ChatGPT for Finance Teams: Top 7 Uses from a Network of 300+ CFOs

Finance leaders spent much of 2024 in “wait and see” mode with AI. Among C-suite roles, CFOs were the most cautious—unsure what was hype, concerned about accuracy, and wary of security gaps. But by mid-2025, that mindset shifted. CFOs began moving from observing to experimenting, building familiarity even when they weren’t ready to hand over the tougher work.

That’s the perspective of Kalee Gardella, Chief Community Officer at The Circle, a private executive network supporting more than 300 growth-stage CFOs. Through peer discussions and workshops, she’s watched AI adoption climb quarter after quarter. Recent surveys now show that more than half of small and midsize businesses are using AI in some part of their operations, and finance has become one of the fastest-rising areas for adoption.

Gardella sat down with us and shared where CFOs are seeing the strongest early gains. Below are seven ways finance teams are using ChatGPT to cut down on repeatable work, speed up core processes, and understand troves of data faster.

1. Turning financial data into usable narratives

Finance teams spend a huge amount of time writing: board updates, monthly summaries, investor notes, and explanations of what changed in the numbers. That’s why many CFOs started using AI for narrative work, and 68% of CFOs say GenAI is essential for efficient reporting.

“The qualitative side of finance was the easiest place to start. It wasn’t about trusting the math. It was about seeing whether the tool interpreted the data correctly,” Gardella explains.

A common workflow is to feed ChatGPT a short set of metrics (revenue growth, margin shifts, churn, or changes in spending) through a secure, private environment and ask for a brief explanation. The model produces a draft that teams review and edit, which cuts down on the time spent starting from scratch.

This extends across the reporting cycle. Some investor relations teams give AI prior earnings call transcripts and quarterly results to draft opening remarks and possible analyst questions. For SMBs, AI helps translate financial jargon into plain language so non-financial managers can follow key updates without long back-and-forth.

2. Automating everyday, repeatable tasks

Some early wins with AI often come from simple tasks that show up every week. CFOs in Gardella’s community leaned into individual productivity first, removing small but constant drains on their time.

Finance teams gravitate toward what Gardella calls “deterministic” work—tasks that produce a predictable output for a given input. This includes tasks like cleaning CSVs, reformatting system exports, standardizing templates, drafting routine vendor emails, creating first-pass variance notes, and organizing files. Surveys show that 71% of companies using GenAI in finance have seen productivity gains, with more than half reporting better use of data in decision-making.

Some teams are taking this further with “vibe coding,” in other words, describing their ideal process in plain language and letting the AI generate small tools that automate it. This approach helps finance staff build solutions without needing traditional coding skills.

3. Reducing manual work in the month-end close

Month-end close can consume weeks of effort as teams move files, review entries, check documents, and prepare reports. Generative AI is helping reduce some of that grind.

One CFO automated a vendor-invoice entry process that previously took about 20 hours, bringing it down to roughly two. Others use AI to support file routing, invoice review, categorization, reconciliation prep, close checklists, flux analysis drafts, and early versions of the close package. Teams are also using AI to support SOX compliance reporting, automating portions of the workflow that used to require extensive manual documentation.

Gardella notes that one CFO built an internal “review agent” that checks models, decks, and reconciliations for consistency. “It saves hours of tick-and-tie. Their rule is: humans own the narrative, and AI checks accuracy and completeness,” she says.

AI doesn’t replace the judgment needed for close, but it removes large portions of setup and checking.

4. Preparing budgets and early forecast scenarios

Finance leaders were initially hesitant to trust AI with numerical work. As tools improve, confidence is growing.

Roughly three-quarters of CFOs now view AI as very or extremely important for financial reporting, FP&A, and decision support. Teams use it to pull historicals into trends, draft baseline forecasts, compare scenarios, summarize changes, and combine external benchmarks with internal data.

Some of the more advanced CFOs in Gardella’s network are going further. “We’re seeing custom CFO co-pilots built with metrics, risk levels, and company context that generate board-ready outputs,” she explains. Others are scraping quarterly summaries, benchmarking data, or public filings to produce forward-looking estimates. A few are building agents that monitor foreign exchange rates, flag anomalies, or surface trading opportunities.

CFO Cosmin Pitigoi of Flywire notes that AI helps connect forecasting with explanation, giving teams better reasoning behind model behavior—long a pain point for analysts.

5. Supporting better collaboration across departments

Finance interacts with every part of the business, from sales to customer support. AI helps teams respond faster without taking on more manual searching.

ChatGPT is used to scan customer contracts, pull renewal terms, flag exceptions, draft responses to billing questions, and curate internal knowledge. “Some CFOs are using AI to enrich customer signals—funding rounds, job changes, anything that helps their teams keep relationships warm,” Gardella says.

Teams are also building agents that route internal requests to the right people. When someone in the organization needs finance approval or has a question about billing, these agents act as a first line of response, directing requests appropriately and reducing the back-and-forth that slows down deal workflows.

6. Acting as a partner in decision-making and analysis

Many CFOs describe ChatGPT as a second set of eyes. It helps pressure-test assumptions, outline pros and cons, generate questions for a strategy discussion, draft decision memos, or break down risks in new initiatives.

Gardella sees this across nearly every team she works with. “CFOs are using AI as an associate to bounce ideas off of or get to a conclusion. Anything that doesn’t require deep calculation is fair game,” she says.

CFOs still trust their own Excel models and judgment for work that requires inference and tradeoffs, the kind of analysis where experience shapes the outcome. But finance teams are starting to trust AI for setup work on repeatable processes—building comparison tables, organizing data inputs, or structuring initial scenario models—so they can spend more time on interpretation.

7. Upskilling teams and reshaping finance hiring

AI literacy is rapidly becoming a baseline skill in finance. Many CFOs are already adding it to hiring criteria for analyst and manager roles. By 2025, 79% of CFOs said they planned to increase AI spending.

Gardella says the mindset change has been striking. “Midway through the year, it flipped. CFOs realized they needed to spend time on AI themselves so their teams would follow,” she says.

Teams that build AI fluency move faster and spend more time on decisions rather than mechanics. Nearly 94% of finance chiefs believe generative AI will materially improve at least one area of their department within a year, and 98% expect it to positively affect their industry within three years.

However, security remains a top concern. CFOs are addressing this by requiring teams to use enterprise-level AI accounts with built-in privacy protections rather than public AI platforms where company data could be exposed.

As more companies adopt AI at the organizational level, IT teams are working to establish company-wide security protocols specifically for AI tools, which reduces the risk of individual departments inadvertently exposing sensitive financial information through unsecured platforms.

For Salesforce administrators looking to understand how finance and IT collaboration is evolving with AI adoption, we recommend our recent webinar on connecting finance and Salesforce..

The next step: AI built into your accounting platform

While tools like ChatGPT are flexible and can be used in many different ways, finance teams are also turning to tools built specifically for accounting with embedded AI capabilities. Platforms like Accounting Seed now embed specialized AI agents that live inside the financial system—Collections Agents for receivables, Bill Pay Agents for payables, and General Ledger Agents for transaction research.

Because these agents run on the same platform where financial data already lives (Salesforce), teams avoid complex integrations or risky data transfers. AI becomes part of the workflow instead of something bolted onto it, resulting in faster insights with less effort and fewer workarounds.

Getting started with AI in finance

If you’re ready to move beyond experimentation and want to understand how to implement AI successfully in your finance function, this webinar on why most AI fails in finance—and how to fix it walks through practical steps for getting started. You can also explore how AI can support your accounting workflows directly within Accounting Seed’s Salesforce-native system.