6 AI agents transforming finance workflows

Finance teams are under pressure to move faster, operate leaner, and deliver sharper insights while navigating complex regulations and rising expectations. But outdated systems and disconnected data often get in the way. Too much time is still spent reconciling transactions, tracking down documentation, and piecing together answers from different tools.

AI agents offer a smarter approach. These intelligent systems understand business context, surface the right information at the right time, and help teams execute multi-step financial workflows with more speed and confidence. Whether it’s closing the books, prepping for audits, or analyzing variances, finance AI agents can give teams the time to focus on what matters most.

This blog explores what’s possible when finance teams build their own AI agents using platforms like Glean. The examples that follow are meant to spark ideas — showing how purpose-built agents can reduce manual effort, improve accuracy, and help teams get more value from the tools and data they already have.

What are AI agents for finance teams?

AI agents are intelligent systems designed to help finance teams complete complex, multi-step tasks with greater efficiency. They use large language models, retrieval-augmented generation (RAG), and deep integration with company systems to understand questions, find answers, and assist with actions through a natural language interface.

Unlike traditional automation, AI agents can interpret unstructured data, adapt to different formats, and reason through ambiguity. They understand intent, pull from verified sources, and deliver context-rich responses that help teams move faster with more confidence.

When built on platforms like Glean, these agents can securely connect to the tools and knowledge your teams already use, including ERPs, contract repositories, and shared drives. They can retrieve the right documentation, identify patterns, and suggest next steps, all while respecting role-based access controls and compliance requirements.

Core capabilities of effective AI agents

The most effective AI agents deliver results your team can trust. Achieving that takes more than a powerful model. It requires real business context, secure system access, and clear guardrails. The capabilities below make that possible.

• Natural language understanding: Ask questions like “What caused the increase in our Q2 OPEX?” and get a clear, supported answer that links directly to relevant data and documents.
• Contextual reasoning: Agents can analyze trends, reference policies, and explain outcomes based on what’s happening inside your business, not just generic benchmarks.
• Multi-system access: When agents connect to the tools your team already uses, like Workday, NetSuite, OneDrive, and SharePoint, they can deliver useful responses without requiring you to dig across systems.
• Built-in governance: Role-based access, permission-aware indexing, and audit logs help agents maintain compliance and ensure sensitive data stays protected.

Glean’s Work AI platform is designed to support all of the above. With 100+ connectors and real-time permission syncing, it gives finance teams the foundation to build agents that are not only helpful but secure, scalable, and reliable.

How AI agents are transforming finance workflows

AI agents give finance teams a new way to work — one that reduces friction, eliminates busywork, and helps teams make faster, more confident decisions. By tapping into real business context, these agents can support complex processes, surface critical insights, and keep information aligned across systems. They’re designed to be secure, compliant, and adaptable to your organization’s structure and tools.

Here are a few examples of where agents can make an immediate impact:

• Reconciliation and close: Match entries across systems, identify discrepancies, and reduce the manual lift during close.
• Variance analysis: Explain budget vs. actual changes using supporting content like approval memos, invoices, or contracts.
• Audit prep: Organize documentation, summarize control evidence, and streamline audit responses.
• Policy and compliance: Deliver the most current procedures by team or region, and flag outdated materials for review.
• Reporting: Generate daily or quarterly updates automatically, with links to data sources and callouts for unusual activity.

6 strategic use cases for AI agents in finance

These six examples show what’s possible when finance teams use Glean to build their own AI agents. Each one is designed to address a specific workflow challenge, helping reduce manual work, increase accuracy, and support compliance across functions like FP&A, audit, procurement, and reporting.

Use these ideas as a starting point to imagine how agents can securely connect your systems, respond in natural language, and deliver measurable impact.

1. Financial risk assessor

Identifies potential financial risks during budget planning and forecasting.

• Problem to solve: Finance leaders often lack a clear, unified view of where over- or under-investment is occurring, making it difficult to rebalance budgets with confidence.
• What it does: Reviews planning data, spend projections, and performance trends across tools like NetSuite and internal models to highlight investment gaps or inefficiencies and suggest potential reallocations.
• The impact: Improves financial planning accuracy and capital efficiency, enabling teams to adjust spending with clarity and foresight.

2. Investment researcher

Aggregates insights from internal and external data sources to inform strategic investment decisions.

