3 Ways AI Is Showing Up in Nonprofit Finance

When AI-powered tools started to creep into nonprofit software, the use-cases were obvious—for fundraising. But as the tools have evolved, so have the opportunities for the finance office.

While generative AI has captured headlines for its creative abilities, the most valuable advances for finance teams are happening behind the scenes, reshaping how organizations communicate, automate, and make decisions.

Let’s break down the three practical ways AI is transforming nonprofit finance systems and how your team can get ahead of the curve.

1. Generative AI Is Powering Better Communication and Collaboration

As ChatGPT turns 3 years old, there is no denying that generative AI has found a place across the nonprofit organization, even in finance teams. Generative AI is making it easier for finance teams to communicate clearly, collaborate efficiently, and empower colleagues across an organization.

Instead of getting bogged down in endless email chains or struggling to explain complex financial concepts to non-finance colleagues, members of finance teams are turning to AI-powered chat tools for quick, accurate answers. Imagine a team member needing to know the remaining budget for a program or the next grant reporting deadline. Instead of popping into your office or your Slack notifications, they can ask a chat assistant and get immediate, reliable information. This reduces bottlenecks and frees up your staff’s time for more strategic work.

Generative AI also helps draft and tailor communications, from dunning letters to board report overviews, and can adjust tone or content for different audiences. This means finance professionals can focus on the message, not mechanics. AI can even summarize lengthy reports, so everyone gets the key points without wading through pages of data.

And when it comes to policies, generative tools can review drafts, flag potential issues, or help translate finance jargon for non-finance colleagues. So, you have fewer misunderstandings and a more informed, empowered organization.

2. AI-Powered Automation Turbocharges Financial Operations

While generative AI speeds up a few one-off tasks, automated workflows powered by AI take you to the fast lane. AI-driven automation goes well beyond simple “if-this-then-that” rules. Traditional automation can move documents through a workflow, but AI-powered tools actually analyze the details to identify inconsistencies in invoices, flag outliers, and even match payments with supporting documentation. Your finance team spends less time on manual checks and more time on value-added analysis.

AI accelerates processes like invoice review, payment approval, bank reconciliation, and report generation. For example, instead of reviewing every transaction, the system only surfaces anomalies for your team to review, allowing staff to focus on exceptions rather than repetitive work.

With continuous monitoring, you can catch potential errors or fraud faster, reducing risk and enabling quicker resolution. According to an IBM study, finance teams that integrate AI into their workflows can close their monthly books 33% faster—a game-changer for organizations juggling multiple programs and funding streams.

3. Agentic AI Is Enhancing Decision-Making in Real Time

The third type of AI showing up in nonprofit finance is like having a smart and capable intern, feeding your team information so you can make more strategic decisions. Agentic AI focuses on anticipating needs, identifying risks, and recommending actions in real time. By analyzing data from multiple sources, AI can spot trends, forecast cash flow, and generate scenarios that flag potential shortfalls before they become a crisis.

Take grant management as an example. AI agents can automatically pull required reports, monitor deadlines, and highlight missing documentation—streamlining compliance and reducing last-minute scrambles. When evaluating vendors, AI can analyze payment histories and tailor outreach based on account-specific risk.

These tools continuously monitor transactions and policy updates, recommending changes when regulatory shifts or audit findings require action. This helps your finance team move from reactive problem-solving to proactive, strategic leadership.

Building a Responsible AI Strategy Is Non-Negotiable

Using ChatGPT or Copilot doesn’t check the box for your organization’s goal to embrace AI. You need thoughtful policies and ongoing training. Recent studies from the Blackbaud Institute show that while 82% of fundraisers are using AI in some form only 14% of organizations have a formal policy in place. That gap leaves organizations exposed to risks around bias, confidentiality, and intellectual integrity.

A responsible AI strategy starts with drafting or updating your AI policy. Spell out use cases, clarify what’s in and out of scope, and ensure everyone understands the importance of upholding ethical standards. Regularly review and update your policy as technology and organizational needs evolve.

Training is equally important: keep humans in the loop, provide context for all recommendations, and encourage staff to question and validate AI-generated outputs. As Cat Ward from the Taproot Foundation put it, “technology alone doesn’t change organizations. People do.”

Sign up for the free AI for Social Impact certification to build practical skills tailored to nonprofits and social impact organizations. This platform-agnostic course is an initiative of the AI for Social Impact Coalition.

Clean Data Is the Backbone of Every Good AI Strategy

The most sophisticated AI is only as good as the data it draws from. If your fund accounting system isn’t accurate and up to date, automation and analytics will amplify errors instead of solving them. Strong data governance—built on best practices for fiscal period close and reconciliations—ensures that AI tools provide relevant, actionable insights.

Investing in clean, well-organized data pays dividends across every aspect of AI in finance, from process automation to scenario planning. Before layering on new tools, take time to audit your current systems and data landscape and address any gaps. This foundation will make every AI-powered initiative smarter and more effective.

By embracing a responsible, strategic approach, finance leaders can harness the full potential of AI and empower their organizations for the future. Want to learn more about how these tools are being incorporated into Blackbaud Financial Edge NXT? Check out Blackbaud’s latest product updates and AI resources for nonprofits.