AI-enabled HR: Unlocking the potential with employee buy-in

Artificial Intelligence is the “flavour of the day”. We are subjected to predictions about its future impact – negative and positive – on all aspects of life. Organisations use AI-washing to Artificially Inflate (a different type of “AI”) their share price or attractiveness to investors. The world has gone a little AI crazy.

For these reasons, I have been reluctant to write about AI over the past few months. Nonetheless, like many of you, I do reflect about the future AI-enabled world. For example, I think about how PeopleWeek could or should build AI capabilities into our technology, and about how people management practices might evolve using AI. On the other hand, I am brought quickly back down to earth when I think about how many medium- and large-sized organisations do not even provide their employees, managers, and HR with basic HR technology, never mind AI.

In this article I consider the application of AI in human resources – as distinct from the deployment of AI tools in an employee’s own role – in terms of its potential impact on the HR function and on employees. I contend that while AI can offer many benefits for HR, employees will approach its adoption with scepticism, only embracing AI tools in HR if they enhance their overall work experience.

Benefits for the HR Function

The area of HR that has seen the most usage of AI (and Machine Learning) up till now is recruitment. Advocates of AI-powered recruitment tools argue that it drives more accurate and objective screening and selection, as well as a faster and more engaging candidate experience. Critics point out the potential data privacy risks and express concern about the possibility of an AI system being trained on past recruitment data, which may unintentionally perpetuate biases, leading to unjust and discriminatory results for specific applicant demographics.

However, there are many other potential uses of AI that would make the job of HR teams more efficient and enjoyable. Here are three examples with varying degrees of complexity:

Low Complexity

Job descriptions are a foundational tool for so many HR activities, including recruitment, performance management, workforce planning, compensation benchmarking, career planning, and talent management. Yet, in my experience, most employees do not have an up to date job description because it is too time consuming for HR and managers to do it properly. With only a little bit of basic information, a tool like Chat GPT can quickly write a job description that may be a ~70% match and can then be personalised and finalised with relatively little effort.

Medium Complexity

Job and compensation benchmarking requires very large data sets. In particular, the task of matching like-for-like jobs across relevant geographies and industries is painful. I used to dread the annual process of preparing the data with the survey vendors. Sadly, at least double the amount of time was spent on data preparation than data analysis of the results to make informed decisions. AI could surely take a lot of the pain out of this important activity and free up HR time for analysis and informed recommendations.

High Complexity

AI could drive Predictive HR. Today, HR tends to be reactive rather than predictive. For example, HR intervenes because there is a vacancy, a performance issue, a behavioural issue, a resignation, etc. With the right data set and algoriths, AI could help organisations to identify patterns that lead to the need for reactive HR interventions, and thereby mitigate them or avoid them altogether. For example, imagine if HR had access to data that indicates a certain employee – and a highly valued one at that – is susceptible to a near-term burn out. This “prediction” could be derived from analyzing the employee’s data alongside a comprehensive historical dataset encompassing individuals – both internal and external to the organization – who have previously experienced burnout. Factors considered may include age, gender, family situation, marital status, income level, post code, performance evaluations, vacation patterns, and absenteeism.

Benefits for Employees

The benefits of AI for HR would also indirectly benefit employees. Nonetheless, I doubt that any of the examples above would particularly interest them and predictive HR may raise concerns about the use of personal data even if it could prevent the talented employee having a burn out.

We know that some industries are already shedding jobs due to AI-powered productivy gains. This is very rarely the result of an entire job having been replaced by AI but, rather, some parts of many jobs having been replaced by AI and this, in turn, meaning that collectively less humans are needed. This trend is an important factor in the record share prices of the “Magnificent Seven” technology giants: they have been able to significantly increase revenues whilst reducing costs thanks to AI-driven productivity increases and resultant workforce reductions.

As such, the starting point for many employees is that AI is a threat to their job security, earning power, and personal data. For this reason, organisations will have quite a challenge selling the virtues of using AI in HR. Using AI to automate administrative people management tasks could also alienate employees by making HR less human or personal. For example, whilst ChatGPT could help managers to prepare an employee’s job description or a reference letter, an employee would surely be upset if the AI generated output was a lazy, generic job description or reference letter that did not acurately reflect their responsibilities and achievments.

Organisations need to think about uses of AI within HR that will make the quality of working life better for employees, as opposed to implementing tools that will make them less relevant and job secure. Here are some examples of how AI within HR could benefit employees:

Job Fit – The precise and thoughtful use of AI in recruitment can help organisations and job seekers (and internal candidates) to find the right match of role and organisation to person. This would increase job satisfaction and, therefore, both productivity and retention.

Process and Product Improvements – AI can be used to perform organisational analysis designed to identify trends in customer and employee complaints and pain points. This could help to drive improvements in processes, product design, and systems that would make work more enjoyable and rewarding. This type of analysis would require the processing and cross-referencing of a large data sets, for example from emails, ticketing systems, performance reviews, customer surveys, etc.

Information Management – In many medium- and large-sized organisations, employees spend excessive time trying to find the information they need on the corporate intranet, SharePoint, Slack channel, etc. The use of an AI chatbot can help employees to find answers to questions far more quickly, for example information on company policies, procedures, training material, etc.

Well-being – Tools exists today to help proactively identify stress or tension amongst employees by analyzing their voices during video meetings. This software is integrated into the company’s meeting app and performs the analyses using machine learning algorithms.


There is a lot of potential for the use of AI within HR and this goes well beyond recruitment. It offers the prospect of HR departments becoming more efficient, thereby freeing up time to focus on higher value-added tasks. It also raises the exciting possibility of Predictive HR, though this will raise concerns about the use of personal data. Despite this great potential, which must be embraced by HR rather than resisted, I see two major challenges. The first is that organisations need to be willing to invest more money in HR technology, be it in AI or HR software in general. HR departments in most organisations still struggle to secure the fair share of the IT budget despite CEOs declaring that people are their greatest asset (“blah, blah, blah”). Secondly, organisations – led by HR – will need to demonstrate to employees that AI used within HR will improve their quality of life: not all workplace AI threatens job security, earning power, and data privacy.