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May 2, 20260 citationsOpen Access

Intelligent Procurement Systems: AI Approaches for Global Value Creation

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RPRajesh Kiran Dr. Patel

Key Points

  • This research explores how AI enhances decision-making in procurement and its potential role in global value creation.
  • Utilized AI techniques including machine learning and predictive analytics to analyze procurement processes.
  • Examined integration of various data sources to improve supplier collaborations and decision-making capabilities.
  • Assessed challenges and innovations in AI-driven procurement strategies.
  • Improved supplier accuracy by integrating predictive analytics and reducing cycle times for procurement.
  • Enhanced compliance with regulations and contractual standards, facilitating seamless operational processes.
  • Identified challenges in data interoperability and resistance to AI adoption in multinational networks.

Abstract

Artificial intelligence (AI) is reshaping procurement by transforming fragmented data and siloed decision-making into unified, intelligence-driven models that create measurable business value on a global scale. AI-driven procurement intelligence integrates predictive analytics, machine learning, and natural language processing to enhance visibility across supplier networks, forecast risks, and generate prescriptive recommendations for sourcing strategies. Unlike traditional procurement methods that rely heavily on historical performance and manual evaluation, AIenabled systems aggregate heterogeneous data from enterprise platforms, supplier systems, and external market indicators into centralized models, enabling real-time decision-making. The unification of procurement intelligence through AI delivers substantial business value by improving supplier accuracy, reducing cycle times, and ensuring compliance with contractual and regulatory standards. Predictive capabilities allow organizations to anticipate supplier risks, demand fluctuations, and pricing volatility, while prescriptive analytics recommend optimized supplier portfolios and negotiation strategies. This integration strengthens supplier collaboration, fosters transparency, and drives mutual value creation, which is increasingly critical in globalized supply chains. Beyond efficiency, AI-driven procurement intelligence supports sustainability and ethical sourcing by monitoring environmental, social, and governance (ESG) compliance across global supplier bases. However, challenges remain in realizing the full potential of AI-driven procurement. Issues of data interoperability, model interpretability, and organizational resistance can limit adoption, particularly across complex multinational networks. Despite these barriers, emerging applications such as blockchain-enabled procurement ecosystems and digital twin simulations hold promise for building more resilient, adaptive, and autonomous procurement systems. AI-driven procurement intelligence represents a paradigm shift in how organizations manage global supply chains. By creating unified models that align cost efficiency, resilience, and sustainability, it enables procurement to evolve from a transactional function into a strategic driver of global business value.

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Cite This Study

Rajesh Kiran Dr. Patel (2025) studied this question.

synapsesocial.com/papers/69f5951171405d493a00002dhttps://doi.org/10.5281/zenodo.19922077
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