The Agentic CFO: How Finance Leaders Build AI-Native Organisations That Govern, Scale, and Compound

The Agentic CFO: How Finance Leaders Build AI-Native Organisations That Govern, Scale, and Compound book cover

The Agentic CFO: How Finance Leaders Build AI-Native Organisations That Govern, Scale, and Compound

Author(s): Narendra Cherlopalli (Author)

  • Publisher: Packt Publishing - ebooks Account
  • Publication Date: November 10, 2026
  • Edition: 1st
  • Language: English
  • Print length: 70 pages
  • ISBN-10: 1808761596
  • ISBN-13: 9781808761591

Book Description

Build an AI-native finance function that can govern, automate, and scale by designing the data foundations, controls, audit trails, and human accountability every finance agent needs

Key Features

  • Build the data and governance foundations required for finance AI
  • Apply agentic AI across FP&A, close, tax, AP/AR, and treasury
  • Design human oversight, audit trails, and controls before scaling AI

Book Description

AI can automate finance workflows, but autonomy without strong foundations creates new risks. The Agentic CFO shows finance leaders how to build an AI-native finance function where agents operate within clearly defined data, governance, accountability, and control structures.

You’ll begin by addressing the problems that undermine finance AI initiatives before they scale: inconsistent data, unclear ownership, poor process documentation, and weak accountability. You’ll then design the governance architecture around autonomous agents, including human authority lines, audit trails, escalation paths, and agent ownership.

The book applies these principles to the finance workflows where AI can have the greatest impact, including financial close, FP&A, tax, AP/AR automation, treasury, and spend management. You’ll see how to determine what agents can handle autonomously, what requires human judgment, and how to make automated decisions auditable.

Finally, you’ll explore the evolving role of the CFO, build a self-improving finance system, and establish proof before expanding AI across the organization.

What you will learn

  • Prepare finance data and processes for agentic AI
  • Define human authority before deploying autonomous agents
  • Build auditable decision trails for finance AI
  • Apply AI agents to close, FP&A, tax, and AP/AR
  • Introduce agentic AI into treasury and spend management
  • Establish ownership, escalation paths, and governance
  • Build finance systems that improve with every cycle
  • Prove AI outcomes before scaling across the organization

Who this book is for

This book is for CFOs, controllers, VPs of Finance, FP&A leaders, finance transformation leaders, and senior finance professionals responsible for introducing AI into the finance function. It is particularly relevant to leaders moving beyond AI pilots toward governed, production-ready agentic workflows. No AI development or programming experience is required.

Table of Contents

  1. The Post-Mortem Nobody Wants to Write
  2. The Sequencing Problem
  3. The Data Foundation
  4. The Human Authority Line
  5. The Audit Trail Architecture
  6. The Agent Org Chart
  7. Financial Close
  8. FP&A Transformation
  9. Tax in the AI-Native Finance Function
  10. AP/AR Automation
  11. Treasury and Spend Management
  12. The COFO
  13. The Self-Improving Finance System
  14. Proof Before Scale

Editorial Reviews

Editorial Reviews

About the Author

Narendra Cherlopalli is a Finance and Supply Chain AI practitioner and transformation advisor helping CFOs build AI-native functions that govern, scale, and compound. He is the founder of NYDTACH.AI and author of The Value Chain Practitioner newsletter. His work spans agentic AI in financial close, planning and budgeting, tax, treasury, and strategic finance.

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