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When AI meets HR, here’s what happens

by Max Smolaks
Article Image

by Laura Timms, MHR Analytics

10 January 2020

According to a recent survey, 82% of HR leaders believe their roles will be completely different in a decade’s time. Big things are happening, with Artificial Intelligence (AI) taking a starring role. 

At MHR Analytics, our research points to a similar conclusion. More than a third of the 500 companies we recently polled said they had adopted some form of AI in the past year, and almost half of the HR leaders we surveyed said that machine learning – a form of AI – will improve their HR function.

AI
is already being put to work in key areas such as recruitment, onboarding and
employee development. For talent teams, these technologies are helping to free
up resources, make better decisions, and crucially, deliver the type of
experience that encourages top talent to stick around.

Less
time bogged down in processes and more time
for people: This is perhaps AI’s most exciting promise –
and one that forward-thinking people managers are already taking advantage of.
So here’s a closer look at how HR is being transformed, along with a glimpse at
what the future holds…

1. Talent spotting

With multiple positions to fill and a mountain of CVs to wade through,
the traditional paper sift can turn into a major HR chore. Fortunately,
however, help is already at hand in the form of Natural Language Processing
(NLP).

With this category of AI, computers can go way beyond a basic
keywords-based trawl of the text. Through NLP, machines have the ability to
actually analyse context and understand meaning.

AI-driven recruiting tools such as Pomato provide
a useful illustration of what’s possible. Upload the CVs, define your desired
employee attributes and ask the machine to ‘read’ the documents to show you the
most promising candidates. As well as saving time, this also avoids inevitable
personal biases. By focusing only on the attributes that matter, AI-driven
technology can help to introduce a welcome element of
objectivity.         

2. Interviews

On-demand video interviewing isn’t exactly new.
Candidates tend to be impressed by it, while hiring teams appreciate its ability
to eliminate scheduling headaches. Now though, AI-driven video assessments are
becoming an even more powerful part of the HR toolkit.

Choice of word, intonation, body language and
more: just a 15-minute interview can generate 20,000 data points, which can be
aggregated and used to assess and compare candidates, based on criteria proven
to be predictive of job performance. This is according to the creators of HireVue, one of the new
breed of video assessment tools. 

Faced with multiple seemingly suitable
candidates for recruitment or promotion, it’s easy to drift into ‘hiring on a
hunch’. By contrast, AI-driven technology gives a concrete framework to base
your decisions on. If data-driven HR decision making is the end-goal, AI is one
of the most effective ways of reaching it.  

3. Training and development

Show the new starter to their desk and tell
them to plough through the workplace manual: it’s a sure-fire way to sap the
enthusiasm of any promising recruit! 

Given that an estimated 20% of turnover happens in the first 45 days of employment, it’s not surprising that forward-thinking HR teams are looking carefully at making their onboarding efforts more user-friendly. The right technology can have a big role to play in minimizing staff attrition. Increasingly, this involves the deployment of AI. 

Helping employees to help themselves: that’s the thinking behind providing an online training portal for your employees. With this type of solution, staff can get to grips with organizational rules and processes in bite-size chunks, participate in interactive tutorials and develop new skills, all from a single hub. AI-driven search and chatbot features can enhance your employee portal even further, allowing staff to ask any work-related question and instantly get an answer they can trust. 

A greater self-service element in onboarding can mean your team spends less time on fielding routine organizational and technical queries. It frees up time to focus more on employee well-being as opposed to admin. 

4. Employee satisfaction

As a rule, how well an organization is doing depends on how well its people are doing. At its best, HR should be less about enforcement and more about building the type of environment in which employees can thrive. 

So what kind of employee experience are we
actually delivering? What do our people really think?
Too often, the HR department only becomes aware of a particular problem once it
has reached a tipping point; where relationships have broken down and
employees already have a foot out of the door. 

In answer to this, sentiment analysis allows HR
teams to interpret potentially vast quantities of comments to uncover attitudes
and concerns. At its most basic, an analytics tool can help you pick out the
key areas of concern from staff surveys.

What’s more, combinations of AI-based NLP and machine learning allow analysis not just of surveys but also of open-ended comments and communications across an organization (e.g. exchanges across Slack and email). As the tech evolves, it is also becoming increasingly effective at distinguishing between different types of emotion; even so far as being able to tell the difference between, say, confusion and worry. 

For your HR team, this type of AI-driven tech
can provide a valuable early warning system. Picking up on rumblings of
discontent on a particular issue gives you the chance to respond proactively to
it before it becomes a major problem. 

What’s next for your HR
team? 

First off, AI is not an all-or-nothing game. So for instance, just because it’s technically possible to place the task of candidate assessment exclusively in the hands of a piece of software, it doesn’t mean that it’s necessarily the best course of action for your organization. 

A far more realistic approach to it will likely
involve identifying your particular bottlenecks and considering what tools will
enable you to address them. For instance, while you may be more than happy to
rely on an analytical tool with NLP capabilities to help you narrow down a
talent pool, you might still want to keep end-stage assessments firmly in the
hands of humans.

Secondly, as outlined in MHR Analytics Ultimate Guide to AI, HR is by no means the only department where AI-based transformation is happening. In areas such as project management, sales and finance, advanced modeling capabilities can give managers a much better ability to predict their future resource needs, including their staffing requirements. It’s always worth making sure these insights are being fed through to HR as soon as they are made available. After all, insight is only of value if you act on it – and it’s here that your role is always vital!


Laura Timms is product strategy manager at MHR Analytics and a ‘data maturity’ advocate, supporting organizations to advance their data journey.

MHR Analytics is a specialist provider of business intelligence, analytics and financial performance management. The MHR Analytics team enables businesses to capitalize on the data available to them, to identify opportunities and prepare for the future – whatever stage of the data journey they are on.

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