---
title: "AI dollar impact"
canonical_url: "https://docs.getdx.com/reports/ai-dollar-impact/"
md_url: "https://docs.getdx.com/reports/ai-dollar-impact.md"
last_updated: "2026-05-22"
---

# AI dollar impact
The **AI dollar impact** tab on the AI Impact report translates your organization's AI investment into a concrete dollar figure. Rather than debating whether AI is "worth it" in the abstract, leaders can see a financial picture of what AI is producing, what it costs, and what the net is—making board-level reporting and budget conversations significantly easier.

> This tab requires both [AI Code Insights](https://docs.getdx.com/ai-code-insights/overview/) (deployed to developer machines) and AI time savings responses from DX snapshots.

![Dollar impact tab in DX](https://docs.getdx.com/assets/images/reports/ai-dollar-impact.png)

## When to use AI dollar impact

This report helps leaders:

- **Quantify the financial return on AI tools** — Move beyond adoption metrics to a net dollar figure that accounts for both the value AI creates and the costs it introduces.
- **Justify AI tool spend** — Use concrete, defensible numbers for budget conversations, board reports, and ROI reviews.
- **Identify where AI delivers value vs. where it doesn't** — Break down impact by team to see which parts of the organization are getting the most return and where oversight costs are eating into gains.

## How net AI dollar impact is calculated

The headline metric is an annualized net dollar figure that combines four components:

**Net AI dollar impact = Efficiency gain + Agent output − Oversight cost − AI tool spend**

### Efficiency gain

The dollar value of time saved by developers using AI tools. This is derived from DX snapshot responses where developers self-report how many hours per week AI tools save them.

The calculation factors in:

- **Average FTE salary** (configurable in report settings, default $150,000)
- **Developer count** from snapshot respondents
- **AI adoption rate** — the share of developers actively using AI tools (based on your configured "active AI user" tags)
- **Percentage of time spent on development** (configurable, default 65%)
- **Self-reported hours saved** from snapshot behavioral responses

### Agent output

The dollar value of work completed autonomously by AI agents, estimated by treating agent-authored PRs as human-equivalent work.

The calculation factors in:

- **Agent PR count** — PRs where the code is AI-authored (bot-authored PRs count fully; partially AI-authored PRs are prorated by their AI code percentage)
- **Median human work time** — the median time from first commit to ready-for-review across human-authored PRs in the same period, used as a baseline for what this work would have cost a human
- **Hourly salary** derived from the configured FTE cost

### Oversight cost

The cost of reviewing and fixing AI-generated output. This is subtracted from the total because human oversight of AI work is a real cost that offsets the gains.

The calculation factors in:

- **Review time** — estimated from the number of review comments on agent-authored PRs (approximately 5 minutes per comment)
- **Rework from reverts** — reverted agent PRs multiplied by the median human cycle time, representing the cost of undoing and redoing failed AI work

### AI tool spend

The annualized cost of AI tool licenses, configured in report settings. This is split proportionally across the organization based on headcount in scope.

## Breakdown by team

Below the summary, a breakdown table shows all four components and the net impact for each team (or other aggregation). Use this to compare:

- Which teams are seeing the highest efficiency gains
- Where agent output is most concentrated
- Where oversight costs are highest relative to output

The table supports CSV export and can be expanded to drill into sub-teams.

## Breakdown modal

Clicking **View breakdown** on the net AI dollar impact figure opens a detailed receipt-style view showing each component with its inputs:

- **Human efficiency gain** — engineer count, AI adoption %, and speed boost multiplier
- **Human-equivalent agent work** — agent PR count and average cycle time
- **Human oversight & remediation** — average review time and revert rate
- **AI tool costs** — configured tool names and annualized spend

## Report settings

The Dollar impact calculation depends on several configurable inputs, accessible via the settings icon on the AI Impact report:

| Setting             | Description                                                              | Default  |
| ------------------- | ------------------------------------------------------------------------ | -------- |
| Average FTE salary  | Fully loaded annual cost per developer, used in all dollar calculations. | $150,000 |
| Dev time %          | Percentage of a developer's time spent on development work.              | 65%      |
| AI tools            | List of AI tools with their annual license costs.                        | $0 each  |
| Active AI user tags | Tags that define which developers are considered active AI users.        | —        |

If AI tool costs are all set to $0, an admin banner will prompt you to configure them so the total AI spend component is reflected accurately.
---

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