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Thur, 21st September 2017 12-1 PM, Sydney
Ways to participate:
• Q&A Box - comment, whinge & share
• Twitter Backchannel - @capabilitycafe #AI/ML
Knowledge
Sharing
Better Practices
Experienced
Panel
Impact of Artificial
Intelligence/Machine Learning on
Workforce Capability
Introductions Adslot
ANZ
Articulate Consulting
Baxter Healthcare
Bayer
Blackboard
BNZ
Canon Australia
Career BluePrint
CBA
Coca-Cola Amatil
Cochlear
Create LMS
DEDJTR
Deloitte
DHS
e3 Learning
EY
GPC AP
Health Care Services Corporation
Hoffman Consulting
IAG
IMC
Improvising Careers
Intouch Solutions
LearnD
LLN In-Sight
Macquarie Bank
Maddocks
Maura Fay Learning
Ray Greenwood
Machine Learning Architect
SAP Australia and New Zealand
Prashanthi Sylada
Global Transition and Organization
Change Adviser
Jeevan Joshi
Producer & Founder
CapabilityCafé /LearningCafe
Consultant - LearnD
News Corp
NSW Department of
Education
Pernod Ricard
Winemakers
Prometheus Workplace
Solutions
Qantas
QBE
Qudos Bank
Rio Tinto
safe patient system
group Ltd
SMS Management &
Technology
South West TAFE
Sponge Uk
Squiz
SUNCORP
SWTAFE
Telstra
Thiess
tna solutions
University of Santo
Tomas
Ventia
WBC
Westpac
100+ 50+
Registrations Organisations
Blog
Magazine
Webinars
UnConference
Twitter
Linkedin
Facebook
Coffee Catch
Ups
Workshops
Community of Capability Professionals
with a focus on implementing ideas
Building
Capability
L&D
Human Resources
Workforce Planning
Capability Managers
Change Managers
Future of Work
Context
Culture
Tools
Frameworks
Business
Results
Competencies
Learning
Capability
Management
CAPABILITY MANAGEMENT Ver 0.8
• L&D
• Workforce
Planning
• Acquisition &
Recruitment
• Organisation Design
• Leadership
• Engagement
• Rewards inc Perf Mgt
• Operations
• IT
• Shared Services
Our definition of
Capability is the
combination of
Knowledge and skills +
right tools + context that
allow the results to be
delivered.
We believe that desired
business results cannot
be optimally achieved
without optimising the
three legs of Capability.
JEEVAN JOSHI
Producer & Founder at CapabilityCafé & LearningCafe
Jeevans Slide 1
http://www.alphabeta.com/the-automation-advantage/
Context
Culture
Tools
Frameworks
Business
Results
Competencies
Learning
Capability
Management
CAPABILITY MANAGEMENT Ver 0.8
Context will be
relevant to people
aspects
Tools will
accommodate AI
CapabilityCafe’s Take on Business Adoption
InventionExperimentAdopt
0 2 4 6
Chatbots for
Admin
Rec Engines
Acquisition
Voice Assistants
e.g. Alexa,
Google Home
Virtual Personal
Assistants
Hybrid Capability
Frameworks
Aug Reality/
Virtual Reality
Rec Engines - Learning
Aug Reality/
Virtual Reality
Rec Engines - Learning
Rec Engines
Acquisition
3 Scenarios
People
Experts
supported by
Technology
#1 Remain
People
Experts
supported by
Technology
We keep doing what
we are good at.
Improve tech
enablement
#2 People
Experts manage
impact on AI on
People
We keep doing what
we are good at and
take impact of AI on
people in our remit.
Learn more about AI
#3
Hybrid Experts
Integrate People
& AI Capabilities
We look after
capability whether it
is delivered by
people or AI. Needs
new mindset and
skills.
