AI Cost Tracking · Worklytics
See exactly what you spend on AI tools, who is using them, and where licensed seats go to waste — broken down by tool, team, and token.
Get a demoSee sample reportAI cost tracking is the practice of monitoring, attributing, and optimizing what your organization spends on AI tools — covering seat licenses, variable usage fees, and token consumption across every platform your employees use.
Unlike API billing dashboards built for engineers, Worklytics tracks AI cost through a workforce lens: how many licensed seats are actively used, which departments drive token spend, and whether the tools you're paying for are actually delivering value.
The result is a single weekly view of your AI investment — broken down by tool, by team, and by model tier — so IT, finance, and HR leaders can make faster decisions together.
Example: enterprise with 2,500+ employees across 7 AI tools
Total Monthly Cost
Fixed seat licenses + estimated variable usage charges
$67.2K
$62.6K fixed · $4.6K variable
Enabled Seats
Total paid subscriptions assigned across all AI tools
2,520
7 tools across the org
Active Users (MAU)
Accounts that used any AI tool at least once this month
2,176
of 2,520 enabled seats
Seat Utilization
Active users ÷ enabled seats — low utilization = wasted spend
86%
344 seats inactive this month
Cost by tool
For each AI tool your organization uses, Worklytics surfaces the number of paid seats, monthly active users, seat utilization rate, fixed monthly license cost, and estimated variable usage cost for consumption-based tools.
Variable costs are derived from token volume and per-model API rates — so you can see the real cost of ChatGPT Enterprise or Claude usage, not just the license invoice.
Token consumption
For tools with usage-based pricing, cost depends entirely on which models employees are choosing. Claude Opus and GPT-4o are significantly more expensive per token than their lighter counterparts.
Worklytics shows token consumption broken down by model tier, so you can see where cost-efficiency improvements are possible without sacrificing capability.
Take action
Claude users average 48K tokens/week, with 25% going to Opus. Shifting even 10% of Opus traffic to Haiku for simpler tasks could reduce variable Claude costs by ~$65/wk.
Cost efficiency
Not all AI spend is equal. A tool with high monthly cost but low measurable output is a renewal risk. A tool with modest cost but high utilization and demonstrable task impact is a strategic asset.
Worklytics surfaces the outliers in both directions by correlating AI tool cost with estimated value generated — using task completion signals from your collaboration data.
Take action
Microsoft 365 Copilot has the largest gap between licensed seats (500) and WAU (442) — a right-sizing conversation at renewal could free ~$1.7K/mo.
Worklytics connects to your AI platforms via API — Copilot, Gemini, ChatGPT Enterprise, Claude, and GitHub Copilot — without ever reading prompt content or individual messages.
Pulls assigned seats and monthly license costs for each AI tool. Tracks which seats are active vs. inactive each month, so you can identify waste before renewal.
For consumption-based tools, ingests token-level usage data by model and user. Estimates variable costs using per-model API rates, broken down weekly.
No prompt content is ever read or stored. Data is aggregated at team level before surfacing in dashboards. Employees are never individually identified.
Tracks monthly active users (MAU), daily active users (DAU), and weekly engagement per tool — so you can see adoption trends, not just license headcount.
Correlates AI tool spend with task completion signals from your collaboration tools to estimate value generated per dollar, surfacing high-ROI and at-risk tools.
Delivers a consolidated weekly view of total AI spend, broken down by fixed and variable costs, with trend lines to spot anomalies before they hit the monthly invoice.
AI cost tracking is the process of monitoring and attributing spend across all AI tools your organization uses — including seat licenses, variable API usage, and token consumption. It helps IT, finance, and HR leaders understand the true cost of AI adoption and identify where budgets are being wasted on unused licenses or inefficient model usage.
Cloud cost management tracks infrastructure spend. Worklytics focuses on workforce-level adoption — who holds AI licenses, who actively uses them, and what value they generate. It answers the CFO question “are we getting value from our AI subscriptions?” rather than the DevOps question “what did our API calls cost?”
Worklytics currently supports Google Workspace AI, Microsoft 365 Copilot, ChatGPT Enterprise, Claude, GitHub Copilot, Cursor, and Miro AI. Coverage is expanding as enterprise AI tool adoption grows.
No. Worklytics connects to admin-level usage APIs only. We never access, store, or process prompt content, AI responses, or any individual message data. All metrics are aggregated at the team or department level before appearing in dashboards.
For tools with consumption-based pricing (ChatGPT Enterprise and Claude), Worklytics ingests token usage data from each tool’s admin API, then applies the published per-model input and output token rates. The estimated weekly variable cost is updated in real time as usage data flows in.
Seat utilization (active users ÷ enabled seats) is the fastest proxy for license waste. If you have 500 Copilot seats but only 442 monthly active users, 58 seats are generating zero value while costing ~$1,740/mo. Tracking utilization over time also shows whether adoption is growing or stalling after rollout.
Connect your AI tools and get a full picture of what your organization spends on AI, who is using it, and where licenses are going to waste — in under 24 hours.
Get a demoSee a sample AI cost report →
