diff --git a/docs/install_guides/installing-openvino-from-archive-macos.md b/docs/install_guides/installing-openvino-from-archive-macos.md
index e936e0faa10..c10853bed61 100644
--- a/docs/install_guides/installing-openvino-from-archive-macos.md
+++ b/docs/install_guides/installing-openvino-from-archive-macos.md
@@ -1,8 +1,10 @@
 # Install OpenVINO™ Runtime on macOS from an Archive File {#openvino_docs_install_guides_installing_openvino_from_archive_macos}
 
-With the OpenVINO™ 2022.2 release, you can download and use archive files to install OpenVINO Runtime.
+With the OpenVINO™ 2022.2 release, you can download and use archive files to install OpenVINO Runtime. The archive files contain pre-built binaries and library files needed for OpenVINO Runtime, as well as code samples.
 
-You can also check the [Release Notes](https://software.intel.com/en-us/articles/OpenVINO-RelNotes) for more information on updates in this release.
+Installing OpenVINO Runtime from archive files is recommended for C++ developers. If you are working with Python, the PyPI package has everything needed for Python development and deployment on CPU and GPUs. Visit the [Install OpenVINO from PyPI](installing-openvino-pip.md) page for instructions on how to install OpenVINO Runtime for Python using PyPI.
+
+See the [Release Notes](https://software.intel.com/en-us/articles/OpenVINO-RelNotes) for more information on updates in the latest release.
 
 > **NOTE**: Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter can be installed via [pypi.org](https://pypi.org/project/openvino-dev/) only.
 
@@ -11,9 +13,14 @@ You can also check the [Release Notes](https://software.intel.com/en-us/articles
 ## System Requirements
 
 @sphinxdirective
+
 .. tab:: Operating Systems
 
-  macOS 10.15
+  macOS 10.15, 11, 12, and 13 versions with the x86 architecture, 64 bits
+  
+  .. note::
+   
+     Only macOS 10.15 is fully validated with OpenVINO. Other versions depend on the compatibility of macOS.
 
 .. tab:: Hardware
 
@@ -31,7 +38,7 @@ You can also check the [Release Notes](https://software.intel.com/en-us/articles
 
   * `CMake 3.13 or higher <https://cmake.org/download/>`_ (choose "macOS 10.13 or later"). Add `/Applications/CMake.app/Contents/bin` to path (for default install). 
   * `Python 3.6 - 3.10 <https://www.python.org/downloads/mac-osx/>`_ (choose 3.6 - 3.10). Install and add to path.
-     * Note that OpenVINO is gradually stopping the support for Python 3.6. You are encouraged to use Python 3.7 - 3.10.
+     * Note that OpenVINO is gradually phasing out the support for Python 3.6. You are encouraged to use Python 3.7 - 3.10.
   * Apple Xcode Command Line Tools. In the terminal, run `xcode-select --install` from any directory
   * (Optional) Apple Xcode IDE (not required for OpenVINO™, but useful for development)
 
@@ -41,49 +48,53 @@ You can also check the [Release Notes](https://software.intel.com/en-us/articles
 
 ### <a name="install-core"></a>Step 1: Install OpenVINO Core Components
 
-1. Select and download the OpenVINO™ archive files from [Intel® Distribution of OpenVINO™ toolkit for macOS download page](https://software.intel.com/en-us/openvino-toolkit/choose-download/free-download-macos). There are typically two files for you to download: 
+1. Open a command prompt terminal window. 
+2. Create the `/opt/intel` folder for OpenVINO by using the following command. If the folder already exists, skip this command.
    ```sh
-   m_openvino_toolkit_<operating system>_<release version>_<package ID>_x86_64.tgz
-   m_openvino_toolkit_<operating system>_<release version>_<package ID>_x86_64.tgz.sha256
-   ``` 
-   where the `.sha256` file is used to verify the success of the download process.
-
-2. Locate the downloaded files in your system. This document assumes the files are in your `Downloads` directory. 
-
-3. Open a command prompt terminal window, and verify the checksum of the `sha256` file by using the following command:
-   ```sh
-   shasum -c -a 256 <archive name>.tgz.sha256
+   sudo mkdir /opt/intel
    ```
-   If any error message appears, check your network connections, re-download the correct files, and make sure the download process completes successfully.
+   > **NOTE**: The `/opt/intel` path is the recommended folder path for installing OpenVINO. You may use a different path if desired.
 
