American Airlines (AAL) Operating Expenses (2009 - 2026)
American Airlines' Operating Expenses was $16.29 billion in Q2 2026, up 22.9% from $13.26 billion a year earlier and up 16.7% from the prior quarter.
American Airlines (AAL) Operating Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, American Airlines' Operating Expenses was $57.33 billion through Jun 30, 2026, up 9.9% year-over-year; for FY2025, it came in at $53.17 billion, up 3.0% from FY2024.
- Operating Expenses has now increased for five consecutive years, with a five-year compound annual growth rate of 13.9% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $51.6 billion in FY2024 (+3.7%), $49.75 billion in FY2023 (+5.0%), $47.36 billion in FY2022 (+53.1%) and $30.94 billion in FY2021 (+11.5%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q2 2009.
- Compared with a year earlier, Operating Expenses has increased for three straight quarters, with growth averaging 5.5% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q1 2022 (growth of 99.5%); the worst was Q2 2023 (a decline of 4.1%).
- Per Business Quant data, AAL's Operating Expenses in the three quarters before Q2 2026 was $13.95 billion (Q1 2026), $13.55 billion (Q4 2025) and $13.54 billion (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Union Pacific | 178.29 Bn | 170.53 Bn | - | 4.25 Bn |
| 2 | Csx | 96.66 Bn | 91.88 Bn | - | 2.45 Bn |
| 3 | United Parcel Service | 90.64 Bn | 67.53 Bn | - | 21.90 Bn |
| 4 | Canadian Pacific Kansas City | 80.76 Bn | 79.78 Bn | - | 1.95 Bn |
| 5 | Norfolk Southern | 76.34 Bn | 70.80 Bn | - | 2.38 Bn |
| 6 | Fedex | 72.87 Bn | 38.82 Bn | - | 23.46 Bn |
| 7 | Delta Air Lines | 53.46 Bn | 35.65 Bn | - | 18.73 Bn |
| 8 | Old Dominion Freight Line | 38.90 Bn | 38.16 Bn | - | 1.09 Bn |
| 9 | United Airlines Holdings | 34.06 Bn | -23.63 Bn | - | 16.43 Bn |
| 10 | American Airlines | 8.36 Bn | -15.68 Bn | - | 16.29 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 16.29 Bn |
| Mar 31, 2026 | 13.95 Bn |
| Dec 31, 2025 | 13.55 Bn |
| Sep 30, 2025 | 13.54 Bn |
| Jun 30, 2025 | 13.26 Bn |
| Mar 31, 2025 | 12.82 Bn |
| Dec 31, 2024 | 12.53 Bn |
| Sep 30, 2024 | 13.56 Bn |
| Jun 30, 2024 | 12.95 Bn |
| Mar 31, 2024 | 12.56 Bn |
| Dec 31, 2023 | 12.41 Bn |
| Sep 30, 2023 | 13.71 Bn |
| Jun 30, 2023 | 11.89 Bn |
| Mar 31, 2023 | 11.75 Bn |
| Dec 31, 2022 | 11.81 Bn |
| Sep 30, 2022 | 12.53 Bn |
| Jun 30, 2022 | 12.41 Bn |
| Mar 31, 2022 | 10.62 Bn |
| Dec 31, 2021 | 10.21 Bn |
| Sep 30, 2021 | 8.37 Bn |
American Airlines 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=AAL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AAL", "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=AAL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();