Spectral AI (MDAI) Operating Expenses (2021 - 2026)
Spectral AI (MDAI) posted Operating Expenses of $5.44 million for Q2 2026, up 23.2% from $4.41 million a year earlier and up 36.0% from the prior quarter.
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Analysis
Spectral AI (MDAI) Operating Expenses (2021 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Spectral AI was $18.49 million, up 5.7% year-over-year; for FY2025, it came in at $17.53 million, down 11.7% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 663.6% (FY2020 to FY2025).
- In prior years, Spectral AI's Operating Expenses was $19.86 million in FY2024 (-4.8%), $20.86 million in FY2023 (+54.7%), $13.48 million in FY2022 (+294.2%) and $3.42 million in FY2021.
- The Q2 2026 figure stands as the highest quarterly Operating Expenses since Q2 2024.
- On a year-over-year basis, Operating Expenses increased in two of the last eight quarters, with an average decline of 7.2%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q1 2023, with growth of 992.0%; the weakest was Q2 2025, with a decline of 23.3%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $4 million (Q1 2026), $4.09 million (Q4 2025) and $4.96 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 257.79 Bn | 234.30 Bn | 5.13 Bn | 9.87 Bn |
| 2 | Abbott Laboratories | 190.83 Bn | 164.70 Bn | 7.39 Bn | 11.66 Bn |
| 3 | Danaher | 162.10 Bn | 141.75 Bn | 3.84 Bn | 2.59 Bn |
| 4 | Intuitive Surgical | 158.05 Bn | 138.34 Bn | 2.08 Bn | 1.49 Bn |
| 5 | Medtronic | 130.31 Bn | 95.56 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 124.76 Bn | 110.95 Bn | 4.25 Bn | 3.21 Bn |
| 7 | Boston Scientific | 62.03 Bn | 57.46 Bn | 3.43 Bn | 2.60 Bn |
| 8 | Edwards Lifesciences | 58.73 Bn | 41.94 Bn | 1.35 Bn | 844.30 Mn |
| 9 | Becton Dickinson | 58.33 Bn | 55.48 Bn | 2.32 Bn | 4.32 Bn |
| 10 | Spectral AI | 48.76 Mn | -2.84 Mn | 1.11 Mn | 5.44 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 5.44 Mn |
| Mar 31, 2026 | 4.00 Mn |
| Dec 31, 2025 | 4.09 Mn |
| Sep 30, 2025 | 4.96 Mn |
| Jun 30, 2025 | 4.41 Mn |
| Mar 31, 2025 | 4.06 Mn |
| Dec 31, 2024 | 4.46 Mn |
| Sep 30, 2024 | 4.55 Mn |
| Jun 30, 2024 | 5.76 Mn |
| Mar 31, 2024 | 5.09 Mn |
| Dec 31, 2023 | 5.37 Mn |
| Sep 30, 2023 | 5.64 Mn |
| Jun 30, 2023 | 4.78 Mn |
| Mar 31, 2023 | 5.08 Mn |
| Dec 31, 2022 | 4.28 Mn |
| Sep 30, 2022 | 3.48 Mn |
| Jun 30, 2022 | 248,722.00 |
| Mar 31, 2022 | 465,124.00 |
| Dec 31, 2021 | 1.78 Mn |
| Sep 30, 2021 | 1.19 Mn |
API Access
Spectral AI 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=MDAI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MDAI", "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=MDAI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();