This document discusses how artificial intelligence is revolutionizing talent acquisition practices. It begins by outlining the future context of work and talent acquisition, with the rise of automation and skills gaps. It then discusses 10 specific ways AI is changing recruitment, including more effective candidate sourcing, personalized outreach, improved candidate experience through chatbots, and more efficient screening and scheduling. The document argues AI can help recruiters focus on building relationships rather than administrative tasks.

1. HOW ARTIFICIAL INTELLIGENCE (AI) IS
REVOLUTIONIZING TALENT ACQUISITION
PRACTICES
CHARLES COTTER PhD, MBA, B.A (Hons), B.A
www.slideshare.net/CharlesCotter
SIERRA HOTEL, RANDBURG
16 AUGUST 2018

2. PRESENTATION
OVERVIEW
• The current context and the
future of talent acquisition –
the rise of the robots and
the dawn of smarter
(cognitive) recruitment
• The business case for AI in
talent acquisition
• 10 Ways in which AI is
revolutionizing talent
acquisition practices

3. FUTURE OF WORK
“There are really three
themes that’ll shape the
future of talent,
Artificial Intelligence
and automation, the
skills gap and the rise of
independent work.”
(Jeff Weiner, CEO
LinkedIn)

6. THE FUTURE OF HRM
• Strategic goal: To transform to be a HR Business Partner (role)
• Strategic objective: To create a HIPO (High performing
organization)
• Transform from recruitment to Talent Acquisition:
❑Acquire talent faster
❑Acquire better quality talent
❑Acquire talent more intelligently (smarter)
• Q1: So how strategic is HRM?
• Q2. Is AI the solution – the driver/accelerator of change?

7. RESEARCH: DIAGNOSIS OF STRATEGIC HRM
(COTTER, 2018)

8. SABPP HR AUDITED RATINGS
(X39 COMPANIES)

9. HOW HAS RECRUITMENT CHANGED?
(COTTER, 2017)
• Savvy, future-focused recruiters have transitioned from
face-to-face recruitment to facilitating the interface
between people and technology, which is at the coalface
of business strategy.
• The employment landscape has changed from “talent
wars” – battlefield to a “talent economics” – trading floor.
• Smart recruiters have to transform to “behavioural
economists.”
• Next level (future-fit) recruitment in the Gig Economy?

10. DELOITTE’S HCM TRENDS 2017 –
THE RISE OF THE COGNITIVE
RECRUITER
• Leveraging new technologies—from social to
cognitive
• Evolution toward cognitive capabilities that build
on mobile and cloud technologies, as well as
social networks e.g. LinkedIn.
• The more innovative ideas and solutions are
centered around cognitive technologies such as
artificial intelligence (AI), machine-to-machine
learning, robotic process automation, natural
language processing, predictive algorithms and
self-learning.
• Chatbots are becoming popular, including the
recently launched Olivia, which guides candidates
through an application process with sequenced
questions.

11. DELOITTE’S HCM TRENDS 2017
– THE RISE OF THE COGNITIVE
RECRUITER
• IBM’s AI pioneer, Watson, is now moving into the
space with three new technologies:
❑ A machine learning platform that ranks the
priority of open requisitions;
❑ Social listening for an organization’s and
competitors’ publicly available reviews on
Glassdoor, Twitter, and newsfeeds and
❑ A tool that matches candidates to jobs through a
“fit score” based on career experiences and
skills.
• These technologies take pre-existing social data and
information and then apply advanced cognitive
capabilities to deliver actionable analysis.

13. THE BUSINESS CASE FOR AI IN TALENT
ACQUISITION
• A.I. is empowering recruiters today to become smarter and more
efficient by reinventing the hiring process.
• #1: Machines as matchmakers
• #2: Using AI to reduce unconscious bias
• #3: Liberating employers to focus on the human side of hiring
• #4: Improved Candidate Experience
• #5: Faster Time to hire - AI streamlines the recruiting process by
automating high-volume and often time-consuming tasks

14. THE BUSINESS CASE FOR AI IN TALENT
ACQUISITION
• #6: Superior engagement with passive candidates
• #7: Balancing recruitment risk
• #8: Improved quality of hire
• #9: Real-time skill-set testing and evaluation
• #10: Measure the impact of new hires over time

