Who put the non-human into human resources? At first glance, it seems like an unpopular alliance—the use of artificial intelligence to support a company’s strategic goals vis a vis human resources.

IBM, however, is the company going big and bold in championing the benefits of technology driving work efforts to retain the best, the brightest, the aptest to contribute something to the conference table.

IBM receives more than 8,000 resumes a day, making it No. 1 on job-search site Glassdoor for Gen Z applicants.

But that’s not the only way the technology giant, which employs roughly 350,000 workers, knows who in the workforce is currently searching for a new position.

Its artificial intelligence technology is now 95 percent accurate in predicting workers who are planning to leave their jobs.

Its HR has a patent for its “predictive attrition program” which was developed with Watson to predict employee flight risk and prescribe actions for managers to engage employees.

IBM CEO Rometty would not explain “the secret sauce” that allowed the AI to work so effectively in identifying workers about to jump.

Officially, IBM said the predictions are now in the 95 percent accuracy “range”.

The AI retention tool is part of a suite of IBM products that are designed to upend the traditional approach to human resources management.

Rometty described the classic human resources model as needing an overhaul and said it is one of the professions where humans need AI to improve the work.

She said that since IBM implemented technology more widely including cloud services and other modernization, the tech giant has reduced the size of its global human resources department by 30 percent.

Need for a clearer career path

Among the tasks that HR departments and corporate managers have not always proved effective at, and where Artificial Intelligence will play a bigger role in the future, is keeping employees on a clear career path and identifying their skills.

Being transparent with individual employees about their career path is an issue in which many companies still fail. It is going to become more critical.

Being transparent with employees means being honest about the skills that are needed, especially when the workers don’t possess them. IBM managers talk to employees about market skills that are scarce or abundant.

How does it work?

By better understanding data patterns and adjacent skills, IBM AI can zero in on an individual’s strengths. In turn, this can enable a manager to direct an employee to future opportunities they may not have seen using traditional methods.

Predictive Attrition Program
Predictive Attrition Program

IBM technology can view the tasks employees are completing, the educational courses they have taken and any rankings they have earned.

Through these data points, the AI skills inference and HR managers can gain a greater understanding of an employee’s skill set than they would be assessing the feedback from manager surveys.

AI is getting better at providing career feedback to employees. IBM’s MYCA (My Career Advisor) AI virtual assistant uses Watson to help employees identify where they need to increase their skills.

Its companion, Blue Match technology, serves up job openings to employees based on their AI-inferred skills data.

Rometty said some of the 27 percent of IBM workers who received a new job or promotion in 2018 were assisted by Blue Match.

Getting rid of the current HR system

Traditional human resource departments, where Rometty said companies typically “underinvest,” have been divided between a self-service system.

Employees are forced to be their own career managers, and a defensive system to deal with poor performers.

IBM employees no longer need to decipher which programs will help them upskill; its AI suggests to each employee what they should be learning in order to get ahead in their career.

IBM bets in the future of work where a machine will understand the individual better than the HR individual can alone.

But the new era of AI-centered human resources will improve upon something many human-led HR teams can’t handle as effectively as a machine that can crunch millions of data points and learn in new ways.

Recognizing the true resource potential of individuals and serving as growth engines for companies.

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