Intelligent machines will replace teachers within 10 years
– SirAnthony Sheldon
We always overestimate the change that will occur in the
next 2 years and underestimate the change that will
occur in the next 10
– Bill Gates
Market Trends – Digital Transformation
Emerging systems of intelligence
By 2018,
of enterprise and ISV
development will
include AI or ML
75% By 2019, APIs
will be the primary
mechanism to connect
data, algorithms, and
decision services
Embedded Machine
Learning, Analytics
providing built-in
guidance
Artificial Intelligence &
Machine Learning,
IoT, Insights
Source: IDC.
Machine learning is the reality behind artificial intelligence
 Big Data (for example, business networks,
cloud applications, the Internet of Things)
 Massive improvements in hardware
(graphics processing unit [GPU] and
multicore)
 Deep learning algorithms
 Computers learn from data without
being explicitly programmed.
 Machines can see, read, listen,
understand, and interact.
What is machine learning?
Why now?
connecting People, Things and BusinessesIntelligently
Integration Mobile
Collaboration
Big Data
Business Process
Innovation
Connected Data
Design Thinking
Microservices
APIs
Real-time
Analytics
Natural
Language
IoT NetworksMachine
Learning
Experiences
How enterprise data is transformed into business value
From data to insights
Input Machine learning Output
Train
model
Prepare
data
Apply
model
Capture
feedback
Text
Image
Video
Speech
… and more Services
(such as invoice processing
and profile matching)
…and more
Applications
An intelligent cloud helping HR drive better business outcomes through
Machine learning vision for HR
Insights and
Predictions
Automation of
routine tasks
Guidance and
Suggestions
Transformation of HR – from Talent Management to People
Management
From transactional work focused on automation
and integrating their talent practices in early
2000s, now HR is focused on people management
concerns such as employee engagement,
teamwork, innovation and collaboration.
Transactional
work
Strategic Business
Partner
Source: HR Technology Disruptions: The HR Software Market
Reinvents Itself, Bersin by Deloitte, Deloitte Consulting
LLP/Josh Bersin, November 2016
Automated Talent
Management
Automate
Integrated Talent
Management
Integrate
Engagement / Fit /
Culture / Analytics
Engage
Empowerment /
Performance /
Leadership
Empower
1990s-
2000s
2004-2012 2012-2015 2016+
Systems of Automation
Practice-driven solutions
Systems of Engagement
Data-driven solutions
Talent Management:
• Integrated processes & systems
• Talent as core to HR & business
agenda
People Management:
• Focus on:
• Culture
• Engagement
• Environment
• Leadership
• Empowerment
• Fit
The Rapid Evolution of Corporate Learning
e-Learning &
Blended Learning
Course Catalog
Online University
Instructional Design
Kirkpatrick
Self-study Online
Learning
LMS as e-Learning
Platform
Talent
Management
Learning Path
Career track
Blended Learning
Social Learning
Career-Focused
Lots of Topics
LMS as Talent
Platform
Continuous
Learning
Video, Self-Authored
Mobile, YouTube
70-20-10
Taxonomies
Learning On-Demand
Embedded learning
LMS as Experience
Platform
Digital
Learning
Microlearning Real-
Time Video
Courses Everywhere
Design Thinking
Learning Experience
Consumerlike
Always On
LMS is Invisible,
Data-Driven, Mobile
Intelligent
Learning
Intelligent
Personalized
Machine-
Driven
Formats
Philosophy
Users
Systems
2001 2005 2010 2017 2020
We are here
shift to an employee centric Digital Learning
experience, driven by intelligent, personalized and
machine-driven learning recommendations.
traditional e-Learning
LMS based systems in
the early 2000s
Source:
The Disruption of Digital
Learning: 10 Things We
Have Learned, Bersin by
Deloitte, Deloitte
Consulting LLP/Josh
Bersin, November 2016
Challenges Keeping Workers from Gaining Critical Skills &
Knowledge
The Problem
is Context,
Not Content
68%
34%
32%
23%
16%
12%
Frequent change of information makes
it difficult to find the most current
information
Inconsistency of information formats
of sources makes it difficult to
use/comprehend new information
Dynamic nature of job roles makes it
difficult to find sufficiently targeted or
relevant information
Job roles of conditions make it difficult
to access sources of information
Overwhelming volume of information
makes it difficult to notice and keep
track of useful information
Lack of effective tools( such as
search) makes it difficult to find the
most useful information
Content is no longer the problem.
