Agentic AI Supporting the Procure-to-Pay Phase in Procurement

Bernardo Nicoletti
Additional contact information
Bernardo Nicoletti: Temple University, Fox School of Business

Chapter Chapter 7 in Agentic AI for Procurement, 2026, pp 125-138 from Springer

Abstract: Abstract Agent-based artificial intelligence (AAI) places orders, monitors stock levels, and processes invoices daily. This is changing the way operational procurement and order fulfillment work. Operations become more resilient and responsive through intelligent decision-making, adaptive learning, and exception handling. AAIs are better than traditional robotic process automation (RPA) because they continuously improve processes, solve problems before they arise, and add value. They also transform procurement from a cost center to an enabler. Amazon, Nestlé, Walmart, Shell, and other organizations in other industries have put these ideas into practice, and the results show how they can help, including shorter processing times and savings. This transformation is based on the ideas of distributed intelligence, multi-agent architectures, and optimization algorithms that reconcile goals such as cost reduction, shorter lead times, and risk mitigation. This chapter examines how artificial intelligence (AI) can help manage orders, intelligently predict demand, dynamically select partners, optimize inventory levels, and automatically process invoices. To make the supply network more open, we are looking at the potential uses of AI in predictive maintenance, crisis response, and connecting with digital ecosystems such as ERP and IoT. AI can be very useful and intelligent, but it needs solid technology architectures, good change management, and governance frameworks to monitor things and manage risks. Responsible adoption requires careful evaluation of ethical considerations, including transparency of algorithms and the impact on labor. Future advances, including merging quantum computing and AI, are expected to improve computational capabilities and incorporate sustainability into operational decision-making. This summary highlights AI’s importance in keeping operations and procurement current.

Keywords: Procurement; Agentic AI; Operations; Procure-to-pay (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-032-23024-9_7

Ordering information: This item can be ordered from
http://www.springer.com/9783032230249

DOI: 10.1007/978-3-032-23024-9_7

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().