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AI Agent Deployment ROI

Deploy AI agents. Measure what they actually do.

Companies spend $2,068 per employee on AI but 67% still estimate ROI instead of measuring it. Rize tracks AI tool usage per employee, per project, automatically — turning deployment data into productivity proof the CFO can audit.

$2,068
Average AI spend per employee (2026)
67%
Of enterprises estimate AI ROI instead of measuring it
74%
Of AI value captured by top 20% of companies

The problem

The deployment-to-measurement gap

Every enterprise is deploying AI agents. Copilot, ChatGPT Team, Cursor, and custom GPTs are rolling out across departments. FinOps dashboards show the cost. License management tools show seat counts. But neither can tell you which employees saved time, on which projects, and whether the savings justified the spend.

The cost side is solved. Token metering, API billing, model routing — AI Cost Optimization (ACO) tools handle this well. Helicone, Langfuse, and Vantage track every API dollar.

The productivity side is a gap. Nobody measures which employee used which AI tool, for how long, on which project — and whether task duration actually decreased. That is the data the CFO needs, and ACO cannot provide it.

Rize fills this gap with Agent Token Tracking (ATT) — per-employee AI usage measurement captured automatically by a lightweight desktop agent. No manual logging. No surveys. No SDK instrumentation.

How it works

Agent Token Tracking — the employee layer

ATT captures four categories of data that FinOps dashboards miss: per-employee AI hours, per-project cost attribution, shadow AI discovery, and before-and-after task duration deltas. Rize runs in the background on macOS and Windows and tracks which AI applications each person uses alongside their regular work — automatically.

Per-employee AI usage

See exactly which team members use ChatGPT, Copilot, Claude, Cursor, and every other AI tool — how many hours per day, per week, per project.

Shadow AI discovery

78% of employees use unapproved AI tools. ATT detects them automatically because the desktop agent sees every application, not just the ones IT provisioned.

Per-project cost attribution

Map AI time to specific clients and projects. Know that Project X consumed 47 hours of Copilot this month — not just that your total Copilot spend was $15K.

Hours-saved measurement

Compare task duration before and after AI deployment at the individual level. This is the numerator of the ROI equation that cost-only tools cannot provide.

The framework

ACO → ATT → AYO

Foundation

ACO

AI Cost Optimization

Track token spend, API costs, and model routing. Know how much you spent on AI infrastructure.

“How much did we spend?”

Attribution

ATT

Agent Token Tracking

Map AI costs to individual employees and projects. Discover shadow AI. See adoption gaps.

“Who used it and for what?”

Yield

AYO

AI Yield Optimization

Measure hours saved per AI dollar per employee. Calculate productivity ROI the CFO can audit.

“What return per AI dollar?”

Most companies are stuck at ACO. The 20% that reach AYO capture 74% of AI-driven returns (PwC).

Why Rize

Rize ATT vs alternatives

Rize ATT
FinOps
Manual
Per-employee AI usage tracking
Self-reported
Shadow AI detection
Per-project cost attribution
Automatic
Team-level
Manual
Hours-saved measurement
Before/after
Estimates
No employee compliance burden
AYO yield calculation

Read more: How to Measure ROI After AI Agent Deployment · AI Cost Management: ACO to AYO · AI Productivity Metrics

“I installed it and forgot about it for two weeks. When I came back, everything was tracked. I could trust the data completely.”
Leonard Roussard
Leonard Roussard

Founder & CEO, Impulse Lab

Frequently Asked Questions

Measure ROI by tracking three inputs per employee: AI tool cost (licenses plus API usage), hours saved (captured via automatic time tracking), and fully-loaded labor cost per hour. Divide labor value saved by AI cost to get your yield ratio. Rize automates the hours-saved measurement through Agent Token Tracking (ATT), producing defensible numbers within 8 weeks.

Agent Token Tracking (ATT) is the practice of measuring per-employee AI tool usage and compute cost automatically. Unlike FinOps tools that track tokens at the API level, ATT captures which person used which AI tool, for how long, on which project — without manual logging or surveys. Rize pioneered ATT using its desktop agent to detect AI application usage alongside regular work sessions.

AI Cost Optimization (ACO) reduces infrastructure spend — tokens, API calls, model costs. AI Yield Optimization (AYO) measures productivity return per AI dollar per employee. ACO answers 'are we spending efficiently?' while AYO answers 'is each AI dollar producing measurable time savings?' Moving from ACO to AYO requires adding employee-level time tracking data via ATT.

Yes. Rize tracks which AI applications each employee uses and for how long without taking screenshots, recording keystrokes, or capturing screen content. It reads which application is in the foreground to measure AI tool time per person, per project. This privacy-first approach means employees adopt tracking willingly, producing more reliable data.

A team produces its first AI yield report within 8 weeks: 2 weeks for baseline task duration capture, 2 weeks for AI cost mapping, 2 weeks for post-deployment time comparison, and 2 weeks for yield calculation and analysis. Rize runs in the background from day one with zero employee setup required.

Have more questions? Contact us

Deploy AI agents with confidence. Let Rize measure what they produce.