Using Agents to Automate Capturing Events and Seasonality Impact on Demand Predictions for $10M–$100M Companies

Companies in the $10M–$100M range frequently rely on planners to manually adjust forecasts to reflect seasonal peaks and promotional campaigns.

As SKU counts increase and promotional cadence accelerates, manual event capture becomes unsustainable.

AI agents embedded in modern planning systems continuously monitor commercial calendars, historical uplift patterns, and SKU-level variability.

They automatically adjust demand projections to reflect anticipated seasonal and promotional effects.

• Detection of promotion-driven demand shifts
• Isolation of baseline demand
• Quantification of seasonal uplift factors
• Scenario simulation across SKUs
• Automated forecast selection

Traditional workflows rely on planners to override baseline forecasts during high-demand events.

AI agents reduce this reliance by embedding event-aware adjustments structurally.

Planning agents continuously update demand projections as new commercial inputs are introduced.

Procurement recommendations adjust dynamically based on anticipated demand variability.

As companies scale across SKUs and channels, agent-driven forecasting maintains consistent event capture.

This reduces planner workload and improves responsiveness to demand shifts.

For $10M–$100M companies, automating the capture of seasonal demand variability improves inventory stability and reduces manual effort.

Agentic AI planning systems enable scalable, event-aware forecasting aligned with commercial calendars.