30 Total Rewards AI use cases

30 Total Rewards AI use cases


Many Total Rewards professionals are interested to use Artificial Intelligence. However, two concerns often emerge as potential roadblocks: 1) data privacy and confidentiality, and 2) not enough practical use cases. In this article I will try to help address both of them.


1. Data Privacy and confidentially

First, to prevent your data being used by AI (to learn and share with others), you can:

  1. turn ' learning off'. For instance, in ChatGPT to go Settings → Data Controls → Turn off ‘Chat history & training’.
  2. use the Microsoft Copilot or ChatGPT versions that are provided or recommended by your company's Digital or IT department. They will likely recommend you to use an 'enterprise' version, which means that data that you feed into it, stays within your company.

Second, to prevent data privacy concerns, just don't input any employee or personal data into AI - unless you are sure it is safe and allowed to do so. I wrote an earlier post about this here.


2. Total Reward use cases

A 'use case' describes how Artificially Intelligence could be applied to achieve specific objectives. From my experience this largely relies on imagination. If you have some understanding of what AI can do - for instance by 'playing' with it - then it will be easier to imagine how AI can be used in your job.

To help you I developed a simple list of 30 use cases. And, to address one of the concerns, most of them also don't require you to input data on employees or people.

Click on the image below you download it as a PDF or visit this page, where you can also suggest suggestions for potential additional use case.


Since I understand many of you are Total Rewards professionals I'm not going to dive into these use cases, but I'd like to stress that - in my view - they are all achievable. Of course there are more use cases, especially in the field of compensation, but this list is just to get your started.

If I have more time over the next months I may focus on a few more in more detail. But, for now, I hope this is helpful and I look forward to your thoughts or suggestions on what you think AI can help you with in the area of Total Rewards.


Together, with AI, let's advance and transform the Total Rewards profession!



Note: The statements, views, or opinions expressed in my LinkedIn profile, posts and articles represent my own views. Any comments from those responding to my postings belong to, and only to, the responder posting the comment.

Sameer Yaqoubi

Sr. Rewards Partner in COWI

4 个月

Martin Smit, I sent you a message in inbox. Can we connect?

回复
Ran He

Program Manager DDIT LDC Release Integration

6 个月

Petr Hantych as we discussed today, chat under policy design can be a good use case

回复
Woodley B. Preucil, CFA

Senior Managing Director

6 个月

Martin Smit Very interesting. Thank you for sharing

Sofia Platero

Enabling transformations with a human centric approach - | Business Transformation | Project Leadership | Consulting | Coaching | HR Tech & AI | Employee Experience | Digital Transformation | HR- People and Culture |

6 个月

Great and concrete list Martin !!! I’ll repost Well done and thanks for sharing this

Christine Hendrickson

VP at Syndio | EU Pay Transparency Directive, Equal Pay Act, Transparency + Pay Gap Reporting Nerd

6 个月

Great list Martin Smit.

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