Use of Artificial Intelligence in HR

Imagine this!!!

Close-up 1: One fine morning you log-in to your mailbox, and find a mail regarding a specific opportunity in an organization you have always admired. You submit your CV and within a few hours get an intimation that your profile has been shortlisted, and an initial interaction is slotted for tomorrow. You log in to the link for the interview and the voice at the other end, keep on asking probing questions, and based on your answers, asks for further clarification. At the end of the interaction, it is confirmed that you are selected for the position. Almost immediately you get an offer letter in your inbox. You would think – what an efficient HR department!!!

Close-up 2: You are a manager having a busy day. Your HRBP walks up to your desk and you have a conversation. She points out specific two employees in your team who are actively contemplating leaving the organization and one employee who is under tremendous stress. And it is not just her intuition or what she has heard on the grape-vine – she shows you data to substantiate her. You would think – Not even KGB could have topped that!!!!!

These are algorithms at work in the workplace!!!!!

In Close-up 1, the algorithms have analyzed your personality and your strengths and weaknesses based on your internet foot-print, they know your preferred organizations done a matching with their requirements and send out a communication to you, knowing full well that there is a high likelihood that you will be interested and that your profile matches their requirement. The voice at the other side was not a highly skilled interviewer, it was an algorithm again, trained to interpret your answers, and surprises, your facial expression and your body language in videos, and make a match with their requirements. The offer letter that has released to you was created, reviewed, and approved based on clear algorithms designed on the decision matrix. Now things don’t get more efficient than that!!!! Or does it?

On Close up 2, there are tools available such as Organisation Network Analysis (ONA) which monitors employee sentiments, and not through surveys. It analyses tones and languages to know the nature and type of organization interactions and gives real-time insight into the employee moods and sentiments. Likewise, by considering a diverse array of data as diverse from leave and attendance pattern to response on emails, etc. it is possible to predict the likelihood of an employee leaving the organization. Also, the same tools can be used to drive change in the organization by identifying key influencers and onboarding them to drive change.

These are only a few of the myriad of ways artificial intelligence is impacting the workplace.

For example, did you know that through AI you can

a. Influence employee’s decision and motivation using AI

b. Analyze employee’s performance and give them concrete feedback

c. Match a candidate with a line manager to see the right reporting fit based on personality profiles

d. Customize career paths based on your daily activities.

e. Predict likely accidents in the workplace by studying the mental pattern of workers

f. Create learning content

Similar results are being obtained as we speak, in the area of consumers – so, then why not HR? We need to understand the different types of AIs – e.g. Internet AI, Business AI, Perception AI (facial and voice recognition), Autonomous AI (Deep learning, etc.), and what are the possibilities each one offer in the space of HR. It is worthwhile to remember that AI can not only transfer employee experience in routine areas such as time and attendance, or benefits administration, but also more complex areas such as coaching, capability building and engagement, and motivation.

I personally think, since most of us in HR don’t understand AI, the way AI is leveraged in HR is still in its infancy. We have to learn the way AI is being leveraged in various industries (healthcare, retail, automobile, oil and natural gas, banking, etc.) and functions (marketing, Supply Chain, customer service, Research, etc.) and draw inspiration about possibilities here. Of course, the degree of investment a corporation will do in leveraging AI in these functions would be significantly larger in nature in view of direct impact on revenue and business, compared to HR. However, things are changing and in larger corporations, the investment in AI in the arena of HR is surging significantly.

As an AI & digital enthusiast, I would suggest a few things

a. Start building your data strategy – collect as much data as possible about your employees. Many of them may be getting collected even now, but not being leveraged. The time is coming when those “dormant” data will transform your people practices.

b. Start experimenting in small steps – it may be Robotic Process Automation (RPA), or implementing an AI-based CV sourcing software or even a chatbot. You HAVE to start understanding AI!!

c. Watch out what is happening in other functions and apparently un-related fields and imagine the possible implications on HR. This is one skill you are going to need badly in the future.

@Crompton, we embarked on the AI journey around two and a half years ago, and it has turned out to be a vastly different proposition than what we thought it would be. Now we have AI applications in various areas of HR including recruitment, employee engagement, learning, etc. But one thing that stands out is something we all know but don’t really appreciate – the criticality of having reams and reams of data.

Digital Transformation in the Covid-19 Era

Like every other function, HR is also struggling to understand the impact of the Covid-19 crisis. A lot of existing assumptions and beliefs are being put to test. However, among all the chaos and gloom, the one silver lining that stands out is – The power of humans to adjust to the emerging situation and the human ingenuity and creativity that a novel situation can throw up. Well, history is full of it, but we need a crisis like this one to be reminded of it. Experts may come up with all kinds of dire predictions about the future, but I would like to believe in the collective power of human motivation and creativity as a shining beacon to guide us through the crisis.

Though it is early days to define a coherent digital transformation strategy, there are certain possibilities that we have to consider while refining the digital transformation strategy

a. The rapid changes in the landscape is bound to affect and change the sentiments and motivation of people in the same rapid way. The digital tools we have at our disposal can provide us excellent insights into the changing sentiments of employees and address them in real-time. The need for this is greater than ever now.

b. The way we view work and processes have undergone a radical change in the last few months. I view this as a positive thing since it has put to sword some of the outmoded ideas and beliefs we held. Now that those beliefs have been shattered, this is the right time to start building on the new platform of beliefs. The time is ripe to re-design work. @Crompton, we have witnessed our fair share of it, and we have started re-designing work and focus on new skills, starting with customer-facing roles.

c. One thing is sure – the immediate future will be full of change and surprises, positive and negative. The time has arrived to design an extremely agile organization decision-making process to cope with this. And this has to be done really fast.

d. The analogous point would be re-looking at HR processes emanating from the change in work processes. How do you build and maintain social connection when you cannot have a water-cooler conversation? How do you monitor productivity and performance when the work itself is getting re-defined? How do you equip managers with the skills to manage the employees with these transitions? At this stage the answers are not clear – but what would matter at this stage is to ask the right questions.

e. Final watch-out – given the unprecedented (speed and scale) of disruption, the future forecast by Specialists may be marginally true. This has an implication for AI because it primarily analyses past trends and tries to forecast the future. Unfortunately, this approach may not work out in cataclysmic times like this.

Disclaimer: The views expressed in the article above are those of the authors’ and do not necessarily represent or reflect the views of this publishing house


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