Automatic Data Processing (ADP) Research & Development (2022 - 2026)
Automatic Data Processing (ADP) posted Research & Development of $265.9 million for fiscal Q4 2026 (quarter ended Jun 30, 2026), down 1.3% from $269.4 million a year earlier but up 4.7% from the prior quarter.
Automatic Data Processing (ADP) Research & Development (2022 - 2026) Analysis & Trends
For FY2026 (ended Jun 30, 2026), Automatic Data Processing's Research & Development came in at $1.03 billion, up 4.1% from FY2025.
- Annual Research & Development has increased for four consecutive fiscal years, with a four-year compound annual growth rate of 6.5% (FY2022 to FY2026).
- In prior fiscal years, Automatic Data Processing's Research & Development was $988.6 million in FY2025 (+3.4%), $955.7 million in FY2024 (+13.1%), $844.8 million in FY2023 (+5.8%) and $798.6 million in FY2022.
- Quarterly Research & Development has run from a low of $204.2 million in fiscal Q2 2023 to a high of $269.4 million in fiscal Q4 2025 over five years.
- On a year-over-year basis, Research & Development increased in six of the last eight quarters, with growth averaging 3.8%.
- The strongest year-over-year quarter for Research & Development in the past five years was fiscal Q3 2024, with growth of 16.3%; the weakest was fiscal Q1 2025, with a decline of 1.6%.
- According to Business Quant data, Research & Development for the three prior fiscal quarters was $253.9 million (Q3 2026), $257.8 million (Q2 2026) and $251.2 million (Q1 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | R&D (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 480.73 Bn | 449.68 Bn | 1.64 Bn | 192.51 Mn |
| 2 | Oracle | 399.91 Bn | 272.04 Bn | - | 2.40 Bn |
| 3 | Sap Se | 262.30 Bn | 190.08 Bn | 8.40 Bn | -2.14 Bn |
| 4 | Salesforce | 202.26 Bn | 158.13 Bn | 8.70 Bn | 1.69 Bn |
| 5 | ServiceNow | 153.84 Bn | 132.30 Bn | 2.82 Bn | 915.00 Mn |
| 6 | Automatic Data Processing | 114.84 Bn | 96.97 Bn | 2.51 Bn | 265.90 Mn |
| 7 | Intuit | 91.04 Bn | 70.38 Bn | 3.44 Bn | 857.00 Mn |
| 8 | Relx | 70.51 Bn | 69.60 Bn | - | - |
| 9 | Strategy | 53.24 Bn | 46.23 Bn | 81.55 Mn | 23.10 Mn |
| 10 | Thomson Reuters | 48.40 Bn | 45.18 Bn | - | - |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 265.90 Mn |
| Mar 31, 2026 | 253.90 Mn |
| Dec 31, 2025 | 257.80 Mn |
| Sep 30, 2025 | 251.20 Mn |
| Jun 30, 2025 | 269.40 Mn |
| Mar 31, 2025 | 247.10 Mn |
| Dec 31, 2024 | 239.50 Mn |
| Sep 30, 2024 | 232.60 Mn |
| Jun 30, 2024 | 247.90 Mn |
| Mar 31, 2024 | 242.70 Mn |
| Dec 31, 2023 | 228.70 Mn |
| Sep 30, 2023 | 236.50 Mn |
| Jun 30, 2023 | 222.20 Mn |
| Mar 31, 2023 | 208.60 Mn |
| Dec 31, 2022 | 204.20 Mn |
| Sep 30, 2022 | 209.80 Mn |
Automatic Data Processing Research & Development 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=research-and-development&ticker=ADP&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "research-and-development", "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=research-and-development&ticker=ADP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();