS AI Model Revolutionizes Time Series Forecasting with Adaptive Noise Schedules
Researchers introduce StaTS, a diffusion model that learns adaptive noise schedules and uses frequency guidance for superior time series forecasting. The approach addresses key limitations in existing methods while maintaining efficiency.
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.
AI-Powered Geopolitical Forecasting: How Machine Learning Models Are Predicting Regime Stability
Advanced AI systems are now analyzing political instability with unprecedented accuracy, predicting regime vulnerabilities in real-time. These models process vast datasets to forecast governmental collapse and potential conflict escalation.
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.
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.
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.
AI-2027 Authors Accelerate AGI Timelines, Citing Rapid Progress in Agentic Coding
The AI-2027 forecasting group has accelerated its timeline for when AI could replace human software engineers by 1.5 years, from late 2029 to mid-2028. This revision is based on observed rapid progress in agentic coding systems over the last 3-5 months.
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.
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.
Why Your GPU's Memory Ceiling Predicts Your Cloud Inference Costs
Towards AI explains how GPU VRAM constraints, not compute, dictate LLM inference costs locally and in the cloud. The article details memory math, 2026 hardware shortages, and pricing trends, urging teams to manage context and quantization.
NIQ reports 34% AI-native revenue growth as agentic commerce product nears
NIQ reported 34% AI-native revenue growth as its agentic commerce product nears launch. The move signals agentic AI is maturing in retail data, with NIQ competing against Google and Alipay in this emerging category.
Kohl's and ShipBob Deploy Generative AI in Retail Operations as Global
MarketScale reports Kohl's and ShipBob adopting generative AI for retail operations as ecommerce passes $4 trillion globally. This marks a concrete enterprise shift toward AI-powered logistics and merchandising.
BCG: Agentic AI Can Step-Change CPG–Retail Collaboration by Breaking
Boston Consulting Group (BCG) reports agentic AI can break down 'friction silos' between CPG companies and retailers, enabling step-change collaboration through autonomous planning and execution. The analysis targets the consumer goods value chain, where fragmented data and manual handoffs currently limit joint efficiency.
Instacart Acquires Arpalus to Put Computer Vision at the Core of AI-Driven
Instacart acquired Arpalus to integrate computer vision into grocery retail, aiming to improve inventory management and store operations. MarketScale reports the move signals a broader industry trend toward AI-driven retail efficiency.
Epoch AI Opens FrontierMath's Unsolved Problems to Public Scrutiny After 2 Years
Epoch AI opened FrontierMath's unsolved problems to public scrutiny after two years, aiming to verify AI claims. The benchmark includes 1,000+ original math problems, with transparency seen as a step against benchmark gaming.
Advance Auto Parts leans on loyalty program and AI to drive digital growth
Advance Auto Parts uses a new loyalty program and AI tools for pricing and assortment to boost online engagement and repeat purchases. This matters as auto parts retailers compete in digital commerce.
Instacart Acquires Computer Vision Firm Arpalus for Real-Time Grocery
Instacart acquired computer vision firm Arpalus to add real-time shelf intelligence for grocery retailers. The technology automates inventory monitoring, product placement, and pricing verification.
AI now at top of agenda for more luxury houses: Bain report
Bain & Company reports that AI is now a top priority for an increasing number of luxury houses, signaling a major strategic shift. This matters as luxury brands move to integrate AI for personalization, operations, and customer experience.
Stifel Upgrades Shopify to Buy
Stifel upgrades Shopify to Buy, highlighting agentic commerce as a key growth driver. The move signals growing investor belief that AI agents will transform e-commerce operations, from inventory to customer engagement.
Dassault Systèmes expands AI PLM to LVMH, Carrefour and Walmart
Dassault Systèmes is expanding its AI-powered PLM to LVMH, Carrefour, and Walmart. This marks a major enterprise AI deployment in retail and luxury, embedding intelligence into product design, supply chain, and personalization.
Generative AI Usage Trends & Statistics Report by eMarketer
eMarketer's report reveals enterprise GenAI adoption hit 62%, with retail at 38%. Barriers include privacy and integration, but use cases like personalized marketing and inventory management are emerging.