Change Management and Scope Control

IBM reported that its Ai-driven IBM Watson system helped keep a large European infrastructure project on track by analyzing historical data to alert managers to potential delays and cost overruns and by optimizing use of materials and labor while pointing out risk factors. The result was a significant reduction in project delays along with cost savings.

AI and data company Databricks faced a challenge when its workforce doubled as its HR team could not keep up with employee support questions about onboarding, software access, and company policies. The company deployed its own AI assistant R2DB but initially ticket deflection was only 10%. But after expanding R2DB to cover more workflows, using Slack to educate employees directly within their flow of work and fine-tuning processes to balance speed with quality, 73% of support tickets were deflected. Databricks cut annual hiring costs by $1.5 million, while giving employees faster, more reliable help.

A survey by the Project Management Institute showed 91% of executives in the field believed AI would have at least a moderate impact on the field, with 58% saying the impact would be “major” or “transformative.” Companies report improved stakeholder relationships due to enhanced transparency in change management, with AI-generated impact assessments providing clear visibility into the consequences of proposed scope modifications. The technology also contributes to organizational learning by capturing patterns of scope evolution, enabling better initial requirements definition and more accurate project estimation in the future.