Smith A O (AOS) Operating Expenses (2010 - 2026)
Smith A O (AOS) reported Operating Expenses of $220.3 million for Q2 2026, up 15.2% from $191.3 million a year earlier and up 8.0% from the prior quarter.
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Analysis
Smith A O (AOS) Operating Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Smith A O's Operating Expenses came in at $799.7 million, up 7.7% year-over-year; for FY2025, it was $759.4 million, up 0.3% from FY2024.
- Operating Expenses has increased for three consecutive years, with a five-year compound annual growth rate of 2.6% (FY2020 to FY2025).
- By year, Operating Expenses came in at $756.9 million in FY2024 (+1.4%), $746.2 million in FY2023 (+11.2%), $670.9 million in FY2022 (-4.3%) and $701.4 million in FY2021 (+5.0%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses in data going back to Q1 2010.
- Year over year, Operating Expenses has now increased in each of the last six quarters, with growth averaging 3.9% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q2 2026 (growth of 15.2%); the low point was Q3 2022 (a decline of 12.4%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $203.9 million (Q1 2026), $186.6 million (Q4 2025) and $188.9 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Trane Technologies | 99.46 Bn | 94.20 Bn | 2.26 Bn | 1.04 Bn |
| 2 | Johnson Controls International | 90.06 Bn | 87.82 Bn | 2.47 Bn | 1.49 Bn |
| 3 | Comfort Systems Usa | 58.26 Bn | 53.51 Bn | 844.23 Mn | 287.05 Mn |
| 4 | Carrier Global | 45.22 Bn | 39.85 Bn | 1.94 Bn | 5.58 Bn |
| 5 | Otis Worldwide | 24.48 Bn | 21.09 Bn | 1.14 Bn | 3.28 Bn |
| 6 | James Hardie Industries | 14.69 Bn | 13.43 Bn | 548.70 Mn | 327.40 Mn |
| 7 | Masco | 13.29 Bn | 11.40 Bn | 868.00 Mn | 397.00 Mn |
| 8 | Allegion | 13.08 Bn | 11.79 Bn | 517.50 Mn | 262.80 Mn |
| 9 | Carlisle Companies | 12.82 Bn | 9.17 Bn | 568.40 Mn | 210.70 Mn |
| 10 | Smith A O | 7.66 Bn | 6.91 Bn | 387.80 Mn | 220.30 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 220.30 Mn |
| Mar 31, 2026 | 203.90 Mn |
| Dec 31, 2025 | 186.60 Mn |
| Sep 30, 2025 | 188.90 Mn |
| Jun 30, 2025 | 191.30 Mn |
| Mar 31, 2025 | 192.60 Mn |
| Dec 31, 2024 | 182.00 Mn |
| Sep 30, 2024 | 176.60 Mn |
| Jun 30, 2024 | 188.50 Mn |
| Mar 31, 2024 | 192.20 Mn |
| Dec 31, 2023 | 185.00 Mn |
| Sep 30, 2023 | 174.90 Mn |
| Jun 30, 2023 | 180.30 Mn |
| Mar 31, 2023 | 187.20 Mn |
| Dec 31, 2022 | 168.90 Mn |
| Sep 30, 2022 | 155.50 Mn |
| Jun 30, 2022 | 166.70 Mn |
| Mar 31, 2022 | 179.80 Mn |
| Dec 31, 2021 | 184.20 Mn |
| Sep 30, 2021 | 177.60 Mn |
API Access
Smith A O 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=AOS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AOS", "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=AOS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();