AI in HR is increasingly becoming an integral part of the workplace and, despite the risks, the upsides are enormous, writes Josh Bersin
When it comes to AI and HR, we are in an interesting place. On one hand, the AI hype is far ahead of the reality; on the other, the upside of AI is likely much greater than we can imagine.
In this column, I’ll point out ways AI-related tools are now being used (or will be soon) in various areas of our profession, along with solution providers who are making early inroads in putting AI to work.
First, a little background. We first must recognise that AI is not some magical computerised technology. When we talk about AI in HR, we’re primarily talking about machine learning, in which a system “learns” actions based on “teaching sets” of data. Such systems rapidly ingest data, identify patterns, and optimise and predict trends based on a wide range of algorithms. Machine learning tools are not intuitive like human beings but they are fast, so they can analyse millions of pieces of information in seconds and quickly correlate them against patterns.
Imagine an AI system that could review 500 job applications and, by examining various demographic criteria, job histories, and interview answers, could then predict how each candidate would perform on the job. Such systems are in the works right now.
“We will see dramatic improvements in productivity, performance, and employee wellbeing. We just have to be patient, vigilant, and willing to invest”
6 ways AI could impact HR
Recruiting: Managers and HR professionals spend billions of dollars of assessment, tests, simulations, and games to hire people and yet still complain they 30-40 per cent of their hires wrong. Algorithms can weed through resumes, find internal candidates, profile high performers, and even decode video interviews and game-based assessment results to point to those likely to succeed. Such systems also eliminate interview and educational biases often prevalent in hiring processes. One day they may even be able to assess emotional and psychological traits such as ambition, learning agility, passion, and sense of purpose.
Employee development and learning: Although companies spend more than $200 billion annually on training, much of employee learning is forgotten, inappropriately applied, or not relevant to true needs. Now entering the market are Netflix-like learning solutions that can assess learner interests and job needs (as well as those of high performers in the job category) and then make recommendations on learning resources – making learning as useful and fun as chilling on Netflix (well, almost!).
Management and leadership. Managers read books, go to workshops, and emulate the bosses we admire. But do we really know the science of leadership? AI can now help decode this. I know of three vendors building AI-based coaching tools that request feedback, read comments, and intuit sentiment from employees and teams. Using data gathered from high-performing teams, the tools “nudge” managers and supervisors with suggestions for doing better.
Fraud and compliance. The opportunities in this area are massive. AI can analyse organisational network data such as email traffic and comment sentiment to identify areas of stress, potential ethics breaches, and other types of compliance risk so that HR or compliance officers can intervene before bad behavior actually occurs.
Wellbeing and employee engagement. AI is now being used to identify behaviors that cause poor work performance. For instance, AI can identify behaviors and experiences that lead to accidents and alert HR to patterns of stress or bad behaviors.
Employee self-service and candidate management. Here, a new breed of intelligent chatbots can make employee interactions intelligent and easy.
Certainly, there are challenges and risks with AI, such as misuse of data, security breaches, institutionalising hiring and assessment biases, and faulty algorithms that deliver unwanted results. Despite these challenges and risks, the upside is enormous. As AI systems in HR get smarter, more proven, and more focused on specific problems, I believe we will see dramatic improvements in productivity, performance, and employee wellbeing. We just have to be patient, vigilant, and willing to invest.
Recruiting: LinkedIn, Pymetrics, Entelo, HiredScore, IBM, Textio, Talview, Unitive, PredictiveHire
Employee development and learning: Degreed, EdCast, Filtered, Volley, Axonify, BetterUp, Clustree, Workday
Management and leadership: Reflektiv, BetterWorks, Ultimate Software, Zugata, Humanyze, ADP, Impraise
Fraud and compliance: TrustSphere, Keencorp, Volley, Cornerstone
Wellbeing and employee engagement: Limeaid, VirginPulse, Glint, Ultimate Software, CultureAmp, TinyPulse, Peakon
Employee self-service and candidate management: IBM, ServiceNow, Xor, Mya, Ideal, Paradox
Performance management: ADP, Zugata