• Problem to solve: Teams managing investment portfolios or evaluating new opportunities spend hours gathering market trends and comparable data across disconnected systems.
• What it does: Collects and summarizes market data, financial benchmarks, and internal analyses to provide structured insights aligned with corporate investment criteria.
• The impact: Speeds up research and improves decision quality by ensuring every analysis is grounded in current, reliable data.

3. Customer churn assessor

Identifies potential churn or downsell risks that could affect forecasts and revenue planning.

• Problem to solve: Finance and RevOps teams often receive lagging indicators of churn risk, creating last-minute surprises in forecasting and reporting.
• What it does: Analyzes customer signals from tools like Salesforce and Slack, including ticket volume, renewal patterns, and sentiment trends, to flag early warning signs.
• The impact: Improves forecast accuracy and allows finance leaders to work proactively with go-to-market teams to protect revenue.

4. Accounts payable matching agent

Extracts and matches invoice data to purchase orders and ledger entries automatically.

• Problem to solve: Manual AP matching is slow and error-prone, especially when information is spread across systems or formatted inconsistently
• What it does: Reads invoices, identifies coding fields, and matches them to purchase order line items and expense categories to reduce manual reconciliation.
• The impact: Reduces processing time, increases accuracy in reporting, and ensures compliance with purchasing and audit requirements.

5. Expense planning agent

Helps employees navigate expense policies and plan costs efficiently.

• Problem to solve: Employees often struggle to estimate costs or find clear guidance on travel and spend policies, leading to delays and back-and-forth with finance.
• What it does: Uses policy data from sources like SharePoint and internal guidelines to model costs, flag potential compliance issues, and provide clear recommendations.
• The impact: Saves time and minimizes policy violations by giving employees direct, self-service access to verified financial guidance.

6. Due diligence agent

Streamlines the completion of supplier, vendor, and investor questionnaires by leveraging prior submissions.

• Problem to solve: Responding to repeated due diligence requests requires manual effort and coordination across departments.
• What it does: Retrieves existing DDQs, previous responses, and relevant documentation to prepopulate new questionnaires and ensure accuracy and consistency.
• The impact: Reduces time spent on repetitive requests and improves the quality and speed of external reviews.

Beyond AI agents: How Glean connects every part of finance

Finance AI agents automate key workflows across planning, reporting, and operations. Together with Glean Search and Glean Assistant, they create a single, connected foundation for enterprise-wide financial intelligence.

Glean Search connects to every financial data source so teams can instantly find reports, budgets, contracts, or prior analyses without switching between tools. With permission-aware access, it delivers verified answers drawn directly from governed company data.

Glean Assistant makes that information conversational. Finance professionals can ask questions like “What were last quarter’s top budget variances?” or “Show me our latest audit documentation for Q2,” and receive precise, context-rich answers sourced from across internal systems.

Together, Search, Assistant, and Agents give finance teams a unified way to access, understand, and act on their company’s financial knowledge. They remove the busywork from forecasting, reporting, and compliance so finance leaders can stay focused on decisions that drive the business forward.

Why finance teams choose Glean

AI agents are only as effective as the data and context they’re built on. Glean’s Work AI platform is designed to unify company knowledge, apply AI responsibly, and enable secure, scalable automation across teams.

• Enterprise-grade security: Glean enforces zero-retention policies when using LLMs and mirrors existing permissions in real time, keeping sensitive financial data protected at every step.
• Fast time-to-value: With native integrations across your existing tools, Glean gets up and running in weeks. There’s no need for long implementation cycles or costly professional services.
• LLM flexibility: Glean supports leading models from Azure OpenAI, Google Vertex AI, and Amazon Bedrock, so you can choose the providers that align with your compliance and governance needs.
• Proven results at scale: In a Forrester TEI study, companies using Glean saw a 141% return on investment over three years, with millions saved through increased productivity and faster onboarding.

By transforming disconnected systems and scattered knowledge into intelligent workflows, Glean helps finance teams work faster, reduce risk, and make better decisions across the business.

A smarter way to scale finance operations

AI agents have become an essential part of modern finance teams. Their real value doesn’t come from automating tasks for the sake of it. It comes from giving finance teams the context they need to move faster, reduce risk, and make better decisions.

That’s where Glean makes the difference. By connecting the tools you already rely on and grounding agents in your company’s data, Glean enables finance teams to scale their work without adding new layers of complexity. With the right foundation in place, your team can lead the way in defining how modern finance gets done.

Ready to explore what AI agents could do for you? Request a demo or download the financial services whitepaper to learn more.