AI has the capability to improve almost every sector and almost all business functions and operations. So why not HR?
As AI helps business stakeholders make crucial data & analysis-backed decisions and automate the workload to boost efficiency, analysts are wondering if the same principles can be applied to the HR department.
Why Human Resources Needs AI
In recent times, with the emergence of newer disruptive technologies, HR has witnessed a dramatic shift in their workloads.
While the focus used to be on recruitment, now, they need to give equal priority to reskilling activities as well. On the other hand, they are also faced with the headache of talent loss as companies get aggressive in their candidate poaching efforts due to the ever-widening talent demand gap.
These issues cannot be solved by human intervention alone. What complicated matters was the sheer amount of data generated by talent management activities that need to be made sense out of.
This is where AI steps in.
The Impact of AI on HR
Where there is data and a need for extracting insights, AI can be relied upon. And this seems to be the emerging pattern in HR departments globally as they place orders for cutting-edge HR-tech.
AI is helping HR departments solve problems that they were not even aware of.
Consider Textio. Textio is a language-based AI application that helps companies create better, more effective job listings. Before Textio explicitly pointed out the issues with a job description, companies were completely oblivious to the bias and unintended discrimination that seeped into their job descriptions. Combine this with the capabilities of Draup, using which you can recognize the skills, tools, and certifications required across 2,500+ job roles, and your job description is set up for success.
Here are some more areas that AI can help HR in.
Identify talent hotspots
In a given geography, everyone knows which locations are the talent hotspots. These usually have a large concentration of universities and are often tier1/tier2 cities.
But with the talent from these cities raising their expectations and proving increasingly difficult to match expectations and cost-wise, enterprises need to identify more talent hotspots.
These hotspots, while being cheaper to hire from, also contain a very diverse background of candidates.
AI-enabled talent intelligence platforms like Draup are plugged into over 4000 talent data sources and is able to evaluate global talent locations and unearth emerging hubs for over 2500 job roles.
Map job roles evolution
With disruptive tech becoming the norm of the day, job roles are continuously changing in both responsibilities and scope.
A call center tech is no longer a viable position in most companies. Contrast this with the modern demand for Inside Sales reps. HR has a decision to make. Fire the Call Center Agent and hire an Inside Sales rep or reskill the agent to become a rep.
Data and even common sense dictate that reskilling is the viable strategy here.
However, reskilling is not a task should be carried out with pen and paper.
Multiple parameters such as time to reskill, cost of reskilling, sustainability index, course/certification availability and others need to be assessed.
This is where a robust AI-powered reskilling platform can help. Draup will provide you with the ideal target role for a given current role along with how long it will take you to get there, the optimal path to get there and how you can get there.
Several Fortune 500 enterprises have used Draup’s reskilling framework to mitigate the impact of talent loss successfully.
Draup for talent enables HR departments to leverage the full power of AI and build the next-gen, sustainable workforce capable of meeting tomorrow’s demands.