We are consistently bombarded with whether great recruiting is an art or a science. The truth is: it is both. The human heart and mind will always be necessary parts of a successful recruitment process. But, those required parts can be augmented to include data like we've never seen before. And, we have the science to back up the data and decipher it. 'What does it all mean and how can we benefit?' In this webinar, Data and Analytics Expert Andrew Gadomski will share the truth about Artificial Intelligence Today, where we can expect it to be tomorrow and and how it impacts talent attraction, recruiting, and employee retention. HR and Hiring Professionals will benefit from this insightful presentation based in known facts and currently used practices, as well as knowledge-based predictions about analyses-based recruitment to expedite and better the process.

1. Make Recruiting More Human
with AI
Andrew Gadomski Shelley Trout
With: Moderated by:
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Thinking Outside the Bots
Webinar Series

2. Hiretual uses AI and machine learning to source the strongest talent, 10x
faster. Source across 30+ platforms and 700M professional profiles with
Hiretual's AI sourcing assistant. Engage the strongest candidates first with
AI prioritization and save time with instant contact info, and hire efficiently
with team collaboration, pipeline management, and intelligent engagement.

3. 3
Click on the Questions panel to
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www.recruitingbrief.com/webinar-series/thinking-outside-the-box
www.humanresourcestoday.com/webinar-series/thinking-outside-the-box

4. About Andrew Gadomski
Andrew Gadomski launched Aspen Analytics in 2006 as Aspen Advisors. Over the the next 12 years, his curiosity and
refusal to accept data as a non-living part of business helped Aspen grow to become one of the most respected HR
and Recruiting Analytics Firms today. He is a sought after advisor and speaker and former adjunct professor at NYU
with an incessant need to continually learn about the thriving power behind data, and is currently pursuing an MS from
The Leonard Stern Business School at NYU in Business Analytics. Please connect with him on LinkedIn at
https://www.linkedin.com/in/andrewgadomski/
About Shelley Trout
Shelley went to UC Berkeley and majored in Anthropology & Archaeology. After working at the Center of Digital
Archaeology, she became fascinated with digital representations of personality and culture, and now leads Webinar
Production at Aggregage, providing some of the most interesting thought-leaders across a wide variety of industries with
a space to celebrate the diversity, depth, and experience of their professional cultures, personalities, and passions.
Thinking Outside the Bots
Webinar Series

5. WORKFORCE
How we acquire, develop,
and advance
TECHNOLOGY
The systems and tools we use to track our ability to
execute the workforce
DATA
MANAGEMENT
The way we gather and store that information
REPORTING
How we present the information and make decisions
on change
The Evolution of HR Analytics

6. WORKFORCE Expense Flexible Differentiator
TECHNOLOGY ERP Best-in-class Cloud
DATA
MANAGEMENT
CoE On-site E/MSS POS
REPORTING Metrics Analytics Insights
The Evolution of HR Analytics

7. OPERATIONS
HR
We are Playing Catch Up

8. ANALYTICS HAS FUNDAMENTALLY
CHANGED

9. ACCESSIBLE
FOR ALL
DEMYSTIFICATION
OF DATA
SKILL AND
CULTURE
TRANSPARENCY
ANALYTICS IS
GROWING UP
Did you know…
90% of data was created in the last 2 years?
Four Key Shifts

10. ACCESSIBLE FOR ALL
Where we enter, share, and see data is different

11. WHERE
WE
ENTER
DATA
Systems,
apps +
automations
ACCESSIBLE FOR ALL

12. HOW WE
SHARE
DATA
Highly secure,
user-based distribution
matrix
ACCESSIBLE FOR ALL

13. WHERE
WE
SEE
DATA
Need-to-know
info on a 5-inch screen
ACCESSIBLE FOR ALL

14. The demystification of the tech stack through
visualization tools, and leveraging HR tech fully.
DATA IS DEMYSTIFIED

15. …what was data cleanup exercises has become
follow-up with text messages on missing or erroneous
field entries to the user.
DATA IS DEMYSTIFIED

16. SKILL AND CULTURE TRANSPARENCY
We are merging operational performance, skill set
identification, culture match, and meritocracy.

17. In-moment engagement and operations
data picture of
in moment use.
Skills can be categorized,
visualized and tracked.
Companies can assess skills and
culture quickly, and easily use machine
learning, testing and predictive analytics.
SKILL AND CULTURE
TRANSPARENCY

18. ANALYTICS HAS GROWN UP
Automation, analytics, and storytelling are mutually exclusive. Decisions
are being made based on previous actions, machine learning, machine
cognition and of course human decision.

