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Alain Matar and SupChains collaborate on a planner-facing forecasting application

Flowlity Introduces Forecast Studio to Make AI Demand Forecasts More Transparent

Blue Yonder 2026.2 expands planning with forecast transparency, financial impact simulation and inventory agents

Slimstock brings next-generation AI planning focus to SAPICS 2026

Infor and AWS expand their collaboration to accelerate generative AI adoption

Lyric named an Example Vendor in Gartner’s 2026 Supply Chain Analytics and Decision-Making market overview

Intuiflow Integrates SKU Science Demand Planning into Its Planning Platform

Interim S&OP Consultant — London

EVENT: IBF Examines AI Proof of Value in Forecasting and Demand Planning

EVENT: IBF workshop tests AI proof of value for forecasting and demand planning

EVENT: Advanced demand-planning and forecasting programme opens

EVENT: Sunstice to host webinar on touchless demand planning and Agentic AI

EVENT: ISF 2026 brings forecasting research and practice together in Montreal

EVENT: Board explores outside-in signals for continuous enterprise planning

Forecast Value Added Turns Planner Overrides into a Measurable Governance Process

AI agents should enrich forecasts only with information the model cannot see

Amazon moves demand forecasting from specialized models toward a reusable forecasting foundation model

Forecast overrides are a governance problem, not only a forecasting problem

Forecast variability: when human enrichment destabilizes planning

Forecast accuracy is an input to the decision—not the business outcome

Manufacturing Forecasting Needs More Than a Better Algorithm

AI is changing demand planning unevenly, not universally

Is MAPE Still the Right Forecast Accuracy Metric for Demand Planning?

Why cumulative and lag-one forecasts matter for inventory decisions

Machine-learning forecasting with promotions, prices, sell-outs and inventory

AI adoption metrics are meaningless without a decision-quality metric

Machine learning is changing demand planning, but humans still matter

Five demand-forecasting mistakes supply-chain leaders are rethinking

Why Flat Forecasts Can Outperform More Plausible-Looking Plans

Forecasts Predict Demand; Demand Plans Translate It Into Action

Demand Forecasting in an Era of Disruption: What Actually Works

Evaluating agentic AI for demand forecasting requires more than forecast accuracy

Planning productivity claims double-count the same planner minute

Agile planning platforms need decision architecture, not only AI features

Modern Demand Planning Requires Model Selection, External Signals and Governance

Arnaud Morvan and Damien Portmann map practical Supply Chain use cases for AI agents

Self-steering supply chains are arriving before companies have defined who owns the decision

o9, Kinaxis, OMP and Anaplan: Four Different Visions for AI-Driven Supply Chain Planning

Graph context can improve predictive analytics in supply-chain planning

From Bots to Agentic Supply Chains: Why the Next Competitive Advantage Will Be Decision Augmentation, Not Full Automation

Composable Architecture as the Foundation for Scalable Supply Chain AI

Build a Governed AI Forecast Review Workflow Before Connecting AI to Your Planning System

Supply Chain Outlier Detection 101: Build a simple demand-sensing review team with AI agents

Map the supply chain IT portfolio before adding another AI application

How to choose supply chain software when every vendor has an AI story

DeepVu

SKU Science

SAP

Nicolas Vandeput

Adde Jans

Jonathon Karelse

Alain Matar

Arnaud Morvan

Mark Sawaya