Automatic Data Processing (ADP) Capital Expenditures (2009 - 2026)
Automatic Data Processing's Capital Expenditures was $52.7 million in fiscal Q1 2027 (quarter ended Sep 30, 2026), up 12.8% from $46.7 million a year earlier but down 27.6% from the prior quarter.
Automatic Data Processing (ADP) Capital Expenditures (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Automatic Data Processing's Capital Expenditures was $202.6 million through Sep 30, 2026, up 29.4% year-over-year; for FY2026 (ended Jun 30, 2026), it 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%).
- Quarterly Capital Expenditures has moved between $26.5 million (fiscal Q2 2026) and $72.8 million (fiscal Q4 2026) over five years.
- Compared with a year earlier, Capital Expenditures has increased for three straight quarters, with growth averaging 0.9% over the last eight quarters.
- 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 Q1 2027 was $72.8 million (Q4 2026), $50.6 million (Q3 2026) and $26.5 million (Q2 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Capex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 413.65 Bn | 378.59 Bn | 1.93 Bn | 8.01 Mn |
| 2 | Oracle | 374.28 Bn | 246.84 Bn | - | 28.50 Bn |
| 3 | Sap Se | 294.90 Bn | 222.88 Bn | 8.64 Bn | -192.12 Mn |
| 4 | Salesforce | 186.99 Bn | 142.87 Bn | 8.70 Bn | 171.00 Mn |
| 5 | Automatic Data Processing | 120.08 Bn | 106.87 Bn | 2.53 Bn | 52.70 Mn |
| 6 | ServiceNow | 113.02 Bn | 92.28 Bn | 2.90 Bn | 91.00 Mn |
| 7 | Intuit | 95.72 Bn | 75.07 Bn | 3.44 Bn | 27.00 Mn |
| 8 | Relx | 74.73 Bn | 73.84 Bn | - | - |
| 9 | Strategy | 57.35 Bn | 44.49 Bn | 89.63 Mn | 462,000.00 |
| 10 | Thomson Reuters | 52.16 Bn | 48.13 Bn | - | -176.00 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 52.70 Mn |
| 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 |
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();