How to Measure the ROI of an AI Agent in Your Business

By now, you’ve seen it all: promises that AI threatens humanity’s existence to hopes for a new golden age of superintelligence and complete automation. Truth, like business, operates somewhere in the middle, avoiding the extremes of human imagination.

As you implement AI in your operations, it’s fundamental to understand the actual value you’re extracting from it, especially as many tools can be expensive but underdeliver. This article offers formulas and angles to analyze your business data. These will help you track how AI is transforming your operations and workflows, driving real growth.

How to Measure the ROI of an AI agent

Combine the following tracking strategies to understand the impact of AI in your business. These include such metrics as:

• Time savings

• Output increase

• Cost reduction

• Efficiency

• Team utilization

• Revenue growth potential

Let’s take a look at each ROI metric in-depth in the section below. 

Time Savings

The easiest and most popular angle pushed everywhere is time savings, where AI automates time-consuming and repetitive tasks. If you were managing a kitchen, this would be equivalent to automatically slicing ingredients to prepare dishes faster.

Major time-wasters include filtering emails, responding to low-complexity customer service requests, or reporting tasks that involve summarization.

Run a pre-AI benchmark, tracking task completion times and the fully-loaded salary of the responsible person or employee class. Then, implement the AI agents or automation tools, and keep measuring how long each task takes to complete.

Once you have a good data set, run the following formula to understand your time (and money) savings:

Time saved per task × number of tasks per month × fully loaded hourly wage

For example:

Task time dropped from 60 minutes to 5 minutes

100 tasks/month × (55 mins ÷ 60) × $50/hr = ~$4,583/month saved.

Example Use Case: Due Diligence Agent

The due diligence AI agent saves teams time by eliminating manual research and reporting during high-impact financial transactions

Use Case Overview

Output Increase

Sometimes, you implement a new AI agent and notice task times remain the same. Before scrapping this initiative, consider that some tasks are already time-optimized and can’t take any less to complete. But, with AI, total output increases, requiring a different approach to calculate ROI.

In our kitchen management metaphor, increasing output is serving 200 meals per night instead of 150. Real-world tasks in this category include solving complex customer support requests, content operations, and data input tasks.

Start with a pre-AI benchmark. Track the following metrics:

• Tasks completed per person per hour

• Tasks completed per team per hour

There are two options for calculating output increase. Option 1 is assigning a direct dollar value to each task: if each customer support ticket solved is worth $10, an increase of 3,000 more tickets processed equals $30,000.

Option 2 is using a strategic business value score for tasks with a value that’s harder to determine, such as preparing reports. It requires more care and creativity, usually needing your own metrics. For example:

Team processes 1,500 more transaction records per month, 13% higher accuracy

The internal metric is “every 1% increase in reporting accuracy correlates with a 0.5% reduction in budget overrun across departments”

For an average monthly budget of $2M with an historical overrun rate of 8%, a 13% increase in accuracy reduces overrun by 6.5%.

This corresponds to $130,000 in risk avoidance or operational savings.

Example Use Case: Video to Blog Generator

The Video-to-Blog post generator allows you to generate blogs from videos in seconds, greatly increasing content output

Use Case Overview

Cost Reduction

Removing time and output from the variable, implementing AI can reduce costs. In industries where it’s difficult or costly to find or retain talent, you can recoup lost productivity and keep growing. In the kitchen setting, this means automating one line cook’s work, so you don’t need to hire an extra one.

As always, start with a pre-AI benchmark of employee productivity matched with their fully loaded cost (salary + benefits + overhead). For example, if a customer support agent processes 4,000 tickets on average per month and costs $55k per year, every time AI processes 4,000 tickets in a month, you’d save that amount. For a more holistic view, consider HR costs for job postings, interviews, and onboarding.

This is a good time to mention AI error rates: expect mistakes. Incorporate that into your ROI calculation by tracking failed AI workflows that humans had to handle or correct. Deduct that from total productivity, and rerun the formula.

When prioritizing AI agents or workflows to upgrade, consider the ROI. A 1% accuracy increase in one agent could save $5k, while in higher-value ones, up to $20k.

Example Use Case: Loan Underwriting Agent

The Loan Underwriting AI agent automatically analyzes borrower financials during the financing process, eliminating the need for a large team of underwriters

Use Case Overview

Efficiency

As we progress through each category, it becomes harder to clearly pin down the value of AI automation, but there are still strategies we can use. 

For efficiency, we’re not just looking at less time spent, higher output, or cost reduction: we’re looking towards high-value workflows and skilled teams, where using time more efficiently through automation or AI is the real ROI driver.

In the kitchen metaphor, this means your senior chefs can now make 5 high-quality dishes instead of 3. The tasks that fall into this category are connected with strategic decision-making, deep reporting, and creative tasks.

First, establish a pre-AI benchmark on team productivity. Track total tasks completed and total time worked. You can also track the number of tasks per person per hour or deliverables per day. Once you have good data, implement AI and keep tracking changes to these metrics.

When you’re ready to track efficiency, run the following formula for both the pre-AI data and the post-AI data:

Efficiency = Total Tasks Completed ÷ Total Time Worked

Then, compare both benchmarks:

Efficiency Gain (%) = ((Post-AI Efficiency - Pre-AI Efficiency) ÷ Pre-AI Efficiency) × 100

Since this is percentage-based, you can clearly see the change.

Example Use Case: Lead Scoring Agent

The Lead Scoring Tool scores leads for sales teams, so they can focus on selling to prospects rather than manual research. 

Use Case Overview

Team Utilization

Now that your highest-skilled, highest-performing workforce is efficient, it’s time to further clean their schedule of tasks that weigh them down. At the same time, you can factor human skill and experience to allocate more time based on strengths.

In the kitchen metaphor, this is ensuring that your top chef spends over 80% of her time on signature dishes, not on slicing ingredients or managing the kitchen. And, for all top chefs, assigning them to the signature dishes each does best.

Using AI at this stage usually requires more development time, as the workflows at this level are highly personal, matched to product or service constraints, and fundamentally what makes your business and teams unique.

Devising end-to-end automation or human-in-the-loop frameworks takes time, but it may be possible to automate the lower areas of reasoning for each job description, equipping employees with high-quality AI copilots. This means ROI is further down the line, as there’s a learning curve for your teams and trial and error for AI tool developers.

Start tracking team utilization by categorizing tasks and monitoring the time each employee and team spends on each type of task.

Utilization (%) = (Time Spent on High-Value Tasks ÷ Total Work Time) × 100

Identify the task category that brings the most value to your business and automate other less valuable tasks. If you’ve implemented automation across your company, junior employees may now have more time, so delegate non-automatable tasks (due to AI technology limitations or ongoing solution development), freeing senior staff’s time.

Put utilization and core business metrics side by side. When your top teams spend more time on high-value tasks, how does it impact the top KPIs?

Use Case: Investment Memo Generator

The Investment Memo Generator empowers finance teams to on more high priority tasks, instead of manual research and report writing

Use Case Overview

Unlocking ROI with AI

ROI calculation is where the truth lives, beyond optimistic marketing and doom-and-gloom conjecture. Constant tracking and improvement will help implement AI across your business, unlocking productivity gains and making you more competitive.

The insights in this article are used daily at Stack AI. A generative AI platform for AI agents and workflow automation, it has a dedicated team to help clients build solutions and track ROI as they do so. A growth partner beyond powerful software, it helps transform each dollar you invest into tangible productivity, growth, and revenue.

Learn more about partnering with Stack AI to grow with new technology.