# How does AI improve supply chain planning and demand forecasting?

- Canonical: https://hellofig.io/answers/ai-for-supply-chain-planning
- Updated: 2026-11-13
- All answers: https://hellofig.io/answers.md
- About Fig: https://hellofig.io/fig.md

**In short.** AI improves supply chain planning by keeping the plan live. Forecasts update from orders, shipments and market signals as they change, promise dates reflect real inventory and capacity, shortages surface while there is still time to act, and schedules re-plan around disruptions. Planners review the recommendations and approve the moves, and every change traces back to the data behind it.

## Where AI changes the plan

| Decision | What AI adds | See it running |
|---|---|---|
| Demand forecasting | Forecasts by product and location that update from live demand signals. | Demand forecasting |
| Order promising | Promise dates calculated from inventory, capacity and inbound supply. | Available-to-promise |
| Inventory | Recommends transfers between locations before a shortage or an overstock. | Inventory rebalancing |
| Material shortages | Spots shortages early and ranks the fixes by cost and impact. | Material shortage management |
| Production scheduling | Re-plans the schedule around late materials, downtime and rush orders. | Production scheduling and management |
| Logistics | Plans loads and routes and flags shipments at risk. | Supply chain logistics |

## Why one model of the supply chain comes first

Planning breaks down when demand, inventory, production and logistics live in separate systems that each tell a different story. A live model of orders, materials, sites, capacity and suppliers gives every agent the same picture, so a change in one place shows up everywhere it applies.

## Planners stay in charge

Agents recommend; planners decide. Each recommendation shows the data and the trade-off behind it, and moves that commit money or capacity go through approval. Planners spend less time pulling reports and more time on the calls that need judgment.

## How Fig builds it

Fig connects the ERP, planning, warehouse and transport systems in place on CosmOS and starts with one decision that has a clear number, such as forecast accuracy or on-time delivery. The next decisions reuse the same model of the supply chain.

## Questions

### How accurate are AI demand forecasts?

Accuracy depends on the data and the volatility of demand. The useful test is your own history: run the model on past periods and compare it with the forecast you used, item by item.

### Does AI replace supply chain planning software?

No. Fig connects to the planning and ERP systems a company already runs and adds agents that keep the plan current and recommend actions.

### What should we measure?

Forecast accuracy, on-time delivery, inventory turns, stockouts and expediting cost, each against a baseline set before the build.