Will AI eliminate the HR Analyst role?

It's hard to know who or what to believe.

According to the experts, ChatGPT and Artificial Intelligence could make the role of the data analyst redundant.  On the other hand, the human resource analyst manager (also known as people analytics manager or talent analytics manager) has been the second fastest-growing job title over the last five years based on recently published LinkedIn research.  

This article will explore how innovations in AI will change what it means to be an HR Analyst. As we see it, the job function will change but the role will not be eliminated. In fact, HR Analytics stands at the intersection of organizational health and financial performance.    

Separating the signal from the noise.

The consultants at Gartner coined the term "citizen data scientist” to refer to a professional who performs data science tasks without formal training or skills in statistics or advanced analytics. The rationale behind the citizen data scientist is that innovation in data science would make it significantly easier for laymen end-users to use tools powered by Machine Learning and other forms of Artificial Intelligence.

The assumption is based on the growth in tools and methodologies such as Automated Machine Learning or AutoML which reduces the need for data scientists to perform manual tasks. This is done by training algorithms to perform many of the repetitive and labor-intensive aspects of Machine Learning such as data cleansing and model selection.

Based on this outlook, here is the specific prediction from Gartner: more than 40% of data science tasks would be automated in a three-year period.  This prediction was made in 2017 when Gartner stated that “citizen data scientists will surpass data scientists in the amount of advanced analysis produced by 2019.”

Interestingly, Gartner has been somewhat quiet on this prediction in recent years.  Although the citizen data scientist is a valid concept, the democratization of the data science profession is yet to occur at the rate they predicted.

In recent months, the news media has been reporting on Generative-AI and ChatGPT and once again, we are hearing that this is a game-changing technology that will upend the job market.

The rationale should sound familiar.  According to Forbes, ChatGPT can “generate code infinitely faster than a human can, introducing a whole new level of speed when it comes to building software... it also allows for faster and easier identification of bugs and inconsistencies that get in the way of faster releases.”

With so much discussion today about AI, it’s time to re-think the role of the HR Analyst and explore how it will likely evolve.

HR Analyst and the current state of HR reporting

There are four basic analytics categories: Descriptive, Diagnostic, Predictive, and Prescriptive.  

Descriptive Analytics: Descriptive analytics uses past data to gain insights into what has happened in the organization, such as identifying trends, patterns, and key metrics.  An example is the voluntary turnover rate.  

Diagnostic Analytics: Diagnostic analytics aims to understand the reasons or underlying causes behind the patterns and trends observed in descriptive analytics. For instance, diagnostic analytics are the factors that contribute to high employee turnover, such as low engagement scores, and limited career mobility.

Predictive Analytics: Predictive analytics uses historical data to make informed forecasts about the future. For example, the expected employee attrition rate in the next two quarters.  

Prescriptive Analytics: Prescriptive analytics goes beyond prediction and provides recommendations on the best course of action to achieve desired outcomes. It combines predictive models with optimization techniques and then suggests specific intervention strategies. For example, identifying teams with the highest resignation risk and then intervening to support the career development of high-potential employees.

AI and the closing of the analytics loop

The following table provides examples of the four HR analytics categories:

An Analyst may use statistical modeling software like Python and R for frequency distributions or regression analysis but is unlikely to tap into AI capabilities. In general, HR Analysts are more focused on descriptive analytics than on how to decipher and address problems that occur.  

Much of this work is labor intensive, requiring manual statistical modeling.  The result is that instead of finding risks and opportunities that can materially impact the organization and business, the Analyst may be spending more time on the current state.

Here is where AI is likely to have a significant impact.  First, analytics tools will become much easier to use.  Whereas today, part of the Analyst's role is spent on data collection, analysis, and summarizing key insights and visualization of reports, much of this can now be (or soon be) automated.  

Not only does this mean that the role becomes more efficient, but it also frees up the time of the Analyst to provide more intense and strategic insights.  

Another unexpected consequence is that if the job requirements for the role become less technical because AI tools can replace the need for statistical analysis, the position can be opened to people with less training in analytics and more business and people acumen: the so-called Citizen Data Scientists.

When reporting, visualization, and analysis of complex data can be performed automatically by AI, the HR Analyst becomes a storyteller who can connect the dots between information and action.  Instead of analyzing survey data and extracts from HRIS databases, the Analyst can work with managers to assess how to translate the potential risks identified from AI algorithms into actionable interventions.  

Summary and Conclusion

Artificial Intelligence is here to stay, and its adoption by HR is inevitable.  As with other areas of AI such as ChatGPT, applications of AI that only recently sounded like sci-fi, are now part of our daily lives.

While AI is expected to bring significant changes to the role of an HR Analyst, it is unlikely to eliminate the role entirely. At the same time, the job function and required skillset for the HR Analyst will likely morph into something new, opening possibilities for collaboration between HR and the rest of the organization.

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