-4. Extract OpenVINO files from the `.tgz` file:
+3. Browse to the current user's `Downloads` folder:
    ```sh
-   tar xf <archive name>.tgz -C <destination_dir>
+    cd <user_home>/Downloads
+    ```
+    
+4. Download the [OpenVINO Runtime archive file for macOS](https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.2/macos/), extract the files, rename the extracted folder and move it to the desired path:
+   ```sh
+   curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.2/macos/m_openvino_toolkit_osx_2022.2.0.7713.af16ea1d79a_x86_64.tgz --output openvino_2022.2.0.7713.tgz
+   tar -xf openvino_2022.2.0.7713.tgz
+   sudo mv m_openvino_toolkit_osx_2022.2.0.7713.af16ea1d79a_x86_64 /opt/intel/openvino_2022.2.0.7713
    ```
-   where the `<destination_dir>` is the directory that you extract OpenVINO files to. You're recommended to set it as `/opt/intel/`.
-   The standard OpenVINO `INSTALL_DIR` referenced in this document is `/opt/intel/openvino_<version>`.
 
-For simplicity, you can create a symbolic link to the latest installation: `/opt/intel/openvino_2022/`. 
+5. For simplicity, it is useful to create a symbolic link as below:
+   ```
+   sudo ln -s openvino_2022.2.0.7713 openvino_2022
+   ```
+   > **NOTE**: If you have already installed a previous release of OpenVINO 2022, a symbolic link to the `openvino_2022` folder may already exist. Unlink the previous link with `sudo unlink openvino_2022`, and then re-run the command above.
 
-The core components are now installed. Continue to the next section to configure the environment.
+
+Congratulations, you finished the installation! The `/opt/intel/openvino_2022` folder now contains the core components for OpenVINO. If you used a different path in Step 2, you will find the `openvino_2022` folder there. The path to the `openvino_2022` directory is also referred as `<INSTALL_DIR>` throughout the OpenVINO documentation.
 
