Presented by JMT Consulting

Featuring

Buu-Linh Tran, CPA – SVP of Financial Solutions, JMT Consulting
James McCracken – Manager, Data Services (AI Strategy, Integrations & ERP Governance), JMT Consulting

Introduction

Nonprofit finance teams are under constant pressure to move faster, improve accuracy, and provide clearer insights to leadership. At the same time, many teams are still spending the majority of their time on manual processes rather than strategic analysis.

In this webinar, JMT Consulting explored how artificial intelligence is being used today in practical, low-risk ways to increase productivity across nonprofit finance operations. The key message was simple: AI is not a replacement for finance teams. It is a tool that helps them work more efficiently, reduce manual effort, and focus on higher-value work.

What Risks Do Nonprofits Face When Finance Processes Stay Manual?

Many nonprofit organizations still rely heavily on spreadsheets, manual reconciliations, and disconnected workflows. While these approaches may feel familiar, they introduce real challenges over time.

Common risks include:

• Slower month-end close and delayed reporting
• Increased risk of human error
• Limited visibility into financial performance
• Overreliance on individual knowledge and workarounds
• Less time available for analysis and strategic planning

As highlighted in the session, finance teams often spend the majority of their time on data entry rather than insight, which limits their ability to support leadership effectively.

What AI Is and What It Is Not

One of the most important clarifications from the webinar is understanding what AI actually does in a finance context.

AI is best thought of as:

• A productivity assistant
• A pattern recognition tool
• A summarization and first-draft generator

However, AI does not replace core finance responsibilities. It cannot:

• Post journal entries
• Approve transactions
• Override internal controls
• Make accounting judgments
• Replace audits

AI supports finance processes, but human oversight and expertise remain essential .

How AI Fits into the Nonprofit Finance Technology Stack

AI does not replace your ERP system. Instead, it works around it.

As shown in the webinar, AI operates across:

• ERP systems like Sage Intacct (system of record)
• Reporting and exports
• APIs and data feeds
• Documents and internal policies
• AI tools such as Copilot and Gemini

This approach allows organizations to enhance workflows without increasing risk to core financial systems .

How Nonprofit Finance Teams Are Using AI Today

AI is already being used in practical ways across finance teams to reduce manual work and improve communication.

Common use cases include:

• Drafting close narratives
• Explaining variances in plain language
• Preparing board-level summaries
• Flagging anomalies for review
• Supporting audit preparation

At the leadership level, AI helps translate complex financial data into clear insights, allowing teams to spend less time explaining numbers and more time discussing strategy .

Real-World Examples of AI in Action

The webinar highlighted several examples of AI embedded within financial systems:

• Automated reconciliation reporting with variance detection
• Real-time visibility into discrepancies across entities
• Drill-down transaction insights for faster issue resolution
• AI-assisted close processes with task visibility across AP, AR, and GL

These tools allow finance teams to identify issues earlier, resolve them faster, and maintain better control over financial operations .

What Risks Do Nonprofits Face When Adopting AI?

AI adoption introduces its own set of challenges, most of which are organizational rather than technical.

Key risks include:

• Data privacy and confidentiality concerns
• Overreliance on AI-generated outputs
• Inaccurate or misleading results (hallucinations)
• Lack of internal controls around AI usage
• Resistance to change within teams

As emphasized in the session, most AI failures are driven by people and process issues, not the technology itself .

Best Practices for Responsible AI Use

To safely and effectively adopt AI, nonprofits should follow a structured approach:

• Never input confidential data into public AI tools
• Treat AI output as a draft, not a final answer
• Keep humans in control of decisions and approvals
• Document where AI is used in processes
• Establish internal guidelines for AI usage

These practices help ensure that AI enhances operations without introducing unnecessary risk .

How to Get Started with AI in Nonprofit Finance

For organizations just beginning their AI journey, the best approach is to start small and focus on low-risk, high-impact use cases.

Recommended starting points include:

• Writing, summarization, and explanation tasks
• Board reporting and executive summaries
• Internal documentation and communication
• Embedded AI tools within existing financial systems

The goal is to save time and improve efficiency without bypassing controls or introducing complexity.

The Bigger Opportunity for Nonprofit Finance Leaders

AI presents an opportunity for finance teams to shift their role within the organization.

Instead of focusing primarily on manual tasks, teams can:

• Provide faster and clearer insights
• Support strategic decision-making
• Improve communication with leadership and boards
• Reduce operational friction across finance processes

The result is a more proactive, strategic finance function that better supports the organization’s mission.