15. STRATEGICALLY CAPITALIZING ON AI –
APPLING THE 3 A’s (MEISTER, 2018)

16. AGREE OR DISAGREE?
WHY?

18. 10 WAYS IN WHICH AI IS REVOLUTIONIZING
TALENT ACQUISITION PRACTICES
• #1: SOURCING OF CANDIDATES
• #2: PROGRAMMATIC JOB ADVERTISING
• #3: CANDIDATE OUTREACH
• #4: CANDIDATE EXPERIENCE AND RELATIONSHIP
BUILDING (JOB SHOPPERS)
• #5: AI-POWERED ASSISTANTS (CHATBOTS) AND
MACHINE LEARNING ASSISTING APPLICATION

19. 10 WAYS IN WHICH AI IS REVOLUTIONIZING
TALENT ACQUISITION PRACTICES
• #6: PROMOTING EFFICIENCY
• #7: CV SCREENING
• #8: DEEPER AND RICHER CANDIDATE INSIGHTS
• #9: ELIMINATING UNCONSCIOUS HUMAN BIAS BY
MEANS OF PREDICTIVE ANALYTICS
• #10: ADVANCED COMPETENCY TESTING

20. #1: SOURCING OF CANDIDATES
• Arya, a sourcing app that uses machine learning (ML) to identify
the patterns of successful employees and draws potential
candidates out of the millions of online profiles by applying this
algorithm to a company’s existing résumé database and beyond.
• Arya adapts and learns based on the performance of new hires by
analyzing data like performance reviews, turnover rates and the
timing and frequency of promotions.
• It could significantly reduce the time it takes to identify top
candidates.
• By automating the candidate sourcing process, AI can double
recruiters’ efforts by scouring the internet for promising
candidates while the recruiter focuses on other tasks.

21. #1: SOURCING OF CANDIDATES
• AI in the form of machine learning sources qualified candidates online or
within resume databases such as CareerBuilder for recruiters to follow up
with.
• ClearFit saves recruiters sourcing time by automatically finding and ranking
candidates.
• Predictive analytics is increasingly important to TA, as sophisticated
analytics teams begin to prioritize recruiting workflows, conduct
workforce planning, evaluate different recruiting sources, assess quality of
hire and use pre-hire assessments e.g. PredictiveHire, a cloud-based SaaS
analytics solution provider.
• The applicant tracking system (ATS) is being reinvented by innovative
solution providers who are augmenting the ATS with other TA technologies,
including candidate relationship management, video interviewing and
analytics.

22. #1: SOURCING OF
CANDIDATES
• HC Trend: Optimizing sourcing
channels (Deloitte, 2017)
• Gamification - Forward-looking
organizations are also beginning to
employ simulations and gaming to
connect with talent, particularly
Millennials, and analyze whether
candidates are primed to succeed in a
given role (Deloitte, 2017).
• Ansaro is unifying all the data
companies have about their employees
to build predictive models that will
help them hire in smarter way.

23. CASE STUDY: A HIRING ALGORITHM AT
GOOGLE
• One of the few firms to approach recruiting scientifically, Google developed
an algorithm for predicting which candidates had the highest probability
of succeeding after they are hired.
• Its research also determined that little value was added beyond four
interviews, dramatically shortening time to hire.
• Google is also unique in its strategic approach to hiring because its hiring
decisions are made by a group in order to prevent individual managers
from hiring people for their own short-term needs.
• Under Project Janus, it developed an algorithm for each large job family
that analyzed rejected resumes to identify any top candidates they might
have missed.
• They found that they had only a 1.5% miss rate and as a result they hired
some of the revisited candidates.

24. #2: PROGRAMMATIC JOB
ADVERTISING
• Berendt (2018) emphasizes the strategic business imperative of
programmatic advertising. This technique gives recruiters the ability to
place highly targeted ads in front of the right people at exactly the
right time, based on their browsing history and online activity.
• Cognitive recruiters can understand candidate browsing activity using
cookies to track candidates who visit their company career page,
allowing them to compile records of what other pages they’re
browsing.
• By using data management processing (DMP), recruiters can then
select a target set and find other candidates who match up.
• Plug this data into an online advertising platform and it ensure that a
specific group of users sees your job posting, wherever they are,
expanding your reach significantly beyond the local talent pool.
• This can help recruiters grow the top of the recruitment funnel with
qualified and interested talent from different regions e.g. LinkedIn
already offers similarly targeted job posts , shown to the most relevant
candidates.

