Making the business case for AI in HR: two case studies
| Date | 08 April 2019 |
| DOI | https://doi.org/10.1108/SHR-12-2018-0101 |
| Pages | 66-70 |
| Published date | 08 April 2019 |
| Author | Boris Altemeyer |
| Subject Matter | HR & organizational behaviour,Employee behaviour |
Making the business case for AI in HR:
two case studies
Boris Altemeyer
Abstract
Purpose –This paper aimsto analyse two large-scale business case studiesfor the benefits of using AI,
computerscience and machine learning to assess, recruitand retain staff.
Design/methodology/approach –The authors interrogate two large-scale case studies, including
metricson the success of AI in relation to user experience,compatibility, psychometric benchmarking.
Findings –The authors conclude that AI removes bias from assessment, recruitment and training
processes and can save businesses significant time and resources as well as improve the cultural fit
and diversity of their recruits. There is a balance to be struck, though, as the systems used are only as
good as the science supporting the selection –and humans must ultimately retain the role of decision
makers.
Originality/value –These businesscase studies are examined in detail for the first time in thispaper.
Keywords Culture, Technology, Talent management, Recruitment, Analytics, Employer Brand
Paper type Case study
AI and robotics are already being used in HR. But it is no surprise that, in a sector
dedicated to the humanity in business, there is both confusion and apprehension
about this change. Some businesses are only just starting to tackle the fundamental
changes AI is ushering in, while others are further down the line –and theseare reaping the
benefits of the efficiencies AI can bringto HR, and to their bottom line.
The rollout of AI to HR departments is following a pattern. First, AI automates much of the
time-consuming grind of HR processes. Companies that are embracing the power of
machine learning are reaping tangible, clear-cut benefits. Automation speeds things up,
reduces resource expenditure and provides a far more accurate set of data. We can now
digitalise CVs, conduct and analyse video interviews for recruitment and track applicants
and employees through their career.
The next stage, and where it all starts to become moreinteresting, is in a more strategic shift
towards AI: companies that are making the best of machine learning are using it as a
collaborative tool, workingalongside human insight. This is a crucial distinction. AI’svalue in
HR is initially in its ability to crunch data and assess objectively –to do things faster, easier
and cheaper. But more fundamentally, it changes our value as employees: companies
leading the way in using AI in HR understand that innately human skills are going to be
more important, valuable and sought-after than ever before. The trick is in being able to
accurately and scientifically assess who has these skills and where they are. Companies
may already have these skills in abundance, but they may be in the wrong part of the
business. Or these mission-critical skills may be in such short supply that they need to
understand who is capable of being re-trainedwith them.
From the shop floor to the boardroom, employees will need to elevate their contribution to
areas where AI is not going to tangibly contribute: managing people; customer interfaces;
Boris Altemeyer is Chief
Scientific Officer at
Cognisess, Bath, UK.
PAGE 66 jSTRATEGIC HR REVIEW jVOL. 18 NO. 2 2019, pp. 66-70, ©Emerald Publishing Limited, ISSN 1475-4398 DOI 10.1108/SHR-12-2018-0101
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