Global AI (GLAI) Operating Expenses (2010 - 2026)
Global AI (GLAI) posted Operating Expenses of $891,409 for Q2 2026, up 71.1% from $520,864 a year earlier and up 6.2% from the prior quarter.
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Analysis
Global AI (GLAI) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Global AI was $1.7 million, up 2.9% year-over-year; for FY2025, it was $2.35 million, up 132.6% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 106.2% (FY2020 to FY2025).
- In prior years, Global AI's Operating Expenses was $1.01 million in FY2024 (+50.9%), $669,554 in FY2023, $55,504 in FY2022 (-24.7%) and $73,728 in FY2021 (+17.0%).
- Quarterly Operating Expenses has run from a low of -$1.67 million in Q4 2025 to a high of $1.65 million in Q3 2025 over five years.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2023, with growth of 611.7%; the weakest was Q1 2022, with a decline of 54.4%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $839,733 (Q1 2026), -$1.67 million (Q4 2025) and $1.65 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 255.42 Bn | 240.49 Bn | 2.30 Bn | 2.13 Bn |
| 2 | CrowdStrike Holdings | 232.07 Bn | 212.47 Bn | 1.10 Bn | 1.13 Bn |
| 3 | Fortinet | 125.35 Bn | 111.28 Bn | 1.64 Bn | 953.90 Mn |
| 4 | Snowflake | 111.63 Bn | 98.94 Bn | 1.04 Bn | 1.30 Bn |
| 5 | Datadog | 91.35 Bn | 72.99 Bn | 881.34 Mn | 875.89 Mn |
| 6 | Zscaler | 34.43 Bn | 20.55 Bn | - | - |
| 7 | Okta | 33.87 Bn | 23.97 Bn | 641.00 Mn | 534.00 Mn |
| 8 | Axon Enterprise | 31.65 Bn | 26.18 Bn | 546.45 Mn | 499.67 Mn |
| 9 | MongoDB | 29.46 Bn | 19.93 Bn | 569.77 Mn | 541.37 Mn |
| 10 | Global AI | 139.41 Mn | 139.15 Mn | 82,446.00 | 891,409.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 891,409.00 |
| Mar 31, 2026 | 839,733.00 |
| Dec 31, 2025 | -1.67 Mn |
| Sep 30, 2025 | 1.65 Mn |
| Jun 30, 2025 | 520,864.00 |
| Mar 31, 2025 | 744,855.00 |
| Dec 31, 2024 | 272,656.00 |
| Sep 30, 2024 | 117,932.00 |
| Jun 30, 2024 | 263,849.00 |
| Mar 31, 2024 | 346,210.00 |
| Sep 30, 2023 | 110,660.00 |
| Jun 30, 2023 | 16,674.00 |
| Mar 31, 2023 | 18,071.00 |
| Dec 31, 2022 | 16,848.00 |
| Sep 30, 2022 | 15,548.00 |
| Jun 30, 2022 | 15,273.00 |
| Mar 31, 2022 | 17,088.00 |
| Dec 31, 2021 | 7,596.00 |
| Sep 30, 2021 | 25,102.00 |
| Jun 30, 2021 | 16,263.00 |
API Access
Global 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=GLAI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GLAI", "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=GLAI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();