Nowadays, job-hopping and fine tuning your career path has become the norm rather than the exception. Choice is abundant and the competition is ruthless. You can’t afford getting bogged down with human capital hurdles or someone else will attract all the good talent. So it’s understandable that people with an HR or Talent Management role are sleep-deprived, due to the following pressing questions:
- “How do I identify talent? How do I attract the right talent?”
#1 - How will AI tackle hiring
- “How do I keep talent engaged? How do I take the right actions?”
#2 - How will AI influence Retention & Decision making
- “How do I convince my boss that HR are not just a money draining necessity? What is the ROI of what we do?”
#3 - How will AI provide Convincing Data
- “How can I best affect the speed of adaptations, restructures, and globalization within my organization?”
#4 - And what about my Culture & Strategy
Hiring: S.A.R.A has got your back
Retention & Decision Making: AI will be your best advisor
Convincing Data: AI exceeds normal analytics
Culture & Strategy: That’ll be all YOU!
For the sake of analogy, let’s assume you’d like to buy a slightly kitsch shower curtain on Amazon. As you browse through countless pages of shower curtains, a machine learning algorithm follows you around in the background, teaching itself what you search for, like, and purchase. Next time you shop at Amazon, your interface will be plastered with smart suggestions, in tune with your… uhh… “acquired” taste. Amazon’s machine learning is merely one type of Artificial Intelligence.
In order to imagine how AI can impact HR’s hiring process, let’s replace the Amazon website by an advanced HR platform. The platform is powered by a fictional AI, which we will baptize S.A.R.A. (Secure Artificial Recruiting Assistant). S.A.R.A. is going to help us out.
Things are going well at your company, and you're looking to expand. You want someone with a particular set of skills, strengths, ambitions, etc. Meanwhile, there’s Jane, who’s working at another company. She has strong leadership skills, and S.A.R.A. has learned that Jane has a (fictional) empathy score of at least 78. Unknowingly to Jane, S.A.R.A. has noticed that her engagement has gone down the past three months. A more trustworthy environment would do wonders for Jane's motivation, is the conclusion.
Jane’s employer has access to the same data, yet decides not (or is incapable) to help Jane grow within her position. That enables the open market system to kick in, informing both Jane and you of the 94% match Jane has with your open position. After you’ve both met and confirmed that there is indeed a good match, all the tedious administration gets handled by S.A.R.A. Even part of the onboarding and training is likely to be performed by S.A.R.A., where information will "drip" to Jane over a period of days or weeks, at Jane’s desired pace, until she’s fully ready to rumble!
Welcome Jane, and thank you S.A.R.A.
Let’s go back to Jane before she joined your company. Jane was doing a more than decent job, yet got genuinely frustrated because her colleague got promoted instead of her. Unfair in her eyes, as the only thing her colleague was better at than her is “kissing ass.” This could’ve been labeled as “just Jane’s opinion”, but all available data was on her side. So equality was definitely being compromised. Jane experienced first hand that poor management and biased decisions can instantly demotivate, even to the extent she wanted to quit her job on the spot at times.
Why didn’t her manager intervene? Either he or she wasn’t aware of the situation, or just ignored it. Either way, isn’t it a manager’s job to monitor team performance, detect issues and take actions when they’re needed? Or at least communicate the what, how, and why of the situation at hand? Now, throw in some bias and favoritism with those doubtful leadership skills, and we have ourselves a failing manager (1 in 2 according to research).
Even today, AI can already outperform the skillset of a human manager when it comes to analytics and data processing. However, it is unlikely that AI will outperform human managers on soft skills such as comprehending people’s feelings, evoking motivation and the coaching of new and experienced employees.
It’s in this understanding that AI will never be the solution, but will definitely be the perfect assistant in dealing with people management. Flagging potential issues that might come up, warning us of engagement levels that are going down, actions that can be taken… A failing manager will not become a good one just by implementing an AI solution, but it will help decent managers to do even better and become excellent coaches in a relatively short amount of time. And that’s beneficial for everyone involved.
Tim Clauwaert, CEO of INTUO
Tim Clauwaert, CEO of INTUO, believes machine learning and AI will have a great impact on HR’s future role within its company. He argues that “people-centric machine learning will enable us to distribute time and effort to the areas where they matter the most, i.e. providing feedback to employees, understand what drives them, and coach where necessary. All of which will immediately benefit the long-term future of the company and the individuals, giving Talent-Focused roles a hyper-valuable and important seat at the strategic table.”
The Japan Post Insurance have recently implemented AI in their payout calculations, demonstrating that HR departments around the world are already betting on AI to optimize decision making and avoid employee disengagement.
The biggest component in most companies is arguably human capital. And yet this is the component you often understand the least. Yes, while data analytics can already help you to visualize employee performance and some behavior, AI is capable of taking it a couple of steps further. Where analytics still require a user to interpret and think over data, AI can take over a chunk of that process and help you to understand and anticipate situations much faster. Preventing issues faster may lead to avoiding layoffs, detecting skill gaps can lead to faster and better hiring, and suggesting actions to improve engagement may drive up motivation. It’s decision making like this that either saves money or makes sure it’s invested in the right areas, in the most optimal timeframe.
Arne Van Damme argues that from within HR there is a huge need for AI, “because HR is moving from being a necessary cost center to delivering the most important added value. The pressure on HR is increasing. They have to argue and campaign so much for the spending they do in human capital more and more. That’s why they will need all the HR intel they can possibly get their hands on. And the more thorough and accurate the data, the easier the justification.”
On average baby boomers look for a job 11.7 times during their career. Millenials crush that record by changing jobs every two years or less. Knowing that by 2020 the majority of the workplace will consist out of millennials, something’s got to give. And in this case, simply crunching the numbers and implementing artificial intelligence won’t suffice.
Hierarchy and bonuses serve a short-term purpose and, depending on your industry, can work as motivation. But do consider the fact that more and more young people are not driven by money and short-term benefits. Even more so, one third of young professionals don’t believe it should be a business’ sole purpose "to make money". You see the tendency here? Working for a purpose and finding a company that shares your individual goals to some extent are the main drivers for young people for finding a job nowadays. “WHY does your company do what it does, and what kind of impact does your company (aim to) have?” are the most important questions your company culture needs to answer.
Choice, flexibility and independence are three key characteristics of the future workplace. Consequently, flattening the hierarchy and making jobs more dynamic will be crucial, giving employees the required autonomy and ownership.
Outdated company structures are bound to change. Not just to adapt to the features of future generations but also to respond to the rapidly changing market dynamics. Conversation, empathy, a clear purpose and a sound engagement method will be the driving force of your strategy adoption and culture. And make no mistake, those are all areas in which you, the human, will have to make decisions. AI will merely have an enabling role.
Now if you’ll excuse me, S.A.R.A. just pinged me with another interesting profile.
First published on Jorn's Medium account.