ChatGPT & HR
Will it shrink or expand the HR department
ChatGPT launched in Nov’22, providing a real introduction to AI/ML to common folks. It is far from perfect and soon to be launched products from Google, Meta and others may be more advanced.
There is a lot of debate on whether ChatGPT would disrupt Google. It is a futile debate because search is ever evolving. Moreover Google has its own version of chatGPT but as discovery migrates to AI platforms some of the monetization models for these giants will need to change.
In an ideal case AI should relieve HR of its repetitive, time-consuming tasks, so the HR staff and managers, can focus on more complex assignments.
Many organizations in US have turned to AI (via virtual assistants and chatbots) to respond automatically to questions asked by employees – "Where is my training application?" or "How many days off am I entitled to?" – in real time and regardless of where staff are based. AI refers questioners to the correct documentation or the right expert. AI is also being used for filtering job candidates when the volume of applications is high, identifying training needs and even predicting employee attrition.
However there are limitations to what AI can do. Data is the key ingredient for AI, and its quality is very important. If the data injected isn’t good, the results will be vague or distorted. Many companies that tried to use AI for their recruitment engines found that AI reinforced the hiring mistakes of the past because the data from past applications was skewed.
In addition, AI works best with a very diverse set of data. HR data by its very nature is very narrow as the number of people employed by an org is far lower than number of purchases made by customers. The quantity of sales observations for an item is very important for big data applications to be easily performed. But that is missing in HR!
Besides the quantity and quality of data , AI also needs the data to be embedded in a context and time series for analysis and decision-making. For eg, in the field of predictive maintenance of airplanes, expert systems can detect signs of wear in a part before human beings: by collecting the appropriate data, just-in-time interventions can be made to overhaul the machinery. It’s a different matter for human systems, however, where the actions and reactions of individuals are not tracked (and should they be?), and may turn out to be totally unpredictable.
However the most important issue is around privacy, returns on investment for insourcing AI and the danger of AI becoming a gimmick. Most public platforms like Chatgpt are useless in HR because no organization will share the data publicly. Trying to apply AI by developing AI tools in-house or through a vendor will again go through ROI discussions. This will again give a distinct advantage to large tech firms & big businesses in general as they further improve their Employee Value prop with AI.
So rise of public AI platforms will actually increase the pressure on HR as employees get exposed to AI as consumers. They will expect same type of experiences from their HR as they get from businesses as customers including hyper customization, instant response and fulfilment. However HR in most organizations will not have the tools to serve these expectations because of the reasons outlined above.
So what are the options? Well! organizations will have to get used to open employee networks through APIs by working with trusted partners who specialize in HR. These players through employee permissioned systems aggregate and analyze the data and create insights that will promote the overall wellness and experience of the employees.
Next 2-3 years will transform the HR function and we will share more insights as we move along.