CHICAGO and ATLANTA – May 18, 2017 – Artificial intelligence and automation will have a major impact on HR and employment over the next few years, according to new CareerBuilder research. More than 1 in 10 HR managers (13 percent) are already seeing evidence of artificial intelligence (AI) becoming a regular part of HR, and 55 percent say it will be in the next five years.
The national study was conducted online by Harris Poll on behalf of CareerBuilder from February 16 to March 9, 2017 and included a sample of 231 human resource managers across industries and company sizes in the private sector.
While the majority of HR managers said the thought of AI in HR does not make them nervous, a third (35 percent) said it does. Still, only 7 percent of HR managers say they think a robot could do their job.
“There are certain aspects of HR that are transactional in nature, such as how we capture candidate and employee information and maintain those records and reports. Automation is key in finding efficiencies in those processes,” said Rosemary Haefner, chief human resources officer for CareerBuilder. “What robots and AI can’t replace, however, is the human element of HR that shapes the company culture, provides an environment for employees built on IQ and EQ, works hand in hand with company leaders to meet business goals and ensures employees have the training and support to thrive. You need living, dynamic people who can navigate the ‘gray’ to do that, not robots that can quickly work through black and white.”
Manual Data Input Causes Wasted Time and Productivity, Errors
HR managers who do not fully automate say they lose an average of 14 hours a week manually completing tasks that could be automated; more than a quarter (28 percent) waste 20 hours or more, and 1 in 10 (11 percent) spend 30 hours or more.
“We always say, ‘I wish I had more time to plan, to think, to keep up on new trends, to strategize.’ To have 14 hours back in a week, the majority of that would be well spent planning for the future instead of reacting to the present,” Haefner said. “Time would also be spent connecting with the business, with employees. That may mean catchups with company leaders, educating yourself on the company’s products/services, learning the industry, and networking outside the walls of your office.”
Below is a breakdown of the HR functions that HR managers say are currently fully automated, partially automated or not automated at all.
HR Function
Fully Automated
Partially Automated
Not Automated
Payroll
50 percent
42 percent
7 percent
Background checks/drug testing
39 percent
35 percent
21 percent
Applicant tracking
38 percent
35 percent
21 percent
Benefits administration
34 percent
49 percent
13 percent
Distributing job postings to different websites
30 percent
36 percent
28 percent
Compliance
25 percent
45 percent
27 percent
Performance management
24 percent
38 percent
33 percent
Sourcing job candidates
20 percent
47 percent
25 percent
Predictive assessments
20 percent
24 percent
25 percent
Training/learning
18 percent
47 percent
28 percent
Employee referrals
16 percent
29 percent
45 percent
Onboarding
15 percent
56 percent
26 percent
The survey found that a lack of HR automation can have a negative ripple effect on a business. HR managers who do not fully automate say manual processes have led to:
- Lower productivity: 41 percent
- More errors: 40 percent
- Higher costs: 35 percent
- Poor candidate experience: 18 percent
- Poor employee experience: 17 percent
- Less engagement: 17 percent
- Poor hiring manager experience: 11 percent
Survey Methodology
This survey was conducted online within the U.S. by Harris Poll on behalf of CareerBuilder among 231 human resource managers (employed full-time, not self-employed, non-government) between February 16 and March 9, 2017. Percentages for some questions are based on a subset, based on their responses to certain questions. With a pure probability sample of 231, one could say with a 95 percent probability that the overall results have a sampling errors of +/- 6.45 percentage points, respectively. Sampling error for data from sub-samples is higher and varies.