Automatic Data Processing (ADP) Capital Expenditures (2009 - 2026)
Automatic Data Processing's Capital Expenditures was $72.8 million in fiscal Q4 2026 (quarter ended Jun 30, 2026), up 113.5% from $34.1 million a year earlier and up 43.9% from the prior quarter.
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Analysis
Automatic Data Processing (ADP) Capital Expenditures (2009 - 2026) Analysis & Trends
For FY2026 (ended Jun 30, 2026), Capital Expenditures at Automatic Data Processing came in at $196.6 million, up 16.5% from FY2025.
- Capital Expenditures shows a five-year compound annual growth rate of 1.9% (FY2021 to FY2026).
- In earlier fiscal years, Capital Expenditures was $168.7 million in FY2025 (-19.0%), $208.4 million in FY2024 (+1.0%), $206.3 million in FY2023 (+18.3%) and $174.4 million in FY2022 (-2.4%).
- The fiscal Q4 2026 figure marks the highest quarterly Capital Expenditures since fiscal Q1 2018.
- Compared with a year earlier, Capital Expenditures was higher in three of the last eight quarters, with growth averaging 5.5%.
- The best year-over-year quarter for Capital Expenditures over five years was fiscal Q4 2026 (growth of 113.5%); the worst was fiscal Q3 2025 (a decline of 38.9%).
- Per Business Quant data, ADP's Capital Expenditures in the three fiscal quarters before Q4 2026 was $50.6 million (Q3 2026), $26.5 million (Q2 2026) and $46.7 million (Q1 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Capex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 480.73 Bn | 449.68 Bn | 1.64 Bn | 14.55 Mn |
| 2 | Oracle | 399.91 Bn | 272.04 Bn | - | 28.50 Bn |
| 3 | Sap Se | 262.30 Bn | 190.08 Bn | 8.40 Bn | -134.83 Mn |
| 4 | Salesforce | 202.26 Bn | 158.13 Bn | 8.70 Bn | 171.00 Mn |
| 5 | ServiceNow | 153.84 Bn | 132.30 Bn | 2.82 Bn | 114.00 Mn |
| 6 | Automatic Data Processing | 114.84 Bn | 96.97 Bn | 2.51 Bn | 72.80 Mn |
| 7 | Intuit | 91.04 Bn | 70.38 Bn | 3.44 Bn | 27.00 Mn |
| 8 | Relx | 70.51 Bn | 69.60 Bn | - | - |
| 9 | Strategy | 53.24 Bn | 46.23 Bn | 81.55 Mn | 1.77 Mn |
| 10 | Thomson Reuters | 48.40 Bn | 45.18 Bn | - | 177.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 72.80 Mn |
| Mar 31, 2026 | 50.60 Mn |
| Dec 31, 2025 | 26.50 Mn |
| Sep 30, 2025 | 46.70 Mn |
| Jun 30, 2025 | 34.10 Mn |
| Mar 31, 2025 | 36.40 Mn |
| Dec 31, 2024 | 39.40 Mn |
| Sep 30, 2024 | 58.80 Mn |
| Jun 30, 2024 | 54.70 Mn |
| Mar 31, 2024 | 59.60 Mn |
| Dec 31, 2023 | 54.80 Mn |
| Sep 30, 2023 | 39.30 Mn |
| Jun 30, 2023 | 60.90 Mn |
| Mar 31, 2023 | 50.30 Mn |
| Dec 31, 2022 | 49.70 Mn |
| Sep 30, 2022 | 45.40 Mn |
| Jun 30, 2022 | 47.60 Mn |
| Mar 31, 2022 | 51.00 Mn |
| Dec 31, 2021 | 39.90 Mn |
| Sep 30, 2021 | 35.90 Mn |
API Access
Automatic Data Processing Capital Expenditures 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=capital-expenditures&ticker=ADP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "capital-expenditures", "ticker": "ADP", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=capital-expenditures&ticker=ADP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();