Upskilling and reskilling for talent transformation in the era of AI

Artificial
intelligence
(AI)
represents
a
once-in-a-lifetime

change
management
opportunity
that
might
decide
who
wins
and
loses
across
every
industry.
As
the
AI
era
takes
shape
through

digital
transformation
initiatives,
executives
and
employees
alike
are
contemplating
how
it
affects
employment
and
the
skills
needed
to
stay
ahead.
This
is
where
AI
upskilling
and
reskilling
come
into
play.

How
executives
and
employees
view
the
era
of
AI

An
IBM
Institute
for
Business
Value
report
found
that

more
than
60%
of
executives
say
that

generative
AI
will
disrupt
how
their
organization
designs
customer
and

employee
experiences.
Employees
need
to
change
to
meet
those
needs.
Many
are
turning
to
AI

upskilling,
the
act
of
preparing
the
workforce
with
skills
and
education
to
empower
them
to
use
AI
to
do
their
jobs.

A

2024
Gallup
poll
found
that
nearly
25%
of
workers
worry
that
their
jobs
can
become
obsolete
because
of
AI,
up
from
15%
in
2021.
In
the
same
study,
over
70%
of
chief
human
resources
officers
(CHRO)
predicted
AI
would
replace
jobs
within
the
next
3
years.

The
World
Economic
Forum
estimated
that

automation
will
displace
85
million
jobs
by
2025,
and
40%
of
core
skills
will
change
for
workers
in
its

Future
of
Jobs
Report
2023.
AI
will
usher
in
a
new
era
of
productivity
and
value,
and
business
leaders
in
the
C-suite
should
make
employees
part
of
that
future.

Every
organization
is
responsible
for
providing
its
workforce
with
the
requisite
skill
sets
and
education
to
use
AI
in
their
daily
jobs.
CHROs,
specifically,
should
take
a
leading
role
in
decision-making
when
it
comes
to
what
skills
technology
automates
and
which
ones
remain
mission-critical
skills
handled
by
employees.

The
rise
of
AI
is
fundamentally
remaking
corporate
strategy.
Executives
must
enhance
AI
capabilities,
such
as
using

generative
AI
tools,
throughout
the
workforce.
They
must
provide
opportunities
to
develop
employees’
skills
as
the
AI
takes
on
some
of
the
previous
tasks
handled
by
humans.

Employees
are
interested
in
learning
advanced
technical
skills
that
can
harness
the
power
of
AI
to
make
their
jobs
more
efficient
and
their
career
paths
more
successful.
Organizations
have
a
vested
interest
in
upskilling
their
employees
to
better
use
new
technologies
such
as
AI
in
their
daily
activities
to
enhance
productivity
and
improve
problem
solving.

Upskilling
versus
reskilling

Upskilling
and
reskilling
are

separate
but
important
components
of
an
organization’s
approach
to

talent
development
and
skill
building.
The
first,
upskilling,
is
the
process
of
improving
employee
skill
sets
through
training
and
development
programs.
The
goal
is
to
minimize
skill
gaps
and
prepare
employees
for
changes
in
their
job
roles
or
functions. An
example
of
upskilling
is
customer
care
representatives
learning
how
to
use
generative
AI
and

chatbots
to
better
answer
customer
questions
in
real
time
with
prompt
engineering.

Reskilling
refers
to
learning
an
entire
set
of
new
skills
to
do
a
new
job.
For
example,
someone
who
currently
works
in
data
processing
might
need
to
embrace
reskilling
to
learn
web
development
or
advanced
data
analytics.

Executives
estimate
about
40%
of
their
workforce
needs
to
reskill
over
the
next
3
years,
according
to
the

IBM
Institute
for
Business
Value.
But
what
about
upskilling?

Read
more
about
reskilling
your
workforce
in
the
time
of
AI

AI
upskilling
opportunities
in
disciplines
and
industries

Like
other
groundbreaking
technologies
before
it,
the
evolution
of
AI
is
creating
opportunities
for
new
industries,
new
jobs
and
new
approaches
to
existing
jobs.
To
prepare
their
people
and
businesses,
organizations
must
ensure
that
their
employees
are
equipped
with
the
skills
for
tomorrow
without
disrupting
today’s
business.
This
is
where
a
range
of
upskilling
use
cases
are
critical
for
success.

Customer
service

Customer
service
is
most
CEOs’
top
discipline
for
deploying
generative
AI,
according
to
an

IBM
Institute
for
Business
Value
report.
AI
can
handle
some
of
the
initial
queries
by
customers,
but
customer
service
representatives
(CSRs)
also
need
to
use
the
tools
when
issues
get
escalated
to
them.
CSRs
need
to
improve
their
ability
to
do

prompt
engineering
and
talk
to
customers
while
searching
through
AI-built
databases.

Financial
services

Employees
in
finance
increasingly
have
enhanced
tools
to
help
them
make
better
investments
on
behalf
of
their
clients.
Nearly
70%
of
financial
services
leaders
believe
at
least
half
of
their
workforce
requires
upskilling
in
2024.
It
requires
not
only
learning
how
to
use
these
new
technologies,
but
also
feeling
they
can
trust
the
results
from
AI
technologies,
even
if
they
cannot
completely
understand
them.

