Autozone (AZO) Tax Provisions (2009 - 2026)
Autozone (AZO) posted Tax Provisions of $171.78 million for fiscal Q3 2026 (quarter ended May 9, 2026), up 17.3% from $146.45 million a year earlier and up 40.3% from the prior quarter.
Autozone (AZO) Tax Provisions (2009 - 2026) Analysis & Trends
For the trailing twelve months through May 9, 2026, Tax Provisions at Autozone was $652.31 million, down 2.1% year-over-year; for FY2025 (ended Aug 30, 2025), it came in at $636.09 million, down 5.7% from FY2024.
- Annual Tax Provisions shows a five-year compound annual growth rate of 5.6% (FY2020 to FY2025).
- In prior fiscal years, Autozone's Tax Provisions was $674.7 million in FY2024 (+5.6%), $639.19 million in FY2023 (-1.6%), $649.49 million in FY2022 (+12.2%) and $578.88 million in FY2021 (+19.7%).
- Quarterly Tax Provisions has run from a low of $110.02 million in fiscal Q2 2025 to a high of $248.93 million in fiscal Q4 2023 over five years.
- On a year-over-year basis, Tax Provisions increased in four of the last eight quarters, with an average decline of 0.9%.
- The strongest year-over-year quarter for Tax Provisions in the past five years was fiscal Q1 2024, with growth of 30.0%; the weakest was fiscal Q1 2023, with a decline of 19.2%.
- According to Business Quant data, Tax Provisions for the three prior fiscal quarters was $122.39 million (Q2 2026), $147.11 million (Q1 2026) and $211.03 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Taxes (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,659.84 Bn | 2,176.54 Bn | 104.83 Bn | 18.20 Bn |
| 2 | Home Depot | 287.59 Bn | 280.83 Bn | 16.12 Bn | 1.55 Bn |
| 3 | Tjx Companies | 147.38 Bn | 124.93 Bn | 5.07 Bn | 498.00 Mn |
| 4 | Lowes Companies | 105.03 Bn | 97.99 Bn | 8.58 Bn | 776.00 Mn |
| 5 | Ross Stores | 74.93 Bn | 57.86 Bn | 2.12 Bn | 283.46 Mn |
| 6 | Target | 71.05 Bn | 65.64 Bn | 8.94 Bn | 582.00 Mn |
| 7 | O Reilly Automotive | 70.25 Bn | 69.33 Bn | 2.52 Bn | 209.01 Mn |
| 8 | Carvana | 69.96 Bn | 61.56 Bn | 1.38 Bn | 66.00 Mn |
| 9 | Autozone | 46.92 Bn | 45.82 Bn | 2.52 Bn | 171.78 Mn |
| 10 | JD.com | 31.91 Bn | -78.27 Bn | 8.71 Bn | -291.00 Mn |
Historic Data
| Date | Value |
|---|---|
| May 9, 2026 | 171.78 Mn |
| Feb 14, 2026 | 122.39 Mn |
| Nov 22, 2025 | 147.11 Mn |
| Aug 30, 2025 | 211.03 Mn |
| May 10, 2025 | 146.45 Mn |
| Feb 15, 2025 | 110.02 Mn |
| Nov 23, 2024 | 168.59 Mn |
| Aug 31, 2024 | 241.32 Mn |
| May 4, 2024 | 144.03 Mn |
| Feb 10, 2024 | 125.59 Mn |
| Nov 18, 2023 | 163.76 Mn |
| Aug 26, 2023 | 248.93 Mn |
| May 6, 2023 | 136.45 Mn |
| Feb 11, 2023 | 127.82 Mn |
| Nov 19, 2022 | 125.99 Mn |
| Aug 27, 2022 | 229.78 Mn |
| May 7, 2022 | 151.21 Mn |
| Feb 12, 2022 | 112.53 Mn |
| Nov 20, 2021 | 155.97 Mn |
| Aug 28, 2021 | 200.14 Mn |
Autozone Tax Provisions 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=tax-provisions&ticker=AZO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "tax-provisions", "ticker": "AZO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=tax-provisions&ticker=AZO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();