Imagine for a second that there's a really important decision to be made based on heaps of data. Who do you trust will do a better job of dissecting that data and making a decision: humans or artificial intelligence (AI)?
In a heavily data-dependent department like human resources, AI is a no-brainer. Yet, organizations still shy away from "the unknown." The reason why HR is still wary of this relatively new approach is the reliance on the human emotional judgment that has driven the decision making process for decades. Some HR professionals still rely on that familiar gut feeling because they believe an algorithm, no matter how sophisticated, can never replace human intuition. The old management cliché that "people are the most important asset" is in full force here. HR leaders seldom relied on data to provide actionable insights.
This is a problem that requires deeper analysis. IBM research shows that while two-thirds of CEOs say AI will drive significant value in HR, only 11% of chief human resource officers report that their organizations have the necessary skills (AI, data science and machine learning) needed to fulfill that potential. An MIT Sloan Management Review and The Boston Consulting Group study (paywall) shows roughly the same numbers: 85% of business executives think AI will provide their companies with a competitive advantage, but only a handful (one in 20) indicated that they have extensively incorporated AI in processes and offerings.
The main challenge here is implementation, which encompasses a broader understanding of a technology that’s outgrown the limits of typical software installation. Unlike the majority of well-defined problems and outcomes artificial intelligence is typically trained on, business decisions have more complexity to them.
The fear of handling such a complex process, despite AI’s best efforts to mimic the operation of our brain’s neural networks, makes it difficult for businesses to implement AI company-wide, not just in HR. IBM's research shows that only a few organizations are ready to take advantage of AI's potential, despite acknowledging its disruptive capabilities. In fact, as many as 120 million workers in the world's 10 largest economies may need to be retrained or reskilled in the next three years as a direct result of AI and intelligent automation.
It’s not just the existing workforce that will need to readjust to market conditions; the current batch of grads also realizes there is a gap between their formalized education and the skills in demand. The 2019 LinkedIn Grads Guide to Getting Hired found that three out of the top five skills new graduates are investing in learning after graduation are data and AI-based skills. AI is a requisite for integrating applications and data for various use cases, and HR fits perfectly.
The key step for business and HR leaders is to thoroughly understand where AI can and can’t provide value and pave the way for a strategy that will yield long-lasting benefits.
This starts with an understanding of recent advances in deep-learning techniques and how AI learns through the use of training data. Because these systems are trained (as opposed to a prevalent concept of programming), the vision for AI’s use must fit the availability of organizational data, which will align with the organization’s goals and values. Data comes in various sizes and forms, so some in-depth data cleansing will be in order. The bottom line is that not every AI is right for every business.
In the high-tech era we live in, if a company falls behind, its users can swiftly impact the bottom line for the worst. Similar can be said about the dynamics of the workforce. HR has yet to fully engage in using data-based decision making about people, departments, culture and skills, which is strange considering it’s one of the most complex business processes. And when it comes to HR functions, AI has all the capabilities to be the No. 1 disruptor in a wide array of applications, most notably people analytics.
One obvious example is talent recruitment and retention. Detecting workers who best epitomize an organization’s culture is vital to success for both the company and employees. Through sentiment analysis and the ability to discern nuanced characteristics of an individual from both quantitative and qualitative data, AI can identify the right talent with minimal costs and in less time, as well as improve inter-organizational relationships by pairing specific workers’ roles and departments with specific personalities.
Yet, there are significant barriers that prevent such progression, from technical constraints to organizational challenges such as inner culture and arguably the biggest barrier manifesting through a lack of requisite skills. Historically speaking, HR is one of the least technically-minded departments, which, considering the massive amounts of data it collects, is counterintuitive with modern times. There is a lack of data literacy, where understanding the data (instead of just managing it) is key to unlocking AI’s potential.
For good or bad, AI is generating both fear and hope among the workforce. The former can damage the organization in many ways, most notably in terms of failing to acquire capable personnel handling AI-powered applications and embedding them in company products and processes. However, by adding it to the human element of HR, AI can supplement HR employees' daily role and retain its focus on what matters most: people. Hence, it’s clear HR has a vital role in transforming an organization for future work and training humans to work alongside artificial intelligence.
HR-driven investments in data analysis can be the leading factor in improved organization performance. By leveraging data obtained from people analytics, HR can become an enduring source of intelligent insights that can drive decision making and increase operational efficiencies on multiple levels.
I believe AI will augment HR as a more effective resource and allow more time and freedom for a hands-on approach, particularly regarding human-based tasks that make this department a crucial element within any organization. Things are bound to speed up once leaders recognize the value of AI in assisting the management of their workforce. Until then, there’s more work to do.
By Dr. Jeremy Nunn
Syndicated content featured from Frobes.
