Artificial intelligence (AI) has been in the media limelight in recent months, and rightfully so—the AI market will be worth nearly $60 billion by 2025, a figure that doesn’t even account for markets related to AI, like machine learning as a service and deep learning. The data proves that AI is more than just hype, and most businesses are already leveraging AI or automation in some way. In the HR industry, we’re seeing massive growth of AI usage across recruiting, hiring, onboarding, and other human capital management functions.

Myth: Artificial Intelligence (AI) will replace the need for human employees

With the growing hype around AI, comes considerable concern among workers fearing for their jobs, and rightfully so. For every headline referencing the growth of the AI industry, there’s another that offers perspective on how and why AI is a threat to human jobs. One PwC study found that 38% of jobs in the U.S. could be “vulnerable” to AI by the early 2030s. This study, along with countless sources referencing AI’s threat to human jobs, may be missing a critical element – the need for human emotional intelligence and data analysis. If we take a closer look at the specific ways AI is improving the workplace for HR professionals, it’s clear that the human factor will not become obsolete, although roles of employees may change.

Human intervention is critical to the future of AI—and AI is critical to ensuring HR leaders can continue to move from performing a strictly administrative function in an organization to becoming a strategic partner and contributor. We’ve debunked the idea that AI is posing a major threat to jobs—so how can HR leaders make the most out of this growing technology segment? As we continue to apply machine learning and automation to HR processes, we must take a holistic look at the employee lifecycle, from recruiting and onboarding to off-boarding and outplacement, and everything in between.

#1: Recruitment and onboarding

There are a great number of technology vendors committed to bringing AI and automation to the recruiting and onboarding processes. Recently, RiseSmart’s Sanjay Sathe wrote about how AI is radically streamlining the onboarding process in VentureBeat. He described how the types of jobs employees obtain will look much different as AI continues to develop and grow exponentially. He’s not wrong and his point of view supports the idea that AI will not replace jobs as much as redefine them.

Even the task of recruiting and onboarding the new breed of employee will be affected by AI, but will not completely replace the need for humans to interview and meet potential employees to determine things like culture fit and personality. Today, AI applications make the recruiting process more efficient by delivering some information that will help HR leaders make initial candidate decisions by collecting data from work samples, social media posts, and resume “word choice”. From candidate-matching before an interview to candidate scoring based on social interactions, recruiting and onboarding processes have greatly benefited from automated processes and machine learning. Vendors have tapped into the great wealth of candidate data that already exists before the employee is even hired, and are applying machine learning to ensure only those candidates with the matching skills, and apparent values, make it into personal interviews where emotional intelligence and human interactions determine the final outcome.

#2: Performance appraisals

Most HR practitioners agree that the traditional performance appraisal model, with a stand-alone end-of-year performance review, is outdated. When AI is applied to the performance management process, new insights may emerge. Yet the HR person would remain critical to the success of continuous performance management, and talent management processes.

For example, data might show that an employee is hitting her goals and targets, yet her peers receive more promotions or quicker advancements. Simply obtaining accurate data about employee progress brings more subjectivity to the process. But it would still be the manager and HR leader’s job to surface this information and advocate to promote the individual employees who deserve it.

#3: Performance development

Surprisingly, many companies don’t know the talent profiles of the individuals within their organization. When paired with employee data, AI can enable HR leaders to keep tabs on the company’s talent pool and can help to provide professional development opportunities that match the growth and transformation of the business.

Let’s use the oil and gas industry as an example. The industry is currently undergoing a massive transformation. If its employees don’t grow and change alongside the company, it will be difficult to achieve long-term success. There are plenty of situations when the macroeconomic picture or strategic direction of a company might change. AI will be one way to know if your talent pool is ready to tackle these changes.

AI can ensure HR leaders spot gaps and misalignment between business and employee growth and transformation. When we apply automation to people data, the gaps emerge. HR leaders will be able to leverage this information to make strategic decisions, such as whether or not to retrain select employees, or what areas recruitment to focus on.

On the other hand, when a business isn’t developing but its people are, feelings of frustration will quickly surface. People begin to outgrow their environment and itch for a new opportunity. Automatically surfacing these gaps can empower the HR manager to pool additional resources to ensure there are no feelings of misalignment, or gaps in talent. 

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#4: Layoffs and outplacement

While AI technology can identify who should be laid off by simply weighing input metrics, the final candidate decision will come down to cultural fit, soft skills, and other criteria unique to each organization. HR managers will agree that it’s usually feasible to strengthen a skillset, but changing an employee’s personality is not a viable option.

In the human management continuum, an automated system might suggest retaining an employee because he is meeting his goals, but the manager may know he is an internal distraction that only meets his goals while disrupting the work of other team members. Meanwhile, another employee might be scraping by, according to the data, but bring other valuable assets to the team, like leadership, teamwork, and collaboration. It’s vital that HR practitioners learn to combine the data collected by AI applications with human observations and anecdotes to get the complete, 360-degree picture in order to make highly educated and informed decisions.

Learning to use the technology and the resulting data will continue to be a challenge for HR leaders and departments as well as other employees within an organization as more and more data and automation is available for a variety of roles. But artificial intelligence will never completely replace the human element necessary to make the kinds of decisions robots and machines will never be able to make. Gathering data on employees, such as RiseSmart does after a layoff, can give companies and HR leaders great insights into things like alumni sentiment, but making the changes to notification practices or providing resiliency training for the remaining employees takes a human touch that can never be replaced by machines.

Human intelligence and intervention are important components of any AI strategy. As the industry continues to evolve, and HR vendors emerge to apply automation to all parts of the employee lifecycle, remember to take a step back and look at your workforce holistically. Data inputs are vital, and offer a subjective view—but the human eye is still needed, and I don’t see that changing any time soon.