The key is contextualization and recommending useful content to the knowledge worker.
Source:
1. The Contextualization of Learning
Content , Bersin by Deloitte, Deloitte
Consulting LLP/Dani Johnson, 2016
2. Bersin by Deloitte,
2014
Organizations that embrace learning outperform
their competition
more likely to be first
to market
greater employee
productivity
better response
to customer needs
better at delivering
“quality products”
more prepared to
meet future demand
more likely to be
market share leaders
Bersin & Associates, 2012
26%
37%
58%
34%
17%
46%
However, there are barriers to learning adoption
Sources: The State of Learning Measurement, Bersin by Deloitte, 2015; The Starr Conspiracy Unit Enterprise Learning Buyer 2014; Association Talent Development State of the Industry 2014
onlyArchaic Complex Ineffective
Learning Recommender helps
employees stay competitive by
connecting them with
personalized learning beyond
traditional course catalogues to fit
their learning goals and situation.
Learning Recommender
Personalized learning recommendations
Talent development to
build a better workforce
Make better use the vast
amounts of relevant and
current content available
Connect employees with
personalized learning
Help organizations
create a culture of
learning
Flight Risk helps identify key
drivers and risks of attrition
for more informed decision
making
Flight Risk Predictor
Determining who is at risk of leaving and why
Address flight risk before
employees leave
Target programs
towards attrition drivers
Identify key drivers of
attrition in the
organization
Predict likelihood of
leaving
Conversational HR is a new way
to interact with a true digital
assistant.
Conversational HR
An enhanceduser experiencewith HR Systems
Embedded within
SuccessFactors
Quick answers or
deeper conversations to
get things done
Natural language
interface
Interact via social
collaboration platforms
such as Slack, Skype
and Facebook
Talent Acquisition ML Services
Job MatchingResume Matching
Job Standardization Job Analyzer
Summary
This is just the beginning…
Machines learn from available data – collaborative data networks
If you can’t measure the result, you can’t improve the automation
Where is the line between creating and optimizing?
PRASHANTHI SYLADA
Global Transition and Organization Change Adviser
“ Will we consider it unthinkable not to use intelligent assistants to
transform recruiting, HR service centers, and learning and
development? I believe the answer is yes. HR leaders will need to
begin experimenting with all facets of AI to deliver value to their
organizations. As intelligent assistants become more widely used in
our personal lives, we will expect to see similar usage in the
workplace.”
- Bernard Tyson
CEO Kaiser Permanante
Intersection of AI and Human Resources
Intersection of AI and Human Resources : Administrative Expert
Transformative Employee Experience
 Mobile, Website, Facebook, WeChat, iMessage etc.
 Virtual, Greater Connectivity, Consistent Employee
Experience
 HR Operations, Recruitment, Talent Development
HR as an
Administrative
Expert
Transactional Role of HR
 Demonstrate deep knowledge of labor laws
 Implement all requirements from changing legislation
 Builds and Maintains Employee Policies
 Introduce HRIS solutions and eliminates data entry
 Addresses Employee queries around policies and
benefits
Case Study : Chat Bot
Mya is an A.I. recruiting assistant that manages large candidate pools, giving
FirstJob recruiters and hiring managers more time to focus on interviews and
closing offers
Mya can talk to thousands of candidates at once through SMS, Facebook,
Skype, email, or chat
Mya asks prescreen questions; responds to FAQs; delivers application
progress updates; gives tips and guidance to candidates; alerts candidates
when a position has been filled; and administers assessments and challenges
Mya also provides useful information for recruiters and managers, ranking
candidates from most qualified to least based on weighted factors like
experience, recent activity, engagement, and other metrics
According to FirstJob, Mya automates up to 75 percent of the qualifying and
engagement process.
