AI agents in finance

Artificial intelligence (AI) agents are transforming the financial industry at an explosive rate. Research indicates the global market size will grow from $691.3 million in 2025 to $6.7 billion by 2033, reflecting a 31.5% compound annual growth rate.

This guide explores the state of AI agents in finance, including how they work today, their impact on financial service providers, and some types to consider implementing.

What are AI agents in finance?

AI agents are software systems that can manage a complex task with minimal human intervention. Their generative AI automation supports executive function and multi-step reasoning, letting them initiate workflows and see them through to completion.

As a result, AI agents in finance are capable of streamlining entire functions. For example, one might handle almost all of your accounts payable (AP) processes, including:

• Extracting key data from incoming invoices
• Matching invoices against purchase orders
• Updating accounting records with journal entries
• Routing documents through approval chains
• Initiating batch payments via ACH after authorization

In addition to automating work, many conversational AI agents in finance apply machine learning (ML) to your data. This allows them to become increasingly accurate and insightful over time, providing more value the longer you use them.

On the surface, AI agents look similar to traditional AI chatbots, using natural language processing (NLP) to simulate human conversation. However, chatbots struggle with complexity and can often only handle rule-based tasks.

Though often discussed individually, most AI agents in finance are part of a broader platform. Integrating that platform with the rest of your tech stack lets agents pull data and manage activities across existing systems.

How AI agents are changing the financial services industry

The financial services are no stranger to automation, but its applications in the industry have long been limited. Systems often relied on robotic process automation (RPA), which is primarily designed for repetitive tasks, like data entry, not complex workflows.

Today’s AI agents are much closer to genuinely autonomous digital robots. Instead of just following pre-defined rules, they can think and act independently, letting them take over many more finance functions that previously required human oversight.

In addition to improving operational efficiency, financial service providers are using these technological developments to improve the customer experience and deliver more value. For example, some of the most significant ways include:

• Data visibility: AI agents can aggregate and reconcile vast amounts of financial data across tech stacks, creating a real-time source of truth. Instead of waiting for month-end reports, users can always make informed decisions.
• Planning and analysis: Agentic AI solutions excel at processing vast quantities of data and identifying patterns that humans might not. This greatly streamlines techniques like scenario planning, which can help users refine tactics.
• Advanced personalization: With a natural language interface (NLI) and strong reasoning skills, an AI agent can converse like humans. As a result, users can ask them questions directly and get deeply personalized responses.

This is reducing the burden of manual work in the financial sector. As a result, professionals are increasingly free to focus on more valuable tasks, such as regulatory compliance, exception management, and strategic decision-making.

Finance AI agents worth considering

AI agents in finance often specialize in a handful of financial operations. Not only does this help them support stronger capabilities within their primary workflows, but it also helps users organize their AI adoption efforts.

For example, splitting functionality across multiple AI agents makes it easier to pursue a phased implementation approach, reducing the risk of company-wide disruption. It also makes solutions more modular, supporting customization.

As a result, which agentic AI tools are worth considering depends on which aspects of your finance operations you’d like to automate. To narrow things down, start by looking for your most significant bottlenecks and inefficiencies.

These are processes that consistently require significant manual work or are prone to error. Financial AI agents may not always map onto them perfectly, but you’ll often be able to find solutions that address most of the workflows efficiently.

Below, we’ll explore Zeni’s suite of AI finance agents to help you determine what kind you might benefit from the most.

1. AI Accountant Agent

The AI Accountant agent is designed to fill the role of a traditional staff accountant while working at the speed and scale of AI. It automates many traditional bookkeeping and accounting workflows, including:

• Transaction categorization: The agent records your activities intelligently and in real time. This includes matching transactions to supporting documentation like receipts, ensuring your books remain accurate and audit ready.
• Learning and correction: Using machine learning (ML), the agent continuously studies patterns in your financial activities. This makes it more accurate over time and better at catching errors like duplicate vendors or misclassified transactions.
• Journal entries: The AI model schedules and posts recurring journal entries, reducing manual work. For example, that may include accruals or depreciation, amortization, and loan schedules.
• Automatic flux analysis: The agent monitors your financial activities and calculates variances, highlighting those that rise above a certain materiality threshold. It also offers potential explanations for those changes.

If you’re looking for more traditional accounting services, such as tax planning and preparation, a traditional professional may be a better fit. Zeni offers tax services as part of our AI-powered financial management platform.

2. AI CFO Agent

The AI CFO Agent is built to facilitate financial planning and analysis (FP&A) at the executive level. It can’t serve as a true finance leader like a human professional, but it supports several key FP&A functions, including:

• Predictive analytics: The agent uses historical data to make informed predictions about your financial performance. For example, it can calculate your burn rate, estimate your cash runway, and project your cash zero date.
• Strategic financial planning: You can prompt the agent using plain language and instantly receive responses based on your real-time financial data. For example, you might ask where you can cut expenses without slowing growth.
• Ongoing financial insights: The agent provides ongoing visual dashboards of key performance indicators (KPIs). It can also schedule recurring financial reporting, like month-end summaries, without repeated prompting.

If you need financial leadership beyond what an AI tool can provide, consider fractional CFO services. They can be an agile solution for finance teams at growing businesses that can’t justify the cost of a full-time finance executive.

3. AI Expense Agent

The AI Expense Agent is designed to automate your expense management function. Separate from transaction categorization, this refers to the process of managing employee spending. For example, the Expense Agent supports workflows like:

• Expense tracking: The agent captures all relevant expense data, including key details and supporting documentation. In addition, it generates customizable reports that provide visibility into spending across your business.
• Policy enforcement: Once you design your expense policy, the agent monitors employee transactions continuously and flags deviations immediately. This enhances fraud detection and helps prevent out-of-policy charges.
• Employee reimbursements: The Expense Agent routes reimbursement requests through a predefined approval workflow. It can also process payments once authorized, issuing reimbursements via ACH at no additional cost.

4. AI Bills Agent

The AI Bills Agent is the accounts payable counterpart to the AI Expense Agent. Instead of managing your employee spending, it focuses on payments to vendors. For instance, here are some of its primary capabilities:

• Invoice capturing: With permission, the agent automatically scans your email and identifies every invoice you receive. In addition to extracting the key details, it references the AP Aging and flags any unpaid pills.
• Journal entry booking: The AI system validates incoming invoices, flagging any potential duplicates for review. It also matches them against purchase orders and transfers the details directly to your general ledger. 
• Vendor payments: The Bills Agent forwards vendor bills to the appropriate approvers according to your customized routes. It can also schedule payment issuance strategically to help optimize cash flow. Like employee reimbursements, they can go out as $0 ACH transfers.

Implementing AI agents in finance with Zeni

Zeni is a financial management platform designed to meet all your finance team’s needs in one place. In addition to AI agents, users can access an integrated suite of other offerings, including everything from bill payment software to fractional CFO services.

Schedule a free demo today to see Zeni in action.

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