The application of AI/ML is reshaping the job market and will eventually create new jobs & roles that we can’t even imagine today. Reskilling the workforce and reforming learning and career models will play a critical role in facilitating this change. The question remains if that will be provided by the traditional internal HR/L&D team or some other model.
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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
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.
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
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?
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
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.
