TaskUs (TASK) Operating Expenses (2020 - 2026)
TaskUs' Operating Expenses was $275.54 million in Q2 2026, up 4.5% from $263.72 million a year earlier and up 1.3% from the prior quarter.
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Analysis
TaskUs (TASK) Operating Expenses (2020 - 2026) Analysis & Trends
On a trailing twelve-month basis, TaskUs' Operating Expenses was $1.08 billion through Jun 30, 2026, up 9.3% year-over-year; for FY2025, it came in at $1.04 billion, up 15.6% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 19.5% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $902.56 million in FY2024 (+8.8%), $829.33 million in FY2023 (-5.4%), $876.59 million in FY2022 (+7.6%) and $814.99 million in FY2021 (+90.5%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses since Q2 2021.
- Compared with a year earlier, Operating Expenses has increased for nine straight quarters, with growth averaging 14.8% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2021 (growth of 74.2%); the worst was Q2 2022 (a decline of 22.5%).
- Per Business Quant data, TASK's Operating Expenses in the three quarters before Q2 2026 was $272.06 million (Q1 2026), $274.87 million (Q4 2025) and $260.77 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 116.45 Bn | 76.86 Bn | 6.13 Bn | 15.54 Bn |
| 2 | Cintas | 80.26 Bn | 79.45 Bn | 1.48 Bn | 792.12 Mn |
| 3 | Iron Mountain | 33.05 Bn | 32.57 Bn | 1.07 Bn | 1.66 Bn |
| 4 | APi | 16.57 Bn | 13.61 Bn | 703.00 Mn | 528.00 Mn |
| 5 | Rollins | 14.72 Bn | 14.26 Bn | 569.95 Mn | 877.22 Mn |
| 6 | Aramark | 14.30 Bn | 12.32 Bn | 430.34 Mn | 4.84 Bn |
| 7 | UL Solutions | 13.09 Bn | 11.87 Bn | 417.00 Mn | 267.00 Mn |
| 8 | Gartner | 11.73 Bn | 5.42 Bn | 1.19 Bn | 1.30 Bn |
| 9 | Rentokil Initial | 10.36 Bn | 3.71 Bn | - | - |
| 10 | TaskUs | 742.12 Mn | -12.10 Mn | 107.15 Mn | 275.54 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 275.54 Mn |
| Mar 31, 2026 | 272.06 Mn |
| Dec 31, 2025 | 274.87 Mn |
| Sep 30, 2025 | 260.77 Mn |
| Jun 30, 2025 | 263.72 Mn |
| Mar 31, 2025 | 243.55 Mn |
| Dec 31, 2024 | 252.29 Mn |
| Sep 30, 2024 | 231.15 Mn |
| Jun 30, 2024 | 215.21 Mn |
| Mar 31, 2024 | 203.91 Mn |
| Dec 31, 2023 | 202.74 Mn |
| Sep 30, 2023 | 202.68 Mn |
| Jun 30, 2023 | 207.00 Mn |
| Mar 31, 2023 | 216.91 Mn |
| Dec 31, 2022 | 218.98 Mn |
| Sep 30, 2022 | 211.40 Mn |
| Jun 30, 2022 | 227.09 Mn |
| Mar 31, 2022 | 219.13 Mn |
| Dec 31, 2021 | 206.54 Mn |
| Sep 30, 2021 | 184.92 Mn |
API Access
TaskUs Operating Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=operating-expenses&ticker=TASK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "TASK", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=TASK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();