AI impact: ROI

Compare the combined cost of your AI tools and engineering work against the stories, pull requests, and code your teams deliver.

Available at AI tools → AI impact → ROI

The ROI tab puts cost and output side by side, so you can see what your organization spends per unit of delivered work and whether that number is moving. It combines the token value of your AI coding tools with the estimated cost of engineering time, then divides it by the stories, pull requests, and code your teams ship.

This helps you answer questions your finance and leadership teams tend to ask: What are we spending per story or pull request? How much of our engineering cost is AI tools now? Is the AI spend translating into more output per engineer?

Pick a timeframe and optionally a team to drill into. Everything is bucketed by calendar month, and all amounts are shown in US dollars.

Total cost

The first chart stacks developer cost and AI cost per month, so you can see how the two move relative to each other. Alongside it you get the timeframe totals: developer cost, AI cost, AI cost per FTE per month, and AI cost as a share of total cost.

Throughput and cost per unit

Three sections pair a throughput metric with the matching cost per unit of output:

Section	Throughput	Cost
Issue throughput	Stories or epics completed per FTE per month	Cost per story or epic
PR throughput	Merged pull requests per FTE per month	Cost per merged pull request
Code throughput	Lines changed per FTE per month	Cost per line changed

Throughput is divided by developer effort rather than headcount, so growing or shrinking teams don't distort the trend. The cost charts stay stacked into developer cost and AI cost, which shows you whether a change in unit cost comes from AI spend or from engineering time.

Use the Stories and Epics tabs in the issue throughput section to switch between the two issue types.

Team breakdown

The table at the bottom breaks the same metrics down by team. Select a team to drill into its child teams, and download the table as a CSV.

Teams are attributed the pull requests and issues they own, and the AI cost and effort of their current members. If people switch teams, their past cost and effort move with them.

How the costs are calculated

Both cost components are estimates, and each has its own caveats:

• AI cost is the token value of your AI coding tool usage: the list price of the tokens consumed, based on the AI coding tool integrations. It isn't your invoice, and it doesn't include seat or subscription fees.

• Developer cost is estimated from developer effort and an organization-wide average: a team's monthly FTE multiplied by one twelfth of your configured average yearly developer cost.

To get developer cost, an organization admin needs to turn on Show estimated cost and set an Average yearly developer cost in Settings → Organization → General. The figure should cover salary, benefits, and overhead. Until it's set, the ROI tab shows AI cost only, and the cost-per-unit metrics reflect AI spend alone. Estimated developer cost is visible to admins only.

If you configure the average developer cost in euros, Swarmia converts it to US dollars at a fixed rate so both cost components share one currency.

What good looks like

Start with the AI cost share, because it tells you where your effort is worth spending. If AI spend is a small fraction of developer cost, the upside is in getting more out of the tools, not in trimming the tool bill: shaving a few percent off a small AI cost barely moves the total, while a real gain in throughput per FTE does. Cutting AI cost is worth the attention once it makes up a significant share of your total cost.

From there, read the tab as a trend rather than as a single month.

Is the AI spend paying off?

• AI cost share climbing while cost per unit falls. You're trading engineering time for tool spend and getting more out per unit of effort.

• AI cost share climbing while cost per unit holds or rises. The spend isn't translating into output yet.

How has the shape of the work changed?

The three unit costs often move in different directions. Read together, they tell you what changed about the work, not just whether it got cheaper.

• Cost per line changed falls while cost per merged pull request rises. Your pull requests are getting bigger: AI produces more code per change, but each change still needs a review. Check batch size and review time in AI impact: Code to see whether review has become the constraint.

• Cost per merged pull request falls while cost per story holds. The code is flowing faster, but there's no clear increase in customer-facing increments. That points at something outside coding, such as scoping.

What the numbers don't tell you

Cost per issue is the closest thing here to a business outcome, so it's also the one worth questioning: does one story or epic still represent the same amount of customer value it did a year ago? Teams that change how they work with AI tools might change how they split and size issues too.

Treat the unit costs as directional rather than exact. They measure output, not the value of what you shipped, so pair them with quality signals like DORA metrics. For the wider picture, see the guide on understanding the impact of AI tools.

Requirements and limitations

• GitHub Copilot, Cursor, or Claude Code integrations are required for AI cost.

• Issue throughput and cost per story require an issue tracker integration, with issues mapped to the story and epic issue types.

• Lines changed counts merged pull requests and excludes auto-generated files.

• FTE follows the usual effort rules: contributors with fewer than 10 monthly activities are excluded, and each person contributes at most 1.0 FTE per month. Contributors need their Git and AI tool identities connected in the Contributor settings for their cost and effort to land on a team.

• The current, incomplete month is included in the charts, so the latest data point moves as the month fills in.

Frequently asked questions

Why don't the figures match what we pay for AI tools?

AI cost is token value: the list price of the tokens your tools consume, including the harness. Seat and subscription fees aren't included, and on plans where heavy usage doesn't increase your bill, token value won't match your invoice.

Why is developer cost missing?

Either cost estimation isn't set up yet, or your user role doesn't allow you to see estimated cost. Admins can turn it on in Settings → Organization → General.