As reported by Forbes, studies suggest that Mya improves recruiter
efficiencyby 38 percent and increases candidate engagement by over 150
percent
FirstJob: “Mya”
FirstJob is an online-based
recruiting firm that
matches recent college
graduates with entry-level
jobs and internships by
leveraging their existing
social networks
Intersection of AI and Human Resources : Skills Required to Compete
HR as a Change
Agent
Change Agent
 Strategic HR Role
 Responsible for Internal communications and
 Envisages and builds talent for future skills
 Facilitates Organization Change
Redesigning the Work Place
- Work design based on collaborative tasks as
against collaborative roles
- The integration of early artificial intelligence
tools is also causing organizations to become
more collaborative and team-oriented, as
opposed to the traditional top-down hierarchal
structures
AI is definitely not eliminating jobs, it is eliminating tasks
of jobs, and creating new jobs.” – Deloitte’s Human Capital
Survey 2017
What is Next ?
The Deloitte survey also
found that 56% of
respondents are already
redesigning their HR
programs to leverage digital
and mobile tools, and 33% are
utilizing some form of AI
technology to deliver HR
functions
Skills Needed to Succeed
Practice 1: Leave Administration to AI
Practice 2: Focus on Actionable Insights
Practice 3: Treat Intelligent Machines as “Colleagues”
– No need to race the machine
Practice 4: Work Like a Designer
Practice 5: Develop Social Skills and Networks
Skills Needed to Succeed
Explore early. To navigate in an uncertain future, HR managers must
experiment with AI and apply their insights to the next cycle of experiments.
Adopt new key performance indicators to drive adoption. AI will bring new
criteria for success: collaboration capabilities, information sharing,
experimentation, learning and decision-making effectiveness, and the ability to
reach beyond the organization for insights.
Develop training and recruitment strategies for creativity, collaboration,
empathy, and judgment skills.
Those managers capable of assessing what the workforce of the future
will look like can prepare themselves for the arrival of AI. They should
view it as an opportunity to flourish.
LET US TALK TO THE PANEL AND
YOU
www.capabilitycafe.com
@capabilitycafe
http://bit.ly/lcafefb
blogs
capability conversations
free resources
workshops
UnConference 2017
Sydney Melbourne
Webinar recording, ebooks, capability frameworks
Building Effective Employee Social Networks
46
Ideas@work Collaborations
Next Steps
Join Special
Interest
Community
Attend
Workshops
Attend
UnConference
Sydney
CapabilityCafe
LinkedIn Group
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www.capabilitycafe.com.au
Register interest
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Impact of Artificial Intelligence/Machine Learning on Workforce Capability

  • 1. 1 Thur, 21st September 2017 12-1 PM, Sydney Ways to participate: • Q&A Box - comment, whinge & share • Twitter Backchannel - @capabilitycafe #AI/ML Knowledge Sharing Better Practices Experienced Panel Impact of Artificial Intelligence/Machine Learning on Workforce Capability
  • 2. Introductions Adslot ANZ Articulate Consulting Baxter Healthcare Bayer Blackboard BNZ Canon Australia Career BluePrint CBA Coca-Cola Amatil Cochlear Create LMS DEDJTR Deloitte DHS e3 Learning EY GPC AP Health Care Services Corporation Hoffman Consulting IAG IMC Improvising Careers Intouch Solutions LearnD LLN In-Sight Macquarie Bank Maddocks Maura Fay Learning Ray Greenwood Machine Learning Architect SAP Australia and New Zealand Prashanthi Sylada Global Transition and Organization Change Adviser Jeevan Joshi Producer & Founder CapabilityCafé /LearningCafe Consultant - LearnD News Corp NSW Department of Education Pernod Ricard Winemakers Prometheus Workplace Solutions Qantas QBE Qudos Bank Rio Tinto safe patient system group Ltd SMS Management & Technology South West TAFE Sponge Uk Squiz SUNCORP SWTAFE Telstra Thiess tna solutions University of Santo Tomas Ventia WBC Westpac 100+ 50+ Registrations Organisations
  • 3. Blog Magazine Webinars UnConference Twitter Linkedin Facebook Coffee Catch Ups Workshops Community of Capability Professionals with a focus on implementing ideas Building Capability L&D Human Resources Workforce Planning Capability Managers Change Managers Future of Work
  • 4. Context Culture Tools Frameworks Business Results Competencies Learning Capability Management CAPABILITY MANAGEMENT Ver 0.8 • L&D • Workforce Planning • Acquisition & Recruitment • Organisation Design • Leadership • Engagement • Rewards inc Perf Mgt • Operations • IT • Shared Services Our definition of Capability is the combination of Knowledge and skills + right tools + context that allow the results to be delivered. We believe that desired business results cannot be optimally achieved without optimising the three legs of Capability.
