APi (APG) Operating Expenses (2019 - 2026)
APi (APG) recorded Operating Expenses of $528 million in Q2 2026, up 11.9% from $472 million a year earlier and up 2.1% from the prior quarter.
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Analysis
APi (APG) Operating Expenses (2019 - 2026) Analysis & Trends
On a TTM basis, APi's Operating Expenses came in at $2.05 billion as of Jun 30, 2026, up 12.9% year-over-year; for FY2025, it was $1.93 billion, up 14.1% from FY2024.
- Annual Operating Expenses has increased for six straight years, with a five-year compound annual growth rate of 21.7% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $1.69 billion in FY2024 (+7.1%), $1.58 billion in FY2023 (+1.9%), $1.55 billion in FY2022 (+93.3%) and $803 million in FY2021 (+10.8%).
- The Q2 2026 figure is the highest quarterly Operating Expenses in data going back to Q1 2019.
- On a year-over-year basis, Operating Expenses has increased for 13 consecutive quarters, with growth averaging 11.5% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 109.3% in Q1 2022, against a decline of 8.1% in Q1 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $517 million (Q1 2026), $514 million (Q4 2025) and $489 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 132.79 Bn | 93.20 Bn | 6.13 Bn | 15.54 Bn |
| 2 | Cintas | 77.24 Bn | 76.43 Bn | 1.48 Bn | 792.12 Mn |
| 3 | Iron Mountain | 33.76 Bn | 33.28 Bn | 1.07 Bn | 1.66 Bn |
| 4 | APi | 17.50 Bn | 14.54 Bn | 703.00 Mn | 528.00 Mn |
| 5 | Aramark | 14.64 Bn | 12.66 Bn | 430.34 Mn | 4.84 Bn |
| 6 | Rollins | 14.51 Bn | 14.06 Bn | 569.95 Mn | 877.22 Mn |
| 7 | UL Solutions | 13.33 Bn | 12.11 Bn | 417.00 Mn | 267.00 Mn |
| 8 | Gartner | 11.67 Bn | 5.36 Bn | 1.19 Bn | 1.30 Bn |
| 9 | Rentokil Initial | 10.08 Bn | 3.42 Bn | - | - |
| 10 | Tetra Tech | 8.48 Bn | 7.59 Bn | 243.21 Mn | 5.70 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 528.00 Mn |
| Mar 31, 2026 | 517.00 Mn |
| Dec 31, 2025 | 514.00 Mn |
| Sep 30, 2025 | 489.00 Mn |
| Jun 30, 2025 | 472.00 Mn |
| Mar 31, 2025 | 458.00 Mn |
| Dec 31, 2024 | 459.00 Mn |
| Sep 30, 2024 | 425.00 Mn |
| Jun 30, 2024 | 418.00 Mn |
| Mar 31, 2024 | 392.00 Mn |
| Dec 31, 2023 | 433.00 Mn |
| Sep 30, 2023 | 407.00 Mn |
| Jun 30, 2023 | 389.00 Mn |
| Mar 31, 2023 | 352.00 Mn |
| Dec 31, 2022 | 414.00 Mn |
| Sep 30, 2022 | 379.00 Mn |
| Jun 30, 2022 | 376.00 Mn |
| Mar 31, 2022 | 383.00 Mn |
| Dec 31, 2021 | 224.00 Mn |
| Sep 30, 2021 | 211.00 Mn |
API Access
APi 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=APG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "APG", "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=APG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();