This month’s edition brings together a few signals that point to where AI in audit and finance is heading. From growing client expectations to practical ways teams are applying AI inside Excel, the theme is less about experimentation and more about responsible, real-world use.
To help you stay in the loop, here’s what’s new this month.
Generic AI vs. Audit-Specific AI in Excel
What happens when auditors use general-purpose AI tools instead of AI designed for audit work?
As AI adoption grows, many teams are experimenting with generic AI assistants. But audit workflows have specific requirements around traceability, evidence, and reviewability that general tools are not always designed to support.
This comparison looks at how generic AI approaches differ from audit-specific AI built directly for audit and finance workflows.
When Clients Expect AI, Trust Becomes the Real Test
What happens when clients expect firms to use AI, but still demand full transparency?
Client expectations around AI are evolving quickly. Many organizations now assume their auditors are exploring AI-enabled workflows, but that expectation comes with an important condition: trust in how those tools operate.
This article by Vidya Peters highlights why explainability, clear audit trails, and human judgement remain central as AI becomes more embedded in audit and finance work.
Industry View: How Will Accountants Learn When AI Does the Work?
As AI begins to automate more repetitive accounting and audit tasks, the profession is facing an important question: how will the next generation of accountants develop the skills traditionally learned through hands-on work?
Many entry-level tasks have historically helped professionals understand systems, controls, and documentation. As automation takes on more of that work, training may shift toward deeper conceptual learning, stronger oversight skills, and supervising AI-enabled processes.
Journal of Accountancy explores how firms and organizations may need to rethink how accountants learn in an AI-enabled profession.
DataSnipper Named to the Forbes Fintech 50
Forbes released its 2026 Fintech 50, recognizing companies building meaningful innovation across financial services. DataSnipper was included for its work applying AI directly within the audit and finance workflows professionals already use every day.
The recognition highlights how automation and AI are moving closer to the core of assurance and financial operations, particularly when designed to stay transparent and embedded in existing processes.
👉 See the Forbes Fintech 50 2026 list
How Excel Agents Perform Royalty Calculations
Royalty calculations often require reviewing agreements, identifying relevant clauses, and applying the correct logic to financial data. That process can involve extensive document review and manual validation.
Excel Agents can perform these calculations directly in Excel by executing defined instructions and linking results back to the relevant source documents. The workflow remains transparent and reviewable while reducing the amount of manual document analysis required.
👉 Learn how Excel Agents perform royalty calculations
AI Readiness: Where Does Your Audit Team Stand?
Many audit and finance teams are exploring AI but are unsure how mature their current processes are or where to start next.
The AI Maturity Model for Audit and Finance outlines the stages organizations typically move through as AI becomes part of their workflows, from early experimentation to structured, scalable adoption.
You can take a short assessment to understand where your team currently sits and what the next step might look like.
👉 Take the AI maturity assessment
https://datasnipper.outgrow.us/ai-maturity-quiz
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