Air T (AIRT) Operating Expenses (2010 - 2026)
Air T (AIRT) reported Operating Expenses of $128.29 million for fiscal Q1 2027 (quarter ended Jun 30, 2026), up 83.2% from $70.02 million a year earlier but down 4.8% from the prior quarter.
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Analysis
Air T (AIRT) Operating Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Air T's Operating Expenses came in at $403.58 million, up 37.7% year-over-year; for FY2026 (ended Mar 31, 2026), it was $345.32 million, up 19.1% from FY2025.
- Operating Expenses has increased for four consecutive fiscal years, with a five-year compound annual growth rate of 13.4% (FY2021 to FY2026).
- By fiscal year, Operating Expenses came in at $289.94 million in FY2025 (+1.5%), $285.57 million in FY2024 (+13.4%), $251.73 million in FY2023 (+49.6%) and $168.32 million in FY2022 (-8.7%).
- Five-year quarterly Operating Expenses spans a low of $42.53 million in fiscal Q2 2022 and a high of $134.71 million in fiscal Q4 2026.
- Year over year, Operating Expenses gained in four of the last eight quarters, with growth averaging 22.4%.
- The high point for year-over-year Operating Expenses in five years was fiscal Q4 2026 (growth of 95.5%); the low point was fiscal Q4 2022 (a decline of 18.1%).
- Per Business Quant data, the three fiscal quarters before Q1 2027 came in at $134.71 million (Q4 2026), $74.91 million (Q3 2026) and $65.68 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 348.08 Bn | 306.60 Bn | 5.02 Bn | 11.75 Bn |
| 2 | Rtx | 265.63 Bn | 233.90 Bn | 5.81 Bn | 21.79 Bn |
| 3 | Boeing | 136.74 Bn | 45.69 Bn | 2.17 Bn | 2.03 Bn |
| 4 | Lockheed Martin | 135.57 Bn | 119.80 Bn | 2.44 Bn | - |
| 5 | General Dynamics | 97.85 Bn | 83.08 Bn | 2.25 Bn | 13.04 Bn |
| 6 | Motorola Solutions | 87.60 Bn | 84.06 Bn | 1.77 Bn | 780.00 Mn |
| 7 | Howmet Aerospace | 85.98 Bn | 81.73 Bn | 1.00 Bn | 133.00 Mn |
| 8 | Northrop Grumman | 76.55 Bn | 64.01 Bn | 2.35 Bn | 9.85 Bn |
| 9 | Honeywell International | 72.76 Bn | 32.28 Bn | 2.02 Bn | 1.28 Bn |
| 10 | Air T | 76.70 Mn | -19.22 Mn | 70.16 Mn | 128.29 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 128.29 Mn |
| Mar 31, 2026 | 134.71 Mn |
| Dec 31, 2025 | 74.91 Mn |
| Sep 30, 2025 | 65.68 Mn |
| Jun 30, 2025 | 70.02 Mn |
| Mar 31, 2025 | 68.89 Mn |
| Dec 31, 2024 | 76.46 Mn |
| Sep 30, 2024 | 77.62 Mn |
| Jun 30, 2024 | 66.99 Mn |
| Mar 31, 2024 | 71.23 Mn |
| Dec 31, 2023 | 65.36 Mn |
| Sep 30, 2023 | 78.21 Mn |
| Jun 30, 2023 | 70.77 Mn |
| Mar 31, 2023 | 79.93 Mn |
| Dec 31, 2022 | 61.26 Mn |
| Sep 30, 2022 | 60.51 Mn |
| Jun 30, 2022 | 50.03 Mn |
| Mar 31, 2022 | 43.41 Mn |
| Dec 31, 2021 | 45.41 Mn |
| Sep 30, 2021 | 42.53 Mn |
API Access
Air T 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=AIRT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AIRT", "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=AIRT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();