AI-Driven tools and their influence on project decision-making in U.S. technology enterprises - Umme Zinia Zahan Nodia; Md Minar Hossain; Falguni Rahman; Md Mehedi Hasan Antor; Mohammad Tahmid Ahmed (Goodwood Publishing, 2025)
Purpose: This study investigates the impact of AI-driven tools on project decision-making in U.S. information technology (IT) companies, focusing on the roles of predictive analytics, natural language processing (NLP) assistants, and AI dashboards in improving decision quality, project outcomes, and stakeholder collaboration. Research Methodology: A mixed-methods design combining a systematic literature review and an empirical survey was used. Data were collected from project managers at major U.S. IT firms, including Microsoft, Oracle, and Google, who utilize AI-enabled platforms such as Microsoft Project, Jira, and IBM Watson. Quantitative data were analyzed through regression modeling and descriptive statistics, while qualitative insights were examined using thematic analysis. Results: The results show that AI technologies significantly improve the accuracy of project decision-making, minimize budget deviations, and strengthen cross-team communication. Predictive analytics enhanced early risk identification, NLP assistants streamlined scheduling and reporting, and AI dashboards increased real-time visibility and stakeholder engagement. Companies demonstrating higher AI maturity achieved superior performance across key project indicators. Conclusions: Integrating AI into project management enhances decision-making by combining automation with data-driven intelligence. Strategic AI adoption improves efficiency, reduces scope creep, and boosts managerial satisfaction within U.S. IT contexts. Limitations: The study focuses exclusively on large U.S.-based IT firms, limiting its applicability to smaller or global enterprises. The rapid evolution of AI restricts long-term generalization. Contribution: This research enriches project management and information systems literature by contextualizing AI’s role in high-tech decision-making and offering practical guidance for managers, executives, and policymakers driving digital transformation.