Accounts payable (AP) has traditionally been described as a costly, transactional back-office operation. This paradigm is changing due to Agentic AI (AAI), not because of technological advancements. The ability of artificial intelligence (AI) to autonomously observe, reason, and carry out intricate, multi-step workflows sets it apart from rule-based robotic process automation (RPA) and reactive generative AI (GenAI). This chapter examines the revolutionary effect of this technology on the AP function. AP was once a cause of financial risk and operational inefficiency. It can now be rethought as a proactive, strategic element for organizational expansion and economic stability. Modern manual accounting processing is expensive, prone to mistakes, and does not scale well as a business grows. With cycle durations longer than 15 days and human invoice processing expenses as high as $40 per invoice, empirical evidence shows a considerable risk of fraud and expensive errors (Semlani, Intelligent inter-firm automation: The use of AI agents to improve financial settlements. International Journal of Science and Research Archives, 16(01), 2042–2050, 2025). AAI makes an all-encompassing solution with a measurable return on investment possible. Automated systems can achieve near-perfect accuracy, cut processing times to a few days, and lower the cost per invoice to about $2, resulting in estimated efficiency improvements of 80–90% (Losbichler & Lehner, Limits of artificial intelligence in controlling and the ways forward: A call for future accounting research. Journal of Accounting & Organizational Change, 17(1), 1–15. https://doi.org/10.1108/JAOC-02-2020-0022 , 2021). AAI offers supplementary strategic benefits in addition to direct cost savings. The technology also gives small and large organizations a long-term financial edge by allowing them to benefit from early payment discounts, maximize working capital allocation, and shift financial management from a reactive, historical analysis to a proactive, real-time focus (García-Vera et al., Automatización de procesos contables mediante Inteligencia Artificial: Oportunidades y desafíos para pequeños empresarios ecuatorianos [Automation of accounting processes through Artificial Intelligence: Opportunities and challenges for Ecuadorian small business owners]. Revista Transdisciplinaria de Estudios Sociales y Tecnológicos, 3(2), 51–67. https://doi.org/10.58594/rtest.v3i3.93 , 2023). Finance operators can refocus their efforts on higher-order duties like strategic partner negotiating and intricate cash flow analysis by using AI to take on repetitive, low-value jobs. This effectively turns the finance department into a dynamic value engine for the entire organization, redefining its function from a data processing unit to a strategic partner (Eyo et al., Agentic AI in SAP: Collaborative joule agents across procurement, finance, and logistics. Global Journal of Engineering and Technology Advances, 24(02), 091–108, 2025). Phased planning and execution are necessary for the successful deployment of AAI. Strong governance structures, a strong data infrastructure, and a substantial investment in the development of the financial staff are prerequisites. The main implementation obstacle is organizational rather than technological, requiring a fundamental change from a human-centric operational paradigm to one collaborative between humans and AAI. Organizations that complete this shift can achieve a significant competitive edge and future-proof their operations.

Agentic AI Supporting Accounts Payable in Procurement

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发表日期：

2026年

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Bernardo Nicoletti

摘要

Accounts payable (AP) has traditionally been described as a costly, transactional back-office operation. This paradigm is changing due to Agentic AI (AAI), not because of technological advancements. The ability of artificial intelligence (AI) to autonomously observe, reason, and carry out intricate, multi-step workflows sets it apart from rule-based robotic process automation (RPA) and reactive generative AI (GenAI). This chapter examines the revolutionary effect of this technology on the AP function. AP was once a cause of financial risk and operational inefficiency. It can now be rethought as a proactive, strategic element for organizational expansion and economic stability. Modern manual accounting processing is expensive, prone to mistakes, and does not scale well as a business grows. With cycle durations longer than 15 days and human invoice processing expenses as high as $40 per invoice, empirical evidence shows a considerable risk of fraud and expensive errors (Semlani, Intelligent inter-firm automation: The use of AI agents to improve financial settlements. International Journal of Science and Research Archives, 16(01), 2042–2050, 2025). AAI makes an all-encompassing solution with a measurable return on investment possible. Automated systems can achieve near-perfect accuracy, cut processing times to a few days, and lower the cost per invoice to about $2, resulting in estimated efficiency improvements of 80–90% (Losbichler & Lehner, Limits of artificial intelligence in controlling and the ways forward: A call for future accounting research. Journal of Accounting & Organizational Change, 17(1), 1–15. https://doi.org/10.1108/JAOC-02-2020-0022 , 2021). AAI offers supplementary strategic benefits in addition to direct cost savings. The technology also gives small and large organizations a long-term financial edge by allowing them to benefit from early payment discounts, maximize working capital allocation, and shift financial management from a reactive, historical analysis to a proactive, real-time focus (García-Vera et al., Automatización de procesos contables mediante Inteligencia Artificial: Oportunidades y desafíos para pequeños empresarios ecuatorianos [Automation of accounting processes through Artificial Intelligence: Opportunities and challenges for Ecuadorian small business owners]. Revista Transdisciplinaria de Estudios Sociales y Tecnológicos, 3(2), 51–67. https://doi.org/10.58594/rtest.v3i3.93 , 2023). Finance operators can refocus their efforts on higher-order duties like strategic partner negotiating and intricate cash flow analysis by using AI to take on repetitive, low-value jobs. This effectively turns the finance department into a dynamic value engine for the entire organization, redefining its function from a data processing unit to a strategic partner (Eyo et al., Agentic AI in SAP: Collaborative joule agents across procurement, finance, and logistics. Global Journal of Engineering and Technology Advances, 24(02), 091–108, 2025). Phased planning and execution are necessary for the successful deployment of AAI. Strong governance structures, a strong data infrastructure, and a substantial investment in the development of the financial staff are prerequisites. The main implementation obstacle is organizational rather than technological, requiring a fundamental change from a human-centric operational paradigm to one collaborative between humans and AAI. Organizations that complete this shift can achieve a significant competitive edge and future-proof their operations.