International Journal on Science and Technology

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Autonomous AI Agent Performance in Dynamics 365 Finance and Operations Procurement Processes

Author(s) Manish Sonthalia
Country United States
Abstract The convergence of artificial intelligence and enterprise resource planning systems represents one of the most significant transformations in modern business operations. This whitepaper examines the revolutionary impact of autonomous AI agents within Microsoft Dynamics 365 Finance and Operations (D365 F&O) procurement processes, providing enterprise leaders with a comprehensive analysis of implementation strategies, performance metrics, and strategic value propositions.
As global supply chains face unprecedented complexity, inflationary pressures, and demand for operational excellence, organizations are increasingly turning to AI-powered automation to maintain competitive advantage. The integration of autonomous AI agents into D365 F&O procurement processes has emerged as a critical enabler of strategic transformation, moving beyond traditional automation to introduce intelligent systems capable of independent decision-making, adaptive learning, and proactive risk management.
Our research indicates that organizations implementing autonomous AI agents in procurement experience significant operational improvements, including up to 50% reduction in procurement cycle times, 35% improvement in spend compliance, and 20% enhancement in overall procurement ROI. These improvements stem from the agents’ ability to automate routine transactional tasks while providing sophisticated analytics and predictive insights that support strategic decision-making.
The technical architecture underlying these implementations leverages Microsoft’s comprehensive AI ecosystem, primarily through Microsoft Copilot Studio and the Power Platform. This integration transforms D365 F&O from a passive system of record into a proactive “Agentic ERP” that actively drives business processes, enforces compliance, and identifies optimization opportunities in real-time.
However, successful implementation requires careful attention to data quality, change management, and ethical considerations. Organizations must address challenges related to data integration, cultural resistance, and the inherent limitations of current AI technology while maintaining focus on security, compliance, and transparency.
Looking ahead, the evolution toward fully autonomous procurement ecosystems appears inevitable, with emerging technologies promising even greater capabilities in predictive analytics, supplier intelligence, and sustainable sourcing practices. Organizations that begin their AI journey now will be best positioned to capitalize on these future developments.
Field Engineering
Published In Volume 16, Issue 4, October-December 2025
Published On 2025-12-19
DOI https://doi.org/10.71097/IJSAT.v16.i4.9913
Short DOI https://doi.org/hbf82t
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