Cognizant Technology Solutions (CTSH) Operating Expenses (2009 - 2026)
Cognizant Technology Solutions (CTSH) reported Operating Expenses of $812 million for Q2 2026, up 0.2% from $810 million a year earlier and up 2.7% from the prior quarter.
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Analysis
Cognizant Technology Solutions (CTSH) Operating Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Cognizant Technology Solutions' Operating Expenses came in at $3.24 billion, down 3.5% year-over-year; for FY2025, it was $3.57 billion, down 3.7% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of -0.8% (FY2020 to FY2025).
- By year, Operating Expenses came in at $3.71 billion in FY2024 (-4.1%), $3.87 billion in FY2023 (+1.1%), $3.83 billion in FY2022 (-1.7%) and $3.9 billion in FY2021 (+4.6%).
- Five-year quarterly Operating Expenses spans a low of $788 million in Q1 2024 and a high of $947 million in Q2 2023.
- Year over year, Operating Expenses gained in three of the last eight quarters, with an average decline of 0.7%.
- The high point for year-over-year Operating Expenses in five years was Q4 2024 (growth of 8.1%); the low point was Q2 2024 (a decline of 14.5%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $791 million (Q1 2026), $806 million (Q4 2025) and $833 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 51.92 Bn | 38.42 Bn | 1.60 Bn | 528.00 Mn |
| 2 | Cognizant Technology Solutions | 31.76 Bn | 24.92 Bn | 1.83 Bn | 812.00 Mn |
| 3 | Wipro | 21.48 Bn | 16.18 Bn | 738.00 Mn | 2.23 Bn |
| 4 | Cdw | 19.77 Bn | 17.76 Bn | 1.32 Bn | 891.20 Mn |
| 5 | Td Synnex | 19.64 Bn | 13.80 Bn | 1.43 Bn | 784.64 Mn |
| 6 | Cgi | 17.53 Bn | 15.32 Bn | - | - |
| 7 | Arrow Electronics | 11.08 Bn | 10.02 Bn | 1.13 Bn | 747.88 Mn |
| 8 | Avnet | 7.46 Bn | 6.64 Bn | 865.03 Mn | 634.01 Mn |
| 9 | EPAM Systems | 6.79 Bn | 2.43 Bn | 429.57 Mn | 245.25 Mn |
| 10 | Ingram Micro Holding | 6.28 Bn | 1.89 Bn | 958.68 Mn | 722.71 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 812.00 Mn |
| Mar 31, 2026 | 791.00 Mn |
| Dec 31, 2025 | 806.00 Mn |
| Sep 30, 2025 | 833.00 Mn |
| Jun 30, 2025 | 810.00 Mn |
| Mar 31, 2025 | 791.00 Mn |
| Dec 31, 2024 | 893.00 Mn |
| Sep 30, 2024 | 866.00 Mn |
| Jun 30, 2024 | 810.00 Mn |
| Mar 31, 2024 | 788.00 Mn |
| Dec 31, 2023 | 826.00 Mn |
| Sep 30, 2023 | 873.00 Mn |
| Jun 30, 2023 | 947.00 Mn |
| Mar 31, 2023 | 835.00 Mn |
| Dec 31, 2022 | 860.00 Mn |
| Sep 30, 2022 | 838.00 Mn |
| Jun 30, 2022 | 883.00 Mn |
| Mar 31, 2022 | 862.00 Mn |
| Dec 31, 2021 | 871.00 Mn |
| Sep 30, 2021 | 924.00 Mn |
API Access
Cognizant Technology Solutions 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=CTSH&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CTSH", "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=CTSH&period=max&api_key=YOUR_API_KEY");
const data = await res.json();