PMI estimates that approximately 11% of project investment is wasted due to inefficiencies. While some inefficiency is unavoidable, much of it results from delayed decisions, poor information, and teams working on activities that add little value. AI can be used to significantly reduce the most common causes.
1. Reduce Time Collecting and Reporting Information. AI can be used to automatically collect data from schedules, project documents, financial systems, collaboration tools, and field sensors to produce real-time dashboards. Once set up, project professionals spend less time chasing data and producing reports. Instead, they focus on interpreting results, resolving issues, and supporting the project team.
2. Detect Problems Before They Become Expensive. Waste can occur because risk events are only detected after they occur. AI can be used to continuously look for signals or patterns that people may overlook. For example, AI may detect declining productivity, an increasing number of design changes, and supplier delays occurring together. The issue is investigated, and corrective action is taken to prevent milestone delays.
3. Improve Resource Allocation. Resources may be assigned on a fixed basis at the start of the project and not adjusted as the project progresses. AI can be used to continuously evaluate workload, resource skills, priorities, resource availability, and project constraints. The output is recommendations for improved resource assignments and task sequencing. The objective is to enable project leaders to select the best option to deliver the greatest value with the least disruption.
AI can be used to help project professionals make better decisions sooner. Reducing a portion of the 11% waste represents a significant opportunity for organizations to improve project performance without adjusting the scope, budget, or schedule baselines.
Posted on: August 10, 2026 08:00 AM |
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