AgEagle Aerial Systems (UAVS) Operating Expenses (2011 - 2026)
AgEagle Aerial Systems (UAVS) recorded Operating Expenses of $6.97 million in Q2 2026, up 58.0% from $4.41 million a year earlier and up 22.6% from the prior quarter.
AgEagle Aerial Systems (UAVS) Operating Expenses (2011 - 2026) Analysis & Trends
On a TTM basis, AgEagle Aerial Systems' Operating Expenses came in at $26.48 million as of Jun 30, 2026, up 46.9% year-over-year; for FY2025, it came in at $21.37 million, up 12.9% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 31.2% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $18.92 million in FY2024 (-57.6%), $44.61 million in FY2023 (-38.5%), $72.49 million in FY2022 (+109.8%) and $34.55 million in FY2021 (+527.6%).
- Quarterly Operating Expenses has ranged from $3.14 million in Q1 2025 to $48.48 million in Q4 2022 over the past five years.
- On a year-over-year basis, Operating Expenses has increased for five consecutive quarters, with growth averaging 6.1% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 639.4% in Q4 2021, against a decline of 72.5% in Q4 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $5.68 million (Q1 2026), $9.91 million (Q4 2025) and $3.91 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 330.06 Bn | 284.06 Bn | 4.68 Bn | 10.86 Bn |
| 2 | Rtx | 252.10 Bn | 225.31 Bn | 5.13 Bn | 21.96 Bn |
| 3 | Boeing | 148.40 Bn | 55.10 Bn | 2.41 Bn | 2.35 Bn |
| 4 | Lockheed Martin | 118.20 Bn | 104.92 Bn | 2.45 Bn | - |
| 5 | Howmet Aerospace | 92.39 Bn | 87.99 Bn | 951.00 Mn | 156.00 Mn |
| 6 | General Dynamics | 89.92 Bn | 77.03 Bn | 2.18 Bn | 12.63 Bn |
| 7 | Motorola Solutions | 73.84 Bn | 70.20 Bn | 1.68 Bn | 756.00 Mn |
| 8 | Northrop Grumman | 71.73 Bn | 60.97 Bn | 2.12 Bn | 9.78 Bn |
| 9 | Honeywell International | 66.60 Bn | 19.04 Bn | 3.65 Bn | 1.87 Bn |
| 10 | AgEagle Aerial Systems | 59.62 Mn | -43.53 Mn | 1.36 Mn | 6.97 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 6.97 Mn |
| Mar 31, 2026 | 5.68 Mn |
| Dec 31, 2025 | 9.91 Mn |
| Sep 30, 2025 | 3.91 Mn |
| Jun 30, 2025 | 4.41 Mn |
| Mar 31, 2025 | 3.14 Mn |
| Dec 31, 2024 | 6.99 Mn |
| Sep 30, 2024 | 3.50 Mn |
| Jun 30, 2024 | 4.10 Mn |
| Mar 31, 2024 | 4.35 Mn |
| Dec 31, 2023 | 25.37 Mn |
| Sep 30, 2023 | 7.20 Mn |
| Jun 30, 2023 | 5.90 Mn |
| Mar 31, 2023 | 6.14 Mn |
| Dec 31, 2022 | 48.48 Mn |
| Sep 30, 2022 | 7.23 Mn |
| Jun 30, 2022 | 7.94 Mn |
| Mar 31, 2022 | 8.85 Mn |
| Dec 31, 2021 | 20.19 Mn |
| Sep 30, 2021 | 4.59 Mn |
AgEagle Aerial Systems 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=UAVS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "UAVS", "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=UAVS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();