How can AI-powered workload forecasting be configured in Wrike

Question

I’ve heard Wrike has AI-based features for forecasting workloads, but I haven’t figured out how to configure it properly. Has anyone set this up to help predict future resource needs or avoid burnout in Agile teams?

Answer 1

Wrike's AI tools are excellent for estimating workloads, identifying bottlenecks, and assisting project managers in making data-driven staffing choices. To set it up properly, you will need to enable the appropriate features and provide accurate task data.

• Use Workload Charts – Plan resource allocation based on task effort and team capability.

• Set effort estimates – Each job should include a time estimate, which AI models will use to predict future workloads.

• Activate AI suggestions – Wrike's Work Intelligence recommends task owners, risk flags, and possible overloads based on past performance.

• Integrate time monitoring – Tools such as Harvest and Wrike Time monitoring increase accuracy by displaying how long activities really take.

• Monitor AI insights – The platform may alert you to tasks that may be late, allowing you to change before problems develop.

• Run scenario planning – Simulate what-if situations by adjusting priorities or resources and tracking expected changes.

This arrangement enables you to predict hazards, effectively allocate work, and enhance team productivity far before actual issues arise.