  • 5. JEEVAN JOSHI Producer & Founder at CapabilityCafé & LearningCafe
  • 6.
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  • 17. CapabilityCafe’s Take on Business Adoption InventionExperimentAdopt 0 2 4 6 Chatbots for Admin Rec Engines Acquisition Voice Assistants e.g. Alexa, Google Home Virtual Personal Assistants Hybrid Capability Frameworks Aug Reality/ Virtual Reality Rec Engines - Learning Aug Reality/ Virtual Reality Rec Engines - Learning Rec Engines Acquisition
  • 18. 3 Scenarios People Experts supported by Technology #1 Remain People Experts supported by Technology We keep doing what we are good at. Improve tech enablement #2 People Experts manage impact on AI on People We keep doing what we are good at and take impact of AI on people in our remit. Learn more about AI #3 Hybrid Experts Integrate People & AI Capabilities We look after capability whether it is delivered by people or AI. Needs new mindset and skills.
  • 19. Intelligent machines will replace teachers within 10 years – SirAnthony Sheldon We always overestimate the change that will occur in the next 2 years and underestimate the change that will occur in the next 10 – Bill Gates
  • 20. Market Trends – Digital Transformation Emerging systems of intelligence By 2018, of enterprise and ISV development will include AI or ML 75% By 2019, APIs will be the primary mechanism to connect data, algorithms, and decision services Embedded Machine Learning, Analytics providing built-in guidance Artificial Intelligence & Machine Learning, IoT, Insights Source: IDC.
  • 21. Machine learning is the reality behind artificial intelligence  Big Data (for example, business networks, cloud applications, the Internet of Things)  Massive improvements in hardware (graphics processing unit [GPU] and multicore)  Deep learning algorithms  Computers learn from data without being explicitly programmed.  Machines can see, read, listen, understand, and interact. What is machine learning? Why now?
