C3.ai (AI) Accumulated Expenses (2020 - 2026)
C3.ai's Accumulated Expenses was $19.78 million in fiscal Q1 2027 (quarter ended Jul 31, 2026), down 20.5% from $24.86 million a year earlier but up 12.1% from the prior quarter.
Powered by 
Analysis
C3.ai (AI) Accumulated Expenses (2020 - 2026) Analysis & Trends
At the end of FY2026 (ended Apr 30, 2026), Accumulated Expenses at C3.ai came in at $17.64 million, down 32.9% from FY2025.
- Accumulated Expenses shows a five-year compound annual growth rate of -0.8% (FY2021 to FY2026).
- In earlier fiscal years, Accumulated Expenses was $26.3 million in FY2025 (+176.0%), $9.53 million in FY2024 (-44.2%), $17.07 million in FY2023 (+14.8%) and $14.87 million in FY2022 (-18.8%).
- Quarterly Accumulated Expenses has moved between $9.53 million (fiscal Q4 2024) and $33.68 million (fiscal Q2 2022) over five years.
- Compared with a year earlier, Accumulated Expenses has declined for four straight quarters, with growth averaging 49.0% over the last eight quarters.
- The best year-over-year quarter for Accumulated Expenses over five years was fiscal Q4 2025 (growth of 176.0%); the worst was fiscal Q3 2024 (a decline of 50.8%).
- Per Business Quant data, AI's Accumulated Expenses in the three fiscal quarters before Q1 2027 was $17.64 million (Q4 2026), $17.16 million (Q3 2026) and $13.56 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palo Alto Networks | 323.81 Bn | 308.88 Bn | 2.30 Bn |
| 2 | CrowdStrike Holdings | 271.09 Bn | 251.53 Bn | 1.10 Bn |
| 3 | Fortinet | 131.14 Bn | 117.07 Bn | 1.64 Bn |
| 4 | Snowflake | 119.71 Bn | 107.03 Bn | 1.04 Bn |
| 5 | Datadog | 98.30 Bn | 79.94 Bn | 881.34 Mn |
| 6 | Okta | 34.95 Bn | 25.05 Bn | 641.00 Mn |
| 7 | Axon Enterprise | 34.32 Bn | 28.85 Bn | 546.45 Mn |
| 8 | Zscaler | 32.52 Bn | 18.64 Bn | - |
| 9 | Baidu | 29.56 Bn | -44.07 Bn | 1.47 Mn |
| 10 | C3.ai | 1.70 Bn | -818.49 Mn | 16.67 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 19.78 Mn |
| Apr 30, 2026 | 17.64 Mn |
| Jan 31, 2026 | 17.16 Mn |
| Oct 31, 2025 | 13.56 Mn |
| Jul 31, 2025 | 24.86 Mn |
| Apr 30, 2025 | 26.30 Mn |
| Jan 31, 2025 | 27.63 Mn |
| Oct 31, 2024 | 23.98 Mn |
| Jul 31, 2024 | 12.81 Mn |
| Apr 30, 2024 | 9.53 Mn |
| Jan 31, 2024 | 12.39 Mn |
| Oct 31, 2023 | 10.28 Mn |
| Jul 31, 2023 | 10.43 Mn |
| Apr 30, 2023 | 17.07 Mn |
| Jan 31, 2023 | 25.20 Mn |
| Oct 31, 2022 | 19.89 Mn |
| Jul 31, 2022 | 17.65 Mn |
| Apr 30, 2022 | 14.87 Mn |
| Jan 31, 2022 | 33.60 Mn |
| Oct 31, 2021 | 33.68 Mn |
API Access
C3.ai Accumulated 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=accumulated-expenses&ticker=AI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-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=accumulated-expenses&ticker=AI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();