25. WRITING THE PERFECT JOB ADVERT
• The job advert is the genesis of a job applicant’s journey and it’s likely to be the initial
window of contact with a prospective company.
• Textio is an example of a company that gets how important a high-quality job post is for the
number of qualified and diverse candidates that will apply as a result. They aim to help
companies create better job postings that will help differentiate them.
• Their approach is twofold:
❑ Data and predictive analytics. Textio uses algorithms to assess and analyze meaningful
language patterns that cause some posts so succeed where others don’t.
❑ Using those keyword terms that make an ideal post, depending on the candidate the
company is looking for, the software then suggests language choices that will lead to a
more successful placement.
❑ Even better is the fact that the software can learn. As the number of analyzed postings,
adverts and descriptions increases, so does the accuracy of the language predictions.
❑ Textio leverages an extensive database to help write better job adverts
• Job postings: Technology that uses sentiment analysis helps recruiters identify potentially
biased language and provides suggestions on creating job descriptions that attract a more
diverse candidate pool.

26. CANDIDATE PROFILE AUGMENTATION
• Berendt (2018) predicts that AI will soon make it possible to see far more than a
candidate’s job history.
• Using the same technology that allows companies to model people’s behaviour
based on their browsing histories and interests, recruiters could infer a person’s
interests and latent skills.
• This would allow recruiters to recommend jobs related to what they want to do,
not just what they currently do.
• This could be especially useful for roles that are difficult to fill.
• If recruiters were able to augment the profile of people on LinkedIn with data on
their interests, intent and activity, they would be able to find them.

27. #3: CANDIDATE OUTREACH
• Most companies currently have one version of their employee
value proposition (EVP) that they use for all outreach.
• Savvy recruiters now have access to new technologies to forge
connections with candidates and strengthen the employment
brand.
• HC Trend: Building a strategic and digital employment brand
(Deloitte, 2017)
• Berendt (2018) states that companies will soon develop thousands
of personas, allowing recruiters to quickly hyper-personalize
candidate outreach to speak more directly to an individual’s
needs.

28. #3: CANDIDATE
OUTREACH
• Using intelligent targeting and
Crystal Knows, cognitive recruiters
can attract people using a value
proposition that’s tailored exactly
to their needs.
• Rediscovery: Similar to sourcing,
recruiters are able to use AI that
analyzes a job description and
then searches their existing ATS
database to rediscover candidates
who applied for a prior role who
fit the requirements of a current
open requisition.

29. #4: CANDIDATE EXPERIENCE AND
RELATIONSHIP BUILDING (JOB
SHOPPERS)
• Savvy recruiters now have access to new technologies
to forge connections with candidates and strengthen
the employment brand (Deloitte, 2017).
• Beamery focuses on treating candidates like customers.
The company’s candidate relationship platform
‘proactively builds relationships with passive
candidates, reduces hiring cycles and creates a single
source of truth for all your hiring data’.
• This means that the AI and ML elements of the platform
identify so-called priority (passive) candidates and
better yet, even suggest what times best to reach out
to those candidates.
• Beamery is a good example of how a company is using
AI in recruitment to create better, more human
relationships with candidates and to truly treat them
like customers.
• Engage Talent allows recruiters to discover passive job
seekers and target them with personalized messages
at the right time.

30. #4: CANDIDATE EXPERIENCE AND
RELATIONSHIP BUILDING (JOB
SHOPPERS)
• AI in recruitment can significantly improve candidate
engagement through improved communication
between candidates and employers. According to Mya,
a product developed to simplify recruitment, its system
has averaged “a 9.8 out of ten on overall candidate
experience”.
• This is because it can provide candidates with updates,
feedback and guidance, as well as answer their
questions in real-time.
• This communication - which has a significant impact on
candidate experience - is generally lacking in most
companies.
• Messaging - recruiters are aided by chatbots that use
natural language processing to collect information from
candidates, ask screening questions, answer FAQs
about the job, and schedule an interview.
• Information collected by the chatbot is then fed into an
ATS or sent directly to a human recruiter to follow up.

31. AGREE OR DISAGREE?
WHY?

32. #5: AI-POWERED ASSISTANTS (CHATBOTS) AND
MACHINE LEARNING ASSISTING APPLICATION
• Some companies are already using chatbots in recruiting. Sutherland, for example,
uses a bot called, Tasha to answer basic questions from an applicant, responding
24-7.
• Bots can also follow up with candidates if they aren’t actively progressing with an
application.
• They can facilitate the conversation with once [people] arrive at the website, and
they can guide [them] across the funnel.
• By means of NLP, Olivia engages with candidates via the web, various mobile
platforms and/or social channels and she also handles the scheduling part of the
recruitment process.
• Tools like Mya can decode a candidate’s responses through Natural Language
Processing to spot certain skills.
• Mya can also ask questions to fill in gaps in the candidate’s résumés, giving
recruiters a clearer picture of their suitability for a role.

