C3.ai (AI) Operating Expenses (2020 - 2026)
C3.ai's Operating Expenses came in at $114.94 million for fiscal Q1 2027 (quarter ended Jul 31, 2026), down 24.0% from $151.26 million a year earlier and down 13.2% from the prior quarter.
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Analysis
C3.ai (AI) Operating Expenses (2020 - 2026) Analysis & Trends
Over the trailing twelve months to Jul 31, 2026, C3.ai reported Operating Expenses of $539.55 million, down 8.1% year-over-year; for FY2026 (ended Apr 30, 2026), it was $575.88 million, up 2.8% from FY2025.
- Operating Expenses has increased in each of the last seven fiscal years, with a five-year compound annual growth rate of 23.7% (FY2021 to FY2026).
- Going back by fiscal year, Operating Expenses was $560.29 million in FY2025 (+12.8%), $496.9 million in FY2024 (+5.5%), $470.95 million in FY2023 (+22.3%) and $385.17 million in FY2022 (+93.6%).
- The fiscal Q1 2027 figure represents the lowest quarterly Operating Expenses since fiscal Q1 2024.
- Year-over-year, Operating Expenses increased in six of the last eight quarters, with growth averaging 4.1%.
- The fastest year-over-year change in Operating Expenses over five years came in fiscal Q2 2022 (growth of 114.0%), and the weakest in fiscal Q1 2027 (a decline of 24.0%).
- Business Quant data shows AI's Operating Expenses at $132.48 million (Q4 2026), $149.64 million (Q3 2026) and $142.49 million (Q2 2026) in the three fiscal quarters before Q1 2027.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 256.08 Bn | 241.15 Bn | 2.30 Bn | 2.13 Bn |
| 2 | CrowdStrike Holdings | 232.87 Bn | 213.27 Bn | 1.10 Bn | 1.13 Bn |
| 3 | Fortinet | 125.37 Bn | 111.30 Bn | 1.64 Bn | 953.90 Mn |
| 4 | Snowflake | 112.29 Bn | 99.61 Bn | 1.04 Bn | 1.30 Bn |
| 5 | Datadog | 91.82 Bn | 73.46 Bn | 881.34 Mn | 875.89 Mn |
| 6 | Zscaler | 34.54 Bn | 20.66 Bn | - | - |
| 7 | Okta | 33.92 Bn | 24.01 Bn | 641.00 Mn | 534.00 Mn |
| 8 | Axon Enterprise | 31.94 Bn | 26.47 Bn | 546.45 Mn | 499.67 Mn |
| 9 | MongoDB | 29.38 Bn | 19.84 Bn | 569.77 Mn | 541.37 Mn |
| 10 | C3.ai | 1.82 Bn | -703.79 Mn | 16.67 Mn | 114.94 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 114.94 Mn |
| Apr 30, 2026 | 132.48 Mn |
| Jan 31, 2026 | 149.64 Mn |
| Oct 31, 2025 | 142.49 Mn |
| Jul 31, 2025 | 151.26 Mn |
| Apr 30, 2025 | 156.48 Mn |
| Jan 31, 2025 | 145.93 Mn |
| Oct 31, 2024 | 133.13 Mn |
| Jul 31, 2024 | 124.75 Mn |
| Apr 30, 2024 | 133.92 Mn |
| Jan 31, 2024 | 127.83 Mn |
| Oct 31, 2023 | 120.51 Mn |
| Jul 31, 2023 | 114.64 Mn |
| Apr 30, 2023 | 120.78 Mn |
| Jan 31, 2023 | 116.44 Mn |
| Oct 31, 2022 | 113.62 Mn |
| Jul 31, 2022 | 120.11 Mn |
| Apr 30, 2022 | 111.48 Mn |
| Jan 31, 2022 | 99.83 Mn |
| Oct 31, 2021 | 97.97 Mn |
API Access
C3.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=AI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AI", "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=AI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();