 ### <a name="set-the-environment-variables"></a>Step 2: Configure the Environment
 
-You must update several environment variables before you can compile and run OpenVINO™ applications. Set environment variables as follows:
+You must update several environment variables before you can compile and run OpenVINO applications. Open a terminal window and run the `setupvars.sh` script as shown below to temporarily set your environment variables. If your <INSTALL_DIR> is not `/opt/intel/openvino_2022`, use the correct one instead.
 
 ```sh
-source <INSTALL_DIR>/setupvars.sh
-```
+source /opt/intel/openvino_2022/setupvars.sh
+```  
 
-If you have more than one OpenVINO™ version on your machine, you can easily switch its version by sourcing `setupvars.sh` of your choice.
+If you have more than one OpenVINO™ version on your machine, you can easily switch its version by sourcing the `setupvars.sh` of your choice.
 
-> **NOTE**: You can also run this script whenever you start a new terminal session. Open `~/.bashrc` in your favorite editor, and add `source <INSTALL_DIR>/setupvars.sh`. Next time when you open a terminal, you will see `[setupvars.sh] OpenVINO™ environment initialized`. Changing `.bashrc` is not recommended when you have many OpenVINO™ versions on your machine and want to switch among them, as each may require a different setup.
+> **NOTE**: The above command must be re-run every time you start a new terminal session. To set up macOS to automatically run the command every time a new terminal is opened, open `~/.zshrc` in your favorite editor and add `source /opt/intel/openvino_2022/setupvars.sh` after the last line. Next time when you open a terminal, you will see `[setupvars.sh] OpenVINO™ environment initialized`. Changing `~/.zshrc` is not recommended when you have multiple OpenVINO versions on your machine and want to switch among them.
 
 The environment variables are set. Continue to the next section if you want to download any additional components.
 
 ### <a name="model-optimizer"></a>Step 3 (Optional): Install Additional Components
 
-Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter are not part of the installer. The OpenVINO™ Development Tools can only be installed via PyPI now. See [Install OpenVINO™ Development Tools](installing-model-dev-tools.md) for detailed steps. 
+OpenVINO Development Tools is a set of utilities for working with OpenVINO and OpenVINO models. It provides tools like Model Optimizer, Benchmark Tool, Post-Training Optimization Tool, and Open Model Zoo Downloader. If you install OpenVINO Runtime using archive files, OpenVINO Development Tools must be installed separately.
+
+See the [Install OpenVINO Development Tools](installing-model-dev-tools.md) page for step-by-step installation instructions.
 
 OpenCV is necessary to run demos from Open Model Zoo (OMZ). Some OpenVINO samples can also extend their capabilities when compiled with OpenCV as a dependency. To install OpenCV for OpenVINO, see the [instructions on GitHub](https://github.com/opencv/opencv/wiki/BuildOpenCV4OpenVINO).
 
@@ -96,18 +107,35 @@ If you want to run inference on Intel® Neural Compute Stick 2 use the following
 @endsphinxdirective
 
 ## <a name="get-started"></a>What's Next?
+Now that you've installed OpenVINO Runtime, you're ready to run your own machine learning applications! Learn more about how to integrate a model in OpenVINO applications by trying out the following tutorials.
 
-Now you are ready to try out the toolkit. You can use the following tutorials to write your applications using Python and C++.
+@sphinxdirective
+.. tab:: Get started with Python
 
-Start with some Python tutorials:
-   * [Hello Image Classification](https://docs.openvino.ai/latest/notebooks/001-hello-world-with-output.html)
-   * [Convert TensorFlow models with OpenVINO™](https://docs.openvino.ai/latest/notebooks/101-tensorflow-to-openvino-with-output.html)
-   * [Convert a PyTorch model and remove the image background](https://docs.openvino.ai/latest/notebooks/205-vision-background-removal-with-output.html)
+   Try the `Python Quick Start Example <https://docs.openvino.ai/2022.2/notebooks/201-vision-monodepth-with-output.html>`_ to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser.
+   
+   .. image:: https://user-images.githubusercontent.com/15709723/127752390-f6aa371f-31b5-4846-84b9-18dd4f662406.gif
+      :width: 400
 
-To start with C++ samples, see <a href="openvino_docs_OV_UG_Samples_Overview.html#build-samples-macos">Build Sample Applications on macOS</a> first, and then you can try the following samples:
-   * [Hello Classification C++ Sample](@ref openvino_inference_engine_samples_hello_classification_README)
-   * [Hello Reshape SSD C++ Sample](@ref openvino_inference_engine_samples_hello_reshape_ssd_README)
-   * [Image Classification Async C++ Sample](@ref openvino_inference_engine_samples_classification_sample_async_README)
+   Visit the :ref:`Tutorials <notebook tutorials>` page for more Jupyter Notebooks to get you started with OpenVINO, such as:
+   
+   * `OpenVINO Python API Tutorial <https://docs.openvino.ai/2022.2/notebooks/002-openvino-api-with-output.html>`_
+   * `Basic image classification program with Hello Image Classification <https://docs.openvino.ai/2022.2/notebooks/001-hello-world-with-output.html>`_
+   * `Convert a PyTorch model and use it for image background removal <https://docs.openvino.ai/2022.2/notebooks/205-vision-background-removal-with-output.html>`_
+
+.. tab:: Get started with C++
+
+   Try the `C++ Quick Start Example <openvino_docs_get_started_get_started_demos.html>`_ for step-by-step instructions on building and running a basic image classification C++ application.
+   
+   .. image:: https://user-images.githubusercontent.com/36741649/127170593-86976dc3-e5e4-40be-b0a6-206379cd7df5.jpg
+      :width: 400
+
+   Visit the :ref:`Samples <code samples>` page for other C++ example applications to get you started with OpenVINO, such as:
+   
+   * `Basic object detection with the Hello Reshape SSD C++ sample <openvino_inference_engine_samples_hello_reshape_ssd_README.html>`_
+   * `Automatic speech recognition C++ sample <openvino_inference_engine_samples_speech_sample_README.html>`_
+
+@endsphinxdirective
 
 ## <a name="uninstall"></a>Uninstalling the Intel® Distribution of OpenVINO™ Toolkit
 
@@ -116,14 +144,22 @@ To uninstall the toolkit, follow the steps on the [Uninstalling page](uninstalli
 ## Additional Resources
 
 @sphinxdirective
-      
+
 * :ref:`Troubleshooting Guide for OpenVINO Installation & Configuration <troubleshooting guide for install>`
 * Converting models for use with OpenVINO™: :ref:`Model Optimizer User Guide <deep learning model optimizer>`
 * Writing your own OpenVINO™ applications: :ref:`OpenVINO™ Runtime User Guide <deep learning openvino runtime>`
 * Sample applications: :ref:`OpenVINO™ Toolkit Samples Overview <code samples>`
 * Pre-trained deep learning models: :ref:`Overview of OpenVINO™ Toolkit Pre-Trained Models <model zoo>`
-* IoT libraries and code samples in the GitHub repository: `Intel® IoT Developer Kit`_ 
+* IoT libraries and code samples in the GitHUB repository: `Intel® IoT Developer Kit`_ 
 
+<!---
+   To learn more about converting models from specific frameworks, go to:  
+   * :ref:`Convert Your Caffe Model <convert model caffe>`
+   * :ref:`Convert Your TensorFlow Model <convert model tf>`
+   * :ref:`Convert Your Apache MXNet Model <convert model mxnet>`
+   * :ref:`Convert Your Kaldi Model <convert model kaldi>`
+   * :ref:`Convert Your ONNX Model <convert model onnx>`
+--->   
 .. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit
 
 @endsphinxdirective