34. #6: PROMOTING EFFICIENCY - SCHEDULING
MEETINGS WITH CANDIDATES
• X.ai, a solution that can help tackle the administrative nightmare of
scheduling interviews.
• According to Berendt (2018), automated appointment setting will help
recruiters to quickly and easily schedule meetings with candidates.
• Software reviews the recruiter’s calendar, asking a few basic questions and
offering viable options to the candidate.
• However, the human element won’t disappear entirely from recruiting.
Meeting with candidates to give them a good feel for your company culture
will remain vital.
• With so much automation elsewhere, recruiters’ time will be freed up to
focus on things like the candidate experience, so these meetings could
become even better.

35. #6: PROMOTING EFFICIENCY -
ELIMINATING TEDIOUS TASKS
• For most recruiters, the worst part of their job is often
the most time-consuming—the administrative tasks
of screening candidates and scheduling interviews.
• With the help of AI, recruiters and hiring managers can
reduce wasted time by automatically screening
obviously unqualified candidates’ resumes using
keyword and qualification searches.
• AI can also help schedule interviews with those
qualified candidates with an auto-email interview
request service or chat-based program that
surprisingly brings a bit more personalization to the
process.
• Not only does this save time for recruiters to focus on
more important tasks, it also accelerates the screening
process, reduces time-to-hire, and ultimately gives
those companies an advantage when competing with
other companies for talent.

36. #7: CV SCREENING
• According to Berendt (2018), some companies are already using résumé
screenings to find talented candidates and remove unqualified ones.
• ML technology helps recruiters automate screening by learning what
existing employees’ skills and other qualifications are and applying this
knowledge to screen and grade new candidates.
• Once a new résumé is received, recruiters can benchmark that with the
knowledge that they have from their existing employer base.
• It can be screened not only for the keywords, but also for the meaning. So,
if someone has used a different term to describe what they do, the
solutions are now clever enough to decode it.
• These solutions can quickly and effectively compare prospective
candidates to those who’ve proven talented in the past. With this data,
you can more efficiently find those best suited for the job.

37. #7: CV SCREENING
• AI can find patterns. By knowing who got a job within your
company, these systems are able to predict who would be a
successful candidate going forward.
• Recruiters know all too well how resumes are an incomplete
picture of someone’s skills, achievements, capabilities and most
importantly, personality and company fit.
• AI technology is enhancing screening measures e.g. software
Harver uses engaging tests to assess candidates on the types of
tasks they’ll actually be asked to do on the job.
• Ansaro goes a bit beyond that to cull all the data and metrics
companies have on their employees to build predictive models
and personality profiles that help lead them to candidates who fit
the company culture and job requirements more accurately.

39. #8: DEEPER
AND RICHER
CANDIDATE
INSIGHTS -
NATURAL
LANGUAGE
PROCESSING
(NLP)
According to Berendt (2018), AI will help
cognitive recruiters learn even more - analyzing
more than just the words themselves.
These solutions use natural language processing
to check the fluency of the speech, the
pronunciation, the vocabulary and even the
progression of ideas.
This is beneficial for checking language
competency when hiring in diverse markets, but
it will also be useful for testing native speakers.
The AI will analyze their speech to learn what
type of person they are and tell recruiters how
engaging or trustworthy they sound.
For jobs where talking plays a big part e.g. sales,
this will be particularly important.

40. #8: DEEPER
AND RICHER
CANDIDATE
INSIGHTS -
VIDEO
INTERVIEWS
& FACIAL AND
SPEECH
RECOGNITION
SOFTWARE
Berendt (2018)
believes that in a
future video interview
scenario, a candidate
may only have to speak
to the camera while
the machine takes
them through a list of
questions.
As the candidate talks
to the machine and
the machine
processes their
speech to give the
recruiter a detailed
report, there is no
need for human
interaction - a huge
time-saver.
This will free up a lot of
time for recruiters, who can
still meet with top
candidates but won’t need
to laboriously interview
every single applicant.
Companies like HireVue use facial and
speech recognition software to analyze
the candidate’s body language, the
tone of their voice, their stress level
etc.
It might also help
eliminate unconscious
bias, since the technology
won’t have the same
hardwired preconceptions
as humans.