  • 22. connecting People, Things and BusinessesIntelligently Integration Mobile Collaboration Big Data Business Process Innovation Connected Data Design Thinking Microservices APIs Real-time Analytics Natural Language IoT NetworksMachine Learning Experiences
  • 23. How enterprise data is transformed into business value From data to insights Input Machine learning Output Train model Prepare data Apply model Capture feedback Text Image Video Speech … and more Services (such as invoice processing and profile matching) …and more Applications
  • 24. An intelligent cloud helping HR drive better business outcomes through Machine learning vision for HR Insights and Predictions Automation of routine tasks Guidance and Suggestions
  • 25. Transformation of HR – from Talent Management to People Management From transactional work focused on automation and integrating their talent practices in early 2000s, now HR is focused on people management concerns such as employee engagement, teamwork, innovation and collaboration. Transactional work Strategic Business Partner Source: HR Technology Disruptions: The HR Software Market Reinvents Itself, Bersin by Deloitte, Deloitte Consulting LLP/Josh Bersin, November 2016 Automated Talent Management Automate Integrated Talent Management Integrate Engagement / Fit / Culture / Analytics Engage Empowerment / Performance / Leadership Empower 1990s- 2000s 2004-2012 2012-2015 2016+ Systems of Automation Practice-driven solutions Systems of Engagement Data-driven solutions Talent Management: • Integrated processes & systems • Talent as core to HR & business agenda People Management: • Focus on: • Culture • Engagement • Environment • Leadership • Empowerment • Fit
  • 26. The Rapid Evolution of Corporate Learning e-Learning & Blended Learning Course Catalog Online University Instructional Design Kirkpatrick Self-study Online Learning LMS as e-Learning Platform Talent Management Learning Path Career track Blended Learning Social Learning Career-Focused Lots of Topics LMS as Talent Platform Continuous Learning Video, Self-Authored Mobile, YouTube 70-20-10 Taxonomies Learning On-Demand Embedded learning LMS as Experience Platform Digital Learning Microlearning Real- Time Video Courses Everywhere Design Thinking Learning Experience Consumerlike Always On LMS is Invisible, Data-Driven, Mobile Intelligent Learning Intelligent Personalized Machine- Driven Formats Philosophy Users Systems 2001 2005 2010 2017 2020 We are here shift to an employee centric Digital Learning experience, driven by intelligent, personalized and machine-driven learning recommendations. traditional e-Learning LMS based systems in the early 2000s Source: The Disruption of Digital Learning: 10 Things We Have Learned, Bersin by Deloitte, Deloitte Consulting LLP/Josh Bersin, November 2016
  • 27. Challenges Keeping Workers from Gaining Critical Skills & Knowledge The Problem is Context, Not Content 68% 34% 32% 23% 16% 12% Frequent change of information makes it difficult to find the most current information Inconsistency of information formats of sources makes it difficult to use/comprehend new information Dynamic nature of job roles makes it difficult to find sufficiently targeted or relevant information Job roles of conditions make it difficult to access sources of information Overwhelming volume of information makes it difficult to notice and keep track of useful information Lack of effective tools( such as search) makes it difficult to find the most useful information Content is no longer the problem. The key is contextualization and recommending useful content to the knowledge worker. Source: 1. The Contextualization of Learning Content , Bersin by Deloitte, Deloitte Consulting LLP/Dani Johnson, 2016 2. Bersin by Deloitte, 2014
  • 28. Organizations that embrace learning outperform their competition more likely to be first to market greater employee productivity better response to customer needs better at delivering “quality products” more prepared to meet future demand more likely to be market share leaders Bersin & Associates, 2012 26% 37% 58% 34% 17% 46%
  • 29. However, there are barriers to learning adoption Sources: The State of Learning Measurement, Bersin by Deloitte, 2015; The Starr Conspiracy Unit Enterprise Learning Buyer 2014; Association Talent Development State of the Industry 2014 onlyArchaic Complex Ineffective
  • 30. Learning Recommender helps employees stay competitive by connecting them with personalized learning beyond traditional course catalogues to fit their learning goals and situation. Learning Recommender Personalized learning recommendations Talent development to build a better workforce Make better use the vast amounts of relevant and current content available Connect employees with personalized learning Help organizations create a culture of learning
  • 31. Flight Risk helps identify key drivers and risks of attrition for more informed decision making Flight Risk Predictor Determining who is at risk of leaving and why Address flight risk before employees leave Target programs towards attrition drivers Identify key drivers of attrition in the organization Predict likelihood of leaving
  • 32. Conversational HR is a new way to interact with a true digital assistant. Conversational HR An enhanceduser experiencewith HR Systems Embedded within SuccessFactors Quick answers or deeper conversations to get things done Natural language interface Interact via social collaboration platforms such as Slack, Skype and Facebook
  • 33. Talent Acquisition ML Services Job MatchingResume Matching Job Standardization Job Analyzer
  • 34. Summary This is just the beginning… Machines learn from available data – collaborative data networks If you can’t measure the result, you can’t improve the automation Where is the line between creating and optimizing?
