The ROI of AI Agents in Accounting & Finance: Multiple Studies Show Widespread Adoption and Positive Returns

Key Takeaways

• Recent research from Forrester, Google Cloud, and FloQast points in the same direction: AI and finance automation are already producing measurable returns, often within the first year or even within six months.
• In financial services, AI agent adoption is already moving into production, with 53% of surveyed executives saying their organizations are using AI agents live and 40% reporting they have launched more than 10.
• The biggest ROI themes are speed, productivity, accuracy, customer experience, and reduced manual effort, not just labor savings.
• Customer service and experience leads AI agent use cases in financial services at 57%, but finance and accounting are also near the top at 46%, showing that ROI is not limited to front-office functions.
• The pressure to adopt AI is real, but in regulated industries, the winners will be the organizations that pair AI investment with governance, security, and clear documentation.

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Why the ROI Conversation Around AI Has Changed

A year ago, many AI conversations in finance were still theoretical. Now the conversation is more practical. Leaders want proof that AI can save time, improve output, and justify investment.

That shift shows up clearly across all three sources. FloQast’s commissioned Forrester Total Economic Impact study found a 275% ROI, payback in under six months, and measurable reductions in close time and audit costs. Forrester’s broader finance automation work makes a similar point: finance teams are already seeing value through faster processes, lower costs, and more time for strategic work. Google Cloud’s financial services research found that 77% of surveyed executives said their organizations were achieving positive ROI from gen AI within the first year.

In other words, AI ROI is no longer a future-state argument. For many organizations, it is already happening.

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What the Studies Agree On

The details differ, but the pattern is consistent.

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AI Delivers the Most Value When Tied to Real Workflows

AI delivers the most value when it is tied to a real workflow problem. In FloQast’s Forrester TEI study, the value came from concrete accounting outcomes: close time cut in half, external audit fees reduced by 30%, internal audit efficiency improved by 15%, and $2.8 million in total cost savings.

In Forrester’s broader finance automation analysis, the benefits include freeing up finance talent, reducing system costs, improving working capital, and supporting compliance. Google Cloud’s financial services research shows similar gains in productivity, customer experience, security, and growth.

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ROI Comes From Reducing Friction, Not Just Cutting Costs

The strongest ROI stories are not just about cutting headcount. They are about reducing friction. Faster closes, fewer manual reviews, better accuracy, more usable data, and more time for higher-value work show up again and again.

That is a much more credible ROI case for finance leaders than vague promises about “transformation.”

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Adoption Is Already Happening at Scale

Adoption is moving quickly. Google Cloud found that 53% of surveyed financial services executives said their organizations are already using AI agents in production, and 40% said they have launched more than ten. Nearly half said they expect at least 50% of future AI budgets to go toward AI agents.

This is no longer an early experiment phase. It is a competitive shift that is already underway.

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Where AI Agents Are Driving the Most Value

The Google Cloud and National Research Group data are especially useful here because they break out where financial services organizations see the most value from AI agents.

The top business areas include:

• Customer service and experience (57%)
• Marketing (48%)
• Security (46%)
• Finance and accounting (46%)
• Fraud management and detection (43%)
• Risk management (42%)

This ranking shows two things. Companies are starting with high-volume, visible use cases, but they are also moving into more sensitive and regulated areas.

For finance teams, the 46% figure for finance and accounting stands out. It shows that the AI agent value is not limited to customer-facing workflows. Finance organizations are already using AI in meaningful ways, in areas where controls, auditability, and accuracy matter a lot more than hype.

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Why Financial Services Firms Feel Pressure to Move Now

Financial services have always been cautious with new technology. That is part of the job. But the data shows the industry is no longer waiting. This recent research found:

• 79% of executives reported increased gen AI spend
• 61% said their organizations are increasing investment in gen AI initiatives
• 53% are already using AI agents in production

This creates real pressure. Banks, lenders, and insurers do not want to fall behind with slower processes or higher manual costs.

At the same time, they cannot afford to move without controls in place. That tension will define how AI is adopted across financial services over the next few years.

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What ROI Actually Looks Like in Practice

The best part of the FloQast Forrester TEI study is that it puts hard numbers around a workflow most accounting teams know well.

According to the study, enterprise accounting teams using FloQast achieved:

• Close time cut in half
• 30% reduction in external audit fees
• 15% improvement in internal audit efficiency
• Payback in under six months
• $2.8 million in total cost savings
• $1.2 million in preparer time savings
• $429,000 in reviewer efficiency gains

The full report is available to download for free. This kind of ROI is easier to prove in environments where the work is repetitive, time-sensitive, and easy to measure. Accounting fits that description well.

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The Bigger Lesson From Forrester’s Finance Automation Research

Forrester’s broader finance automation blog makes a similar argument from a different angle. It frames ROI around freeing finance talent for strategic work, lowering the cost of outdated systems, improving working capital through earlier payment discounts, and staying compliant across countries. It also models a fictional global enterprise that achieved 111% ROI, with payback in under six months, after implementing modern accounts payable automation.

That matters because it broadens the conversation beyond one product or one workflow. The common thread is that automation pays off when it improves the economics of finance operations. AI agents can make that payoff more visible and faster, but the underlying logic is still operational: less manual effort, better execution, better controls, and more capacity for analysis.

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The Risks Get Bigger as the Value Gets Bigger

One thing the Google Cloud article makes clear is that financial services firms are moving AI into areas like security, fraud, risk, and finance itself. That is where the upside is real, but it is also where the risks get harder to ignore.

In regulated environments, responsible AI usage has to account for more than speed. Teams need to think about data privacy, model accuracy, explainability, access controls, audit trails, regulatory exposure, and third-party risk. Google Cloud’s research reflects this concern as well: when evaluating LLM providers, respondents ranked data privacy and security first at 43%, ahead of systems integration at 29% and regulatory compliance at 28%.

That does not mean finance teams should slow-walk adoption forever. It means ROI and governance have to scale together.

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Smart Guidelines for Responsible AI Agent Adoption

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Start With Real Use Cases

Focus on workflows where the outcome is measurable and the process is well understood.

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Document Where AI Is Used

Identify what tools are in use and what data they touch.

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Assign Ownership

Someone needs to be responsible for oversight and governance.

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Review Outputs Before They Matter

AI outputs should be validated before they impact reporting or customer outcomes.

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Evaluate Vendors Carefully

Make sure providers can clearly explain how they handle privacy, security, and controls.

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Why This Matters for FloQast Readers

The clearest takeaway from these studies is that AI ROI is real, but it is not automatic. Organizations see the best returns when AI is tied to specific workflows, measurable outcomes, and strong governance.

That is especially relevant for finance and accounting teams. These are functions where time savings are visible, process bottlenecks are painful, and control failures are expensive. Done well, AI agents can help reduce manual work, improve consistency, and give teams more time for analysis and decision-making. Doing poorly can create new audit and compliance problems.

FloQast sits right in that intersection. For teams in financial services and other regulated industries, the opportunity is not just to use AI, but to use it in a way that is structured, accountable, and built for finance.

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See What Audit-Ready AI Looks Like in Practice

AI adoption is moving fast, and the ROI case is getting stronger. The next step is making sure your team can capture that value without adding unnecessary risk.

Download the free Forrester TEI study to see the full findings, and get a demo to see how FloQast helps accounting teams build and use AI agents inside real, auditable workflows.

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