Artificial Intelligence In HR – Are You Ready?

It’s coming, whether we like it or not. Look at the topics and exhibitors at any HR conference. It’s coming. Artificial intelligence has the potential to relieve overburdened HR team from decisions that can be made more easily and more scientifically through decision science.

Bad data wastes time and may lead to poor decisions. Technology doesn’t really know the data is bad; it solves for the match you asked it to solve.

When you think about filling a job, you are solving an equation. On one side are the requirements of the job. On the other side are the skills, knowledge, and traits of the employees who fill or may fill the job. The decision to hire is a gap analysis between the two points – demand and supply. That’s what technology does to enable more qualified candidates for jobs; matches the need to the supply of candidates. It works in a similar manner to provide employee directed growth and learning opportunities as well. But, before we can use AI to make strategic decisions we must ensure that the data is accurate. Bad data wastes time and may lead to poor decisions. Technology doesn’t really know the data is bad; it solves for the match you asked it to solve. Now is the time to make sure that future technology has credible, timely and accurate data so that it really can help make good decisions.

The “Job” side of the equation

Take a collective look at the information about jobs that the HR team maintains. By information, I mean the knowledge, skills, and abilities that have been defined. Review job descriptions, job postings, competencies used in performance management and learning paths. By collective look, I mean working together as an HR team to review all of the job data, produced by each team, for each purpose. Ask these questions:

-Do the job requirements match across all HR platforms? If not, should they?

-Do the job requirements actually describe the skills, knowledge, and abilities specifically enough, or have the jobs been clustered and combined for simplicity so that they are too generic to really explain the job?”

-Is the data accurate? How do you know, and who is responsible for timely maintenance?

The “Employee” side of the equation

Employee and manager self-service takes a huge administrative burden off HR but places it in the hands of people who don’t understand the consequences of inaccurate and untimely data. Now is the time to educate those who enter the data on the importance of accuracy, and to implement audit trails to catch and resolve outliers. Employee and manager self-service offers a menu of choices, allowing a data field to be completed with pre-defined data. Are those choices clear and well-defined? Job codes are a key element of matching an employee to a job; are managers too hurried to use the right code?

Termination codes are important to understand retention efforts. Do you offer so many choices that the hurried manager gives up and grabs the first code that seems to fit?

Now is also a great time to make sure that the data codes you use are current, and exactly what you need. If you put 100 codes out there just in case you might need them, that’s 99 possible errors a manager can make.

Conferences and vendors paint a rosy picture of capabilities we haven’t even thought of. Let’s be ready.


Carol Anderson
Carol Anderson
CAROL is the founder and Principal of Anderson Performance Partners, LLC, a business consultancy focused on bringing together organizational leaders to unite all aspects of the business – CEO, CFO, HR – to build, implement and evaluate a workforce alignment strategy. With over 35 years of executive leadership, she brings a unique lens and proven methodologies to help CEOs demand performance from HR and to develop the capability of HR to deliver business results by aligning the workforce to the strategy. She is the author of Leading an HR Transformation, published by the Society for Human Resource Management in 2018, which provides a practical RoadMap for human resource professionals to lead the process of aligning the workforce to the business strategy, and deliver results, and writes regularly for several business publications.

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  1. Thanks a lot, Ms. Carol, for sharing such an important message related to one of the most significant growth catalysts in designing our future. Since I am deeply involved in research related to the Fourth Industrial Revolution, and also in the final stages of releasing my book on “IoT,” I have access to a number of scientific papers and reports discussing the same.

    Kindly allow me to share with you a report I saw in my email this morning. It relates to the wide-ranging, and as yet unaddressed ‘bias’ aspect of AI:

    Thank You!

    My family joins me in Wishing Happy Holidays, and A Very Happy, Healthy, and Prosperous New Year 2019 to You and to All Your Loved Ones!

    • Happy holidays to you and your family as well. Thanks for sharing the article – it has been interesting to see the real world implications of AI over the past year. I’ve been in the business world for a long time, and watch every attempt at creating something that will replace the routine tasks for humans. At least in the HR arena, what I’ve come to realize is that there really are few routine tasks, as there are just too many variables in human beings to capture. In the 1990s, we tried to create an HR Customer Service Center that could answer all the routine questions that employees had about their benefits, their work, etc., and no matter how “right” we got it, employees still had more questions than could be answered. At the risk of sounding cynical, we didn’t do so good with the intentions and aspirations of the third industrial revolution, so I’m not sure how well we’ll do with the fourth, but I’ll be interested in reading your research.