41. #8: DEEPER AND RICHER CANDIDATE
INSIGHTS – DETECTING IRREGULAR
CANDIDATE BEHAVIOUR DURING VIDEO
INTERVIEWS
• Using video as a tool for a compelling candidate experience.
(Deloitte, 2017)
• Video interviews are rapidly becoming an integrated part of
(mobile) recruiting. Apart from promoting efficiency, it also allow
them to get a feel for a candidate’s energy, the way they present
themselves and a more tangible overall impression.
• Paññã is an AI-driven platform, specialized in technical hiring. The
platform provides AI hiring, an ever-growing repository of dynamic
questions, expert evaluation, recorded interviewing, video
conferencing and voice and face recognition.
• The company uses ML to verify the applicants’ video interviews and
see if there is any type of strange behaviour going on. This means
the system can detect if the candidate is regularly looking away
from the screen – which may indicate the use of cue cards – or if
there is another voice on the recording – which may indicate that
the applicant has a friend on the phone for help.
• Although Paññã is powered by AI, there is also an intuitive
interface.

42. #8: DEEPER AND RICHER CANDIDATE
INSIGHTS – DETECTING IRREGULAR
CANDIDATE BEHAVIOUR DURING VIDEO
INTERVIEWS
• With the help of emotion recognition
software like Affectiva, companies can
better assess candidates' emotional
intelligence and truthfulness during video
interviews by analyzing facial expressions,
their word choice, speech rate and vocal
tones.
• These types of software not only help
recruiters determine if a candidate is
being honest and showing genuine
interest in a position, but they also help
remove human biases.
• AI software can help identify whether
their judgement is correct or if this
individual isn’t all that interested and
they’d be better off spending their time
with other potential candidates.

43. #9: ELIMINATING UNCONSCIOUS
HUMAN BIAS BY MEANS OF
PREDICTIVE ANALYTICS
• Studies have shown that humans are
notoriously poor at picking the right applicant
and a meta-analysis illustrated that algorithms
can outperform human experts in hiring.
• According to IBM Watson Talent, gut-based
decisions are no longer acceptable - it’s time
for HRM to rethink its talent strategies –
intuition to intellect.
• According to a 2017 Glassdoor report, as much
as 66% of Millennials are considering to leave
their current jobs by 2020.
• Therefore, an AI recruitment tool using
predictive analytics to recommend candidates
may be just be the solution for many
companies that struggle with unwanted
turnover.

44. #9: ELIMINATING
UNCONSCIOUS HUMAN BIAS
BY MEANS OF PREDICTIVE
ANALYTICS
• However, only 7% of companies use
analytics to make sourcing predictions
and take future actions on those issues.
• Harver, pre-hiring platform, uses data
and predictive analytics to make
predictions on an applicant’s likelihood
to succeed in the role that they’ve
applied for.
• Based on criteria that are specific to the
job and others that are linked to a
company’s cultural requirements,
algorithms calculate a matching score
for every candidate.
• Cognitive systems increase the
likelihood of recruiters identifying the
best fit.

45. #10: ADVANCED
COMPETENCY TESTING
• According to Berendt (2018),
sophisticated companies are
providing neuroscience games,
with the objective of
determining the candidates’
emotional and cognitive traits.
• These games are an excellent
tool to measure candidates’
soft skills that may otherwise
be difficult to detect.
• They can also help recruiters
assess a candidate’s willingness
to take risks e.g. companies like
Pymetrics.

46. #10: ADVANCED
COMPETENCY TESTING
• This AI functionality
enables recruiters to
place the candidate in a
better role or disqualify
them from the job
application process.
• Filtered can help assess
technical candidates
through auto-generated
coding challenges.

47. CONCLUSION
• Key points
• Summary
• Question and
Answer session

48. LIST OF SOURCES
• https://business.linkedin.com/talent-solutions/blog/future-of-
recruiting/2018/9-ways-ai-will-reshape-recruiting-and-how-you-can-
prepare
• Deloitte Consulting LLP. 2017. Global human capital trends report for South
Africa 2018. Oakland, CA: Deloitte University.
• Deloitte Consulting LLP. 2018. Global human capital trends report for South
Africa 2018. Oakland, CA: Deloitte University.
• https://www.forbes.com/sites/valleyvoices/2018/01/29/how-ai-is-
changing-the-game-for-recruiting/#2fa583811aa2
• https://harver.com/blog/uses-ai-in-recruitment/?cn-reloaded=1
• http://www.yoh.com/blog/future-recruiting-4-ways-artificial-intelligence-is-
changing-the-hiring-process

49. CONTACT DETAILS
• Dr. Charles Cotter
• (+27) 84 562 9446
• charlescot@polka.co.za
• LinkedIn
• Twitter: @Charles_Cotter
• https://www.facebook.com/CharlesACotter/
• http://www.slideshare.net/CharlesCotter