Aecom (ACM) Operating Expenses (2009 - 2026)
Aecom (ACM) recorded Operating Expenses of $46.45 million in fiscal Q3 2026 (quarter ended Jun 30, 2026), up 21.7% from $38.16 million a year earlier but down 19.7% from the prior quarter.
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Analysis
Aecom (ACM) Operating Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Aecom's Operating Expenses came in at $271.66 million as of Jun 30, 2026, up 50.6% year-over-year; for FY2025 (ended Sep 30, 2025), it came in at $217.25 million, down 16.1% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of -10.4% (FY2020 to FY2025).
- Across earlier fiscal years, Operating Expenses came in at $259.02 million in FY2024 (-24.3%), $341.98 million in FY2023 (+34.2%), $254.81 million in FY2022 (+25.0%) and $203.91 million in FY2021 (-45.9%).
- Quarterly Operating Expenses has ranged from $38.12 million in fiscal Q2 2023 to $178.79 million in fiscal Q4 2023 over the past five years.
- On a year-over-year basis, Operating Expenses has increased for four consecutive quarters, with growth averaging 2.1% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 200.5% in fiscal Q4 2023, against a decline of 65.5% in fiscal Q4 2024 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $57.87 million (Q2 2026), $68.77 million (Q1 2026) and $98.57 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Quanta Services | 96.85 Bn | 95.03 Bn | 1.55 Bn | 698.49 Mn |
| 2 | Ferrovial | 40.19 Bn | 20.78 Bn | - | - |
| 3 | Emcor | 33.87 Bn | 30.26 Bn | 1.02 Bn | 475.04 Mn |
| 4 | Mastec | 16.39 Bn | 15.29 Bn | 556.28 Mn | 292.57 Mn |
| 5 | Jacobs Solutions | 16.20 Bn | 10.85 Bn | 810.70 Mn | 524.00 Mn |
| 6 | Sterling Infrastructure | 15.30 Bn | 13.66 Bn | 289.96 Mn | 65.66 Mn |
| 7 | IES Holdings | 12.83 Bn | 11.70 Bn | 340.66 Mn | 162.17 Mn |
| 8 | Dycom Industries | 7.99 Bn | 7.13 Bn | - | - |
| 9 | Stantec | 7.84 Bn | 7.84 Bn | - | 972.05 Mn |
| 10 | Aecom | 7.65 Bn | 2.97 Bn | -34.04 Mn | 46.45 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 46.45 Mn |
| Mar 31, 2026 | 57.87 Mn |
| Dec 31, 2025 | 68.77 Mn |
| Sep 30, 2025 | 98.57 Mn |
| Jun 30, 2025 | 38.16 Mn |
| Mar 31, 2025 | 40.05 Mn |
| Dec 31, 2024 | 40.46 Mn |
| Sep 30, 2024 | 61.70 Mn |
| Jun 30, 2024 | 65.23 Mn |
| Mar 31, 2024 | 80.15 Mn |
| Dec 31, 2023 | 51.92 Mn |
| Sep 30, 2023 | 178.79 Mn |
| Jun 30, 2023 | 52.00 Mn |
| Mar 31, 2023 | 38.12 Mn |
| Dec 31, 2022 | 73.11 Mn |
| Sep 30, 2022 | 59.50 Mn |
| Jun 30, 2022 | 45.10 Mn |
| Mar 31, 2022 | 110.39 Mn |
| Dec 31, 2021 | 39.90 Mn |
| Sep 30, 2021 | 58.30 Mn |
API Access
Aecom 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=ACM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ACM", "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=ACM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();