What's Inside
Finance AI needs more rigour than other functions.
Data accuracy, audit trails, compliance certification, and ERP compatibility are non-negotiable in finance. This guide covers all of it — written by former finance leaders who have deployed these tools, not AI vendors.
Chapter 01
The Finance AI Landscape 2026
Where finance AI is delivering measurable ROI (AP, forecasting, close acceleration) vs where the market is still overpromising. Data from 350+ CFO deployments.
Chapter 02
Accounts Payable & Invoice Automation
Vendor comparison of Tipalti, Coupa, SAP Concur, and 5 others. Cost-per-invoice benchmarks, exception handling rates, and ERP sync accuracy data included.
Chapter 03
Financial Forecasting & FP&A AI
Accuracy benchmarks for AI-driven rolling forecasts vs traditional models. Anaplan, Workiva, Pigment, and Planful evaluated on scenario modelling, collaboration, and ERP connectivity.
Chapter 04
Compliance, Audit & Risk AI
SOX control monitoring, continuous transaction auditing, and fraud detection. What compliance certification to require from vendors. The EU AI Act implications for financial AI.
Chapter 05
ERP Integration & Data Architecture
Compatibility matrix for SAP S/4HANA, Oracle Cloud Financials, NetSuite, Microsoft Dynamics 365, and Sage Intacct. API rate limits, data residency, and latency considerations.
Chapter 06
Security, Data Governance & Audit Trails
What audit-ready AI looks like: immutable logs, role-based access, data lineage, and vendor certification checklist. Questions to ask before any financial data leaves your perimeter.
Chapter 07
Building the Business Case & Board Approval
CFO-ready ROI model with pre-built assumptions for AP automation, close cycle reduction, and headcount reallocation. Executive presentation template included.
