LinkedIN Learning Elevates the WS1 Virtual Assistant

Recently, I discussed building the VMware Workspace ONE Virtual Assistant, which was a wonderful experience for me. One thing that I was missing was a more “assistant”-like approach. We are elevating this one step further by integrating the LinkedIN Learning Chatbot to empower users to access a variety of trainings quickly and easily. Please join me in this brief introduction to creating the REST API integration and then easily adding it into Workspace ONE.

Creating the REST API Access in LinkedIN Learning

It was incredibly easy to create your client ID and Secret inside of the LinkedIN console. Let’s walk through it real quickly. If you need more detail about their REST API check out this article here

First, you click on “Me” and select “Integrate”

Click “API Application Provisioning” and “Add Application”

Enter values like you see below and click “Next”

Review the T&C and click “Agree and Save”

Once done, you will see the Client Id and Client Secret that you will need to configure the Chatbot.

Creating the Workspace ONE Chatbot to Workspace ONE UEM

The creation of the Chatbot is just as easy. Let’s walk through the steps together!

Find the Chatbot in the Catalog inside of Content > Mobile Flows and click “Add”

Input the Base URL of https://api.linkedin.com/v2 as seen below and click “Next” twice.

Input your client_id and and client_secret from the previous section and click “Next”, “Next”, “Submit” to complete the setup. Don’t forget that once it’s done, you may need 15-30m for replication to occur before it works inside of the virtual assistant.

Demoing the LinkedIN Learning Functionality Powered by Mobile Flows and Virtual Assistant

As you can see, the setup for this is really quick and painless (especially compared to other products). Let’s check out a short demo of the Virtual Assistant experience.

Final Thoughts

The beauty of the Workspace ONE Virtual Assistant is its pliability. You can build custom connectors, leverage OOTB connectors, and write custom commands inside of IBM Watson to extend the experience to meet your culture, needs, and so much more. I think it’s something that is definitely worth exploring through your journey of the digital workspace.

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