  • 35. PRASHANTHI SYLADA Global Transition and Organization Change Adviser
  • 36. “ Will we consider it unthinkable not to use intelligent assistants to transform recruiting, HR service centers, and learning and development? I believe the answer is yes. HR leaders will need to begin experimenting with all facets of AI to deliver value to their organizations. As intelligent assistants become more widely used in our personal lives, we will expect to see similar usage in the workplace.” - Bernard Tyson CEO Kaiser Permanante
  • 37. Intersection of AI and Human Resources
  • 38. Intersection of AI and Human Resources : Administrative Expert Transformative Employee Experience  Mobile, Website, Facebook, WeChat, iMessage etc.  Virtual, Greater Connectivity, Consistent Employee Experience  HR Operations, Recruitment, Talent Development HR as an Administrative Expert Transactional Role of HR  Demonstrate deep knowledge of labor laws  Implement all requirements from changing legislation  Builds and Maintains Employee Policies  Introduce HRIS solutions and eliminates data entry  Addresses Employee queries around policies and benefits
  • 39. Case Study : Chat Bot Mya is an A.I. recruiting assistant that manages large candidate pools, giving FirstJob recruiters and hiring managers more time to focus on interviews and closing offers Mya can talk to thousands of candidates at once through SMS, Facebook, Skype, email, or chat Mya asks prescreen questions; responds to FAQs; delivers application progress updates; gives tips and guidance to candidates; alerts candidates when a position has been filled; and administers assessments and challenges Mya also provides useful information for recruiters and managers, ranking candidates from most qualified to least based on weighted factors like experience, recent activity, engagement, and other metrics According to FirstJob, Mya automates up to 75 percent of the qualifying and engagement process. As reported by Forbes, studies suggest that Mya improves recruiter efficiencyby 38 percent and increases candidate engagement by over 150 percent FirstJob: “Mya” FirstJob is an online-based recruiting firm that matches recent college graduates with entry-level jobs and internships by leveraging their existing social networks
  • 40.
  • 41. Intersection of AI and Human Resources : Skills Required to Compete HR as a Change Agent Change Agent  Strategic HR Role  Responsible for Internal communications and  Envisages and builds talent for future skills  Facilitates Organization Change Redesigning the Work Place - Work design based on collaborative tasks as against collaborative roles - The integration of early artificial intelligence tools is also causing organizations to become more collaborative and team-oriented, as opposed to the traditional top-down hierarchal structures
  • 42. AI is definitely not eliminating jobs, it is eliminating tasks of jobs, and creating new jobs.” – Deloitte’s Human Capital Survey 2017 What is Next ? The Deloitte survey also found that 56% of respondents are already redesigning their HR programs to leverage digital and mobile tools, and 33% are utilizing some form of AI technology to deliver HR functions
  • 43. Skills Needed to Succeed Practice 1: Leave Administration to AI Practice 2: Focus on Actionable Insights Practice 3: Treat Intelligent Machines as “Colleagues” – No need to race the machine Practice 4: Work Like a Designer Practice 5: Develop Social Skills and Networks
  • 44. Skills Needed to Succeed Explore early. To navigate in an uncertain future, HR managers must experiment with AI and apply their insights to the next cycle of experiments. Adopt new key performance indicators to drive adoption. AI will bring new criteria for success: collaboration capabilities, information sharing, experimentation, learning and decision-making effectiveness, and the ability to reach beyond the organization for insights. Develop training and recruitment strategies for creativity, collaboration, empathy, and judgment skills. Those managers capable of assessing what the workforce of the future will look like can prepare themselves for the arrival of AI. They should view it as an opportunity to flourish.
  • 45. LET US TALK TO THE PANEL AND YOU
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