19. Automation has become consumer oriented – and corporate is to follow. This is
no different with data workflows. We consume data, ask it to move in a certain
way, and cater to our needs.
WORKS GREAT WITH
ANALYTICS HAS GROWN UP

20. Storytelling has become a
critical way for us to
communicate and get our points
across, with data backing it up.
ANALYTICS HAS GROWN UP

21. Debate and
discussion
has its logical
place, and
more SMEs
are used
regularly to
shed light on
issues.
ANALYTICS HAS GROWN UP

22. • When will this hire happen?
• Who will be the best hire?
• Who will leave?
• Who will work team effectively?
ANALYTICS HAS GROWN UP

23. Data visualization has
advanced...
…this is 35,000
employees on one
screen, telling me how
many are ready for a
promotion now
ANALYTICS HAS GROWN UP

24. Tested visuals, like this
scatterplot, are
revealing…
…this is a recruiter’s
active candidate pool
for open requisitions by
age, stage, and source
type
STAGE
CANDIDATE AGE IN DAYS
ANALYTICS HAS GROWN UP

25. BREAK
TIME
OUT

26. The Layers of AI
2nd / Algorithmic
Data is ingested into formulas
and presented as aggregated
or scored insight. May be
proprietary intellectual property.
4th / Artificial
Using computer based language
and logic, data is ingested and
then automated, algorithmic, and
augmented layers are executed
or presented
1st / Automation
Actions, tasks, and workflow
steps are processed based on
pre-determined scripting and/or
conditions of data
3rd / Augmented
Data is analyzed through machine
learning and can be trained by
human invention / user activity,
resulting in automation or
algorithmic activity.
Outcomes / Results
This is what we see as humans
once the AI has been rendered
Technology Barrier

27. AI & the Employee Journey
Recruiting
Onboarding
Engagement
Upskilling
Mobility
Advocacy
Emeritus
Productivity

28. AI & Recruiting
Allyo
Hiretual
Affinix
Blendoor
• Administration
• De-duplication
• Scheduling of interviews
• Bot based questioning
• Outbound sourcing / messaging
• Inbound sourcing

29. AI & Recruiting + On/Off Boarding
Axonify
RiseSmart
“Buddy” by SAP SF
Bot Frameworks
Amazon
Facebook
Google
Microsoft
• Team design
• De-duplication within systems
• Scheduling of tasks
• Bot based questioning
• Training compliance and
attention

30. AI & Recruiting + Productivity
x.ai
Allocate
Coseer
Outreach
• Paper chasing
• Meeting preparation / scheduling
• Enhancing small screen limits
• Interruption reduction
• 40% increase by 2035 (Accenture)

31. AI & Recruiting + Engagement
iRevu
Watson
Joberate
• Automated surveying
• Real time feedback
• Communication analysis
• Succession planning

32. AI & Recruiting + Upskilling
How we train people is
radically going to shift,
as we now have
machines training
machines to do the
work of humans – so
we need to focus on
what should not or
would not be done by
machines.
• Virtual / augmented reality
• Learning to Learn
• Adversarial training
• Micro training
• Training AI

33. AI & Recruiting + Mobility
The merging of staffing
and recruiting can’t be
overlooked.
The ability to move
contractors into full
time hires or vice versa
is becoming more
critical.
• Drip campaigns internally to
suggest movement
• Alignment to teams
• Specialized sourcing / branding
• Predictive exiting

34. AI & Recruiting + Advocacy
Mainstream
technologies such as
Facebook, Google,
LinkedIn, and Microsoft
are entering the talent
space quickly, fusing AI
and talent functions
together quickly.
• Referral programs
• Protected class inclusion
• Team design
• Customer integration through
loyalty / marketing programs

35. AI & Recruiting + Emeritus
Interviewing and
employment is
becoming a driver for
long term customer
acquisition, and organic
revenue growth.
• Alumni programs
• Volunteerism being ingested by
machines
• Post exit training access
• Gig economy assignments and
analysis

36. How AI and Analytics Change Recruiting Organizations
GENDER
PAY
GAP
INDIVIDUALIZED
ANALYTICS
RETAINING
ENGAGED
EMPLOYEES
THEN
NOW
FUTURE
Our growth is predicated on the ability to add to the workforce differently. Recruiters are accommodating of
temp and full time assets in the workforce, it has dramatically increased the
amount of data we need to see and analyze, and its use of AI and outsourcing will continue to mature.
Support growth quickly via M&A
activities
Change headcount with modest
adds or personnel improvement
Focus on full time employees and
applicants only
Limit contract and RPO use
Support Equity-based transactions
and investments
Design workforce to always have
flexible contingent labor
Determine use of AI vs. human
capital as part of budget
Integrate hourly work, technology,
and AI with outsourcing vendors
Recruiters engage in post hire
activities and assessment of
workforce
Constant investigation of
talent set and skills across
workforce
Flexible recruiting workforces,
resources, and technologies are
budgeted
AI and tech seen as separate from
outsourcing

37. 37
Q&A
Shelley Trout
With: Moderated by:
Managing Director, Aspen Analytics
Linkedin page: in/andrewgadomski/
Twitter ID: @AndrewGadomski
Website: myaspenadvisor.com/blog
Andrew Gadomski
Editor, Aggregage
Linkedin page: in/shelleytrout/
Twitter ID: @recruitingbrief
Website: RecruitingBrief.com
www.recruitingbrief.com/webinar-series/thinking-outside-the-box
www.humanresourcestoday.com/webinar-series/thinking-outside-the-box