Healthcare

Hospitals
and
healthcare
providers
are
incorporating
AI
technologies
into
their
back
offices
and
diagnostic
care
facilities.
For
example,
healthcare
companies
are
starting
to
use

machine
learning
technologies
to
improve
and
speed
up

medical
diagnoses.
Understanding
what
these
technologies
can
and
cannot
do
remains
critical
for
healthcare
professionals
to
make
the
right
decisions.

Human
resources
(HR)

Organizations
are
beginning
to

use
AI
in
HR—to
process
job
applications
and
help
find
the
right
candidates.
HR
representatives
need
to
learn
how
to
use
this
technology
to
spot
potential
biases
or
other
uncertainties,
so
they
find
valuable
prospects.

Web
development

Generative
AI
and
other
advanced
technologies
are
creating
massive
opportunities
for
efficiency
in
web
development.
Developers
can
use
it
to
convert
one
coding

language
into
another.
One
such
example:
applications
can
refactor

COBOL
code
for
mainframes
into
modular
business
service
components.

How
AI
can
supercharge
upskilling
opportunities

Organizations
can
use
AI
technologies
to
enhance
the
AI
learning
experience
itself.

Online
learning
and
development

Using
generative
AI
chatbots
and
personalization
can
create
more

customized
learning
opportunities
for
each
employee.
It
can
create

training
programs
that
combine
the
foundational
AI
education
any
employee
needs
with
specific
instruction
tailored
to
the
learners’
jobs.
As
a
result,
the
employee
has
a
robust
and
tailored
set
of
AI
skills
that
helps
them
maximize
their
job
capabilities.

Here’s
a
sample
course
load
for
an

AI
upskilling
development
program
that
IBM
offers:

• 
  Strategic
  essentials,
  such
  as
  the
  rise
  of
  generative
  AI
  for
  business
  and
  how
  to
  become
  a
  value
  creator
  with
  generative
  AI.

• 
  Elements
  of
  enterprise
  AI,
  such
  as
  using
  data
  management
  and
  generative
  AI
  foundation
  models
  to
  drive
  added
  value.

• 
  Putting
  AI
  to
  work
  for
  specific
  disciplines,
  such
  as
  marketing,
  coding
  or
  talent
  development.

On-the-job
training

Employees
can
improve
their
knowledge
and
expertise
in
AI
tools
by
using
AI
applications
while
doing
their
jobs.
Using
generative
AI
tools,
for
instance,
can
help
them
answer
questions
they
have
about
certain
processes,
while
teaching
them
how
to
improve
their
prompts.

Skill-gap
analysis

Organizations
can
input
a
ton
of
information
about
their
employees’
performance
and
certifications
and
use
machine
learning
to
identify
areas
where
they
need
more
training.
This
approach
is
a
more
efficient
way
to
identify
gaps
than
through
guesswork
or
asking
employees
where
they
need
help.

Mentorship

AI
can
help
large
organizations
better
identify
mentors
and
mentees
based
on
various
criteria,
such
as
backgrounds,
interests
and
what
they
want
out
of
that
relationship.
An
AI
program
that
automatically
matches
mentors
and
mentees
eliminates
a
laborious
task
and
drives
stronger
connections
across
the
organization.

Career
path
development

Organizations
can
help
employees
identify
where
they
want
their
careers
to
progress
by
using
AI.
It
can
suggest
potential
career
paths
and
have
them
cycle
through
options
until
their
ideal
job.

Why
AI
upskilling
provides
added
value
for
organizations

It
combines
institutional
knowledge
with
advanced
capabilities

While
AI
and
other
technologies
can
create
opportunities
for
organizations
to
automate
many
processes,
they
still
need
employees
to
provide
valuable
context.
Helping
existing
employees
remain
valuable
to
the
organization
serves
a
dual
purpose
of
using
their
hard-won
experience
to
improve
decision-making.

One
way
to
incorporate
AI
into
employee
work
is
using
IBM

role-based
AI
assistants
with
conversation-based
interfaces
that
can
support
key
consulting
project
roles
and
tasks.

It
fills
important
gaps

Many
AI
technologies
require
humans
to
operate
them
or
interpret
the
results.
Organizations
that
try
to
deploy
these
technologies
without
worker
assistance
can
either
fail
to
maximize
results
or
make
incorrect
decisions.

It
improves
employee
retention

Employees
are
unlikely
to
stay
at
organizations
that
don’t
prioritize
the

employee
experience,
which
should
now
include
AI
skill
development.
One
reason
is
that
they
expect
their
employees
to
provide
lasting
skills
for
their
jobs
and
careers.
A
second
reason
is
that
organizations
that
are
not
prioritizing
AI
are
likely
to
fall
behind
their
competitors.

It
embraces
the
democratization
of
web
development

AI
is
driving
a
massive
change
in
web
development.
The
age
of
AI
ushers
in
a
wave
of
generative
AI
code
development
that
enables

nondevelopers
to
build
code
as
well.
But
only
if
an
organization
invests
in
educating
its
employees
on
how
to
use
it.

It’s
the
right
thing
to
do

Organizations
owe
their
employees
every
chance
to
remain
valuable
in
a
rapidly
changing
talent
landscape.
The
future
of
work
can
leave
many
unprepared
employees
behind.
Training
employees
in
AI
skills
helps
the
organization
today,
but
also
provides
those
employees
with
a
roadmap
for
future
success.

Put
AI
to
work
for
HR
and
talent
transformation
with
the
AI
Academy
Guidebook

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