American Well (AMWL) Operating Expenses (2019 - 2026)
American Well (AMWL) recorded Operating Expenses of $61.6 million in Q2 2026, down 32.5% from $91.28 million a year earlier and down 14.8% from the prior quarter.
American Well (AMWL) Operating Expenses (2019 - 2026) Analysis & Trends
On a TTM basis, American Well's Operating Expenses came in at $299.99 million as of Jun 30, 2026, down 27.0% year-over-year; for FY2025, it came in at $354.6 million, down 24.9% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of -5.6% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $471.9 million in FY2024 (-50.4%), $951.19 million in FY2023 (+72.0%), $553.04 million in FY2022 (+28.0%) and $431.94 million in FY2021 (-8.6%).
- The Q2 2026 figure is the lowest quarterly Operating Expenses since Q3 2019.
- On a year-over-year basis, Operating Expenses has declined for 11 consecutive quarters, with an average decline of 26.9% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 242.4% in Q1 2023, against a decline of 70.8% in Q1 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $72.31 million (Q1 2026), $80.46 million (Q4 2025) and $85.62 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | 178,646.00 |
| 2 | Veeva Systems | 45.35 Bn | 17.59 Bn | 695.95 Mn | 420.93 Mn |
| 3 | Samsara | 22.20 Bn | 18.97 Bn | 392.58 Mn | 387.71 Mn |
| 4 | Toast | 17.53 Bn | 10.20 Bn | 516.00 Mn | 364.00 Mn |
| 5 | Ptc | 15.47 Bn | 14.28 Bn | 490.47 Mn | 323.96 Mn |
| 6 | Trimble | 13.41 Bn | 12.48 Bn | 674.90 Mn | 542.90 Mn |
| 7 | Duolingo | 12.56 Bn | 7.73 Bn | 216.74 Mn | 182.80 Mn |
| 8 | Manhattan Associates | 11.77 Bn | 10.77 Bn | 168.33 Mn | 231.56 Mn |
| 9 | Costar | 10.95 Bn | 4.91 Bn | 728.00 Mn | 652.00 Mn |
| 10 | American Well | 228.49 Mn | -516.79 Mn | 27.56 Mn | 61.60 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 61.60 Mn |
| Mar 31, 2026 | 72.31 Mn |
| Dec 31, 2025 | 80.46 Mn |
| Sep 30, 2025 | 85.62 Mn |
| Jun 30, 2025 | 91.28 Mn |
| Mar 31, 2025 | 97.24 Mn |
| Dec 31, 2024 | 113.76 Mn |
| Sep 30, 2024 | 108.42 Mn |
| Jun 30, 2024 | 115.17 Mn |
| Mar 31, 2024 | 134.55 Mn |
| Dec 31, 2023 | 127.63 Mn |
| Sep 30, 2023 | 205.28 Mn |
| Jun 30, 2023 | 156.95 Mn |
| Mar 31, 2023 | 461.32 Mn |
| Dec 31, 2022 | 144.08 Mn |
| Sep 30, 2022 | 140.33 Mn |
| Jun 30, 2022 | 133.92 Mn |
| Mar 31, 2022 | 134.71 Mn |
| Dec 31, 2021 | 120.17 Mn |
| Sep 30, 2021 | 117.67 Mn |
American Well 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=AMWL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AMWL", "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=AMWL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();