Most finance teams know AI can help. The challenge is knowing where to start. With thousands of tools and endless hype, it’s easy to fall into what we call random acts of AI—disconnected experiments that feel productive but rarely lead anywhere.
A better approach? Start with specific, high-value use cases where AI can deliver results quickly. Here are six, drawn from real-world finance operations, split between practitioner-level and leadership-level opportunities.
1. Touchless Invoice Processing
If you’ve worked in or around accounts payable, you know the pain: invoices arrive as PDFs, emails, and scanned documents. Someone has to manually read each one, extract the data, match it against a purchase order, assign codes, and route it for approval.
AI can now handle this entire pipeline: capturing invoices, extracting fields, validating data quality, proposing coding, and routing only the exceptions to humans. One global manufacturer implemented AI-powered AP automation and cut processing time from seven days to one to two days, reaching 95% touchless invoicing.
2. Automated Expense Auditing
Traditional expense auditing relies on sampling: your team manually reviews a fraction of reports and plenty of policy violations slip through. AI flips this model entirely. Instead of sampling, AI reviews 100% of expense line items, auto-approves low-risk transactions with full documentation, and escalates only high-risk exceptions to human auditors.
A global pharmaceutical company deployed this approach and saved 4,000 auditor hours every quarter while processing 400,000 expense audits per year.
3. Cash Application and Remittance Matching
In accounts receivable, customers send payments with unstructured remittance information, partial payments, and batched remittances with no clear mapping. Matching each payment to the right invoice is a massive manual workload that slows down cash visibility.
AI can learn customer and bank payment behaviors, recommend or auto-clear matches, and dramatically increase straight-through processing. The downstream impact: your AR team shifts from matching payments all day to focusing on collection strategy and working capital improvement.
1. Close Management and Acceleration
If you’re responsible for the monthly or quarterly close, this likely sounds familiar: close effort gets stuck in manual checklists, spreadsheet-based status tracking, and handoffs that introduce risk and delay. You spend enormous energy coordinating the process rather than ensuring the quality of the output.
AI-enabled close management automates the orchestration—task assignment, status tracking, dependency management, and escalation—giving you real-time visibility without having to chase people down.
2. Transaction Matching and Account Reconciliation
This is one of the biggest bottlenecks in any finance organization. Manual matching is high volume, error-prone, and time-consuming late in the close cycle, exactly when that time is most valuable.
AI-assisted matching combines automated rules with intelligent exception handling, reducing the volume needing human review to a fraction of the total while creating a more reliable audit trail.
3. Lease Abstraction and Accounting Automation
Lease accounting standards require detailed contract data: key dates, payment schedules, renewal options, escalation clauses. Manually extracting this from hundreds or thousands of contracts is slow and expensive, and auditors need to trace every journal entry back to the source.
AI can extract lease terms using natural language processing and generate the accounting records and journal entries automatically, maintaining full traceability. This isn’t just better efficiency, it’s also reducing compliance risk.
These six use cases are starting points. To find more in your own role, ask yourself:
The pattern is simple: if a task is frequent, doesn’t require deep judgment, and follows a predictable sequence, it’s probably a great target for AI.
Learn More at AI Academy
AI for Finance is a comprehensive learning journey designed to transform how you approach finance in the age of artificial intelligence. You will move from understanding the strategic imperative for AI adoption to building a complete, prioritized action plan for your specific role and organization.
Across four courses, you will master frameworks for identifying and prioritizing AI opportunities, learn to navigate the complex technology landscape with confidence, and develop hands-on skills that put you ahead of the vast majority of finance professionals. Whether you are a frontline practitioner managing close cycles and variance analysis or a senior leader responsible for building a scalable, high-performing finance function, this series will equip you with the mindset, methodology, and practical capabilities to lead AI transformation in your organization.