Can generative artificial intelligence productivity tools support workplace learning? A qualitative study on employee perceptions in a multinational corporation
Journal of Workplace Learning,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 29, 2025
Purpose
The
purpose
of
this
study
was
to
explore
employees’
perceptions
and
firsthand
experiences
the
impact
generative
artificial
intelligence
(AI)
productivity
tools,
specifically
Microsoft
365
Copilot,
on
individual
collective
learning
processes
within
a
multinational
corporation.
In
doing
so,
provides
insights
into
how
these
tools
can
shape
workplace
dynamics,
fostering
both
skill
development
collaborative
knowledge-sharing
practices.
Design/methodology/approach
authors
collected
responses
from
357
participants
through
survey
that
included
multiple-choice
open-ended
questions.
This
focuses
exclusively
qualitative
responses.
reflexive
thematic
analysis
method
used
capture
interpret
role
Copilot
–
AI-powered
assistant
integrated
suite
applications
(e.g.,
Word,
Excel,
PowerPoint,
Outlook,
Teams)
in
enhancing
their
work
opportunities
workplace.
Findings
results
highlight
four
key
themes
contributing
learning.
At
level,
Task
Support
illustrates
extent
which
AI
transform
practices
facilitate
formal
informal
pathways,
while
Meaningful
Work
underscores
tools’
foundational
knowledge
enriched
information.
organisational
culture
suggests
importance
supportive
environment
for
integration,
socialisation
highlights
its
influence
team
cohesion
essential
effective
collaboration
among
members.
Practical
implications
offer
actionable
organisations
integrating
Understanding
inform
design
targeted
training
programmes
promote
foster
sharing.
Furthermore,
positions
as
complementary
resource
improve
employee
engagement,
reduce
resistance
new
technologies
encourage
growth-oriented
mindset,
ultimately
driving
personal
development.
Originality/value
shifts
narrative
around
by
examining
enhance
at
levels,
rather
than
focusing
solely
potential
disrupt
displacement
automation.
By
positioning
AI-based
human
work,
approach
enablers
development,
sharing
job
enrichment,
more
adaptive
learning-oriented
environment.
Язык: Английский
Unmasking deepfakes: a multidisciplinary examination of social impacts and regulatory responses
Human-Intelligent Systems Integration,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 20, 2025
Abstract
This
paper
presents
a
comprehensive
analysis
of
deepfake
technology
and
its
multifaceted
impacts
on
society,
privacy,
trust,
information
integrity.
Deepfakes,
synthetic
media
generated
using
AI-powered
algorithms,
pose
significant
challenges
to
individual
societal
the
integrity
information.
To
explore
these
issues,
we
employed
mixed-methods
approach
that
included
in-depth
expert
interviews
with
professionals
from
diverse
fields
such
as
law,
ethics,
artificial
intelligence,
cybersecurity,
social
sciences,
along
dichotomous
question
survey,
which
provided
insights
multiple
perspectives.
methodological
facilitated
multidimensional
perspective
potential
risks
benefits
deepfakes.
Our
findings
reveal
unanimous
concern
among
experts
regarding
profound
implications
deepfakes,
particularly
their
capacity
amplify
disinformation,
erode
public
inflict
psychological
harm
individuals.
Key
themes
identified
include
urgent
need
for
robust
regulatory
frameworks,
critical
role
literacy
in
enhancing
resilience,
varying
deepfakes
across
different
demographic
groups.
The
consensus
points
out
necessity
an
ethically
guided
development
deployment
technology,
emphasizing
importance
interdisciplinary
collaboration
crafting
effective
policy
responses.
study
advances
ongoing
discourse
by
providing
stakeholders
policymakers
evidence-based
recommendations
aimed
at
mitigating
associated
harnessing
benefits.
These
promote
balanced
informed
navigating
complexities
this
emerging
technological
challenge.
Язык: Английский
Change Management in Hospital Digital Transformation: Roadmap to Promote the Humanization and Efficiency Through Technology
Опубликована: Янв. 1, 2025
Язык: Английский
Exploring human-robot interaction in remanufacturing: bibliometric insights
International Journal on Interactive Design and Manufacturing (IJIDeM),
Год журнала:
2025,
Номер
unknown
Опубликована: Март 12, 2025
Abstract
Human–robot
interaction
(HRI),
in
all
its
different
variants,
has
gained
significant
attention
industry.
The
combination
of
human
skills
and
robotics
significantly
enhances
manufacturing,
improving
operations
quality
efficiency.
This
is
particularly
relevant
highly
variable
contexts
like
remanufacturing,
which
aims
to
preserve
the
value
products
components
over
time
involves
complex,
non-standardized
tasks
such
as
inspection,
disassembly,
reprocessing,
reassembly.
Uncertainties
related
conditions
remanufacture
cannot
be
managed
by
pure
automation
making
HRI
beneficial.
Although
researchers
have
focused
on
use
several
fields
application
(from
construction
logistics),
no
extensive
mapping
research
trends
specifically
addressed
intersection
remanufacturing
contexts.
To
fill
this
gap,
paper
presents
a
comprehensive
study
based
bibliometric
analysis
explore
current
state
topic.
Based
120
articles
from
Scopus
database,
points
out
main
countries,
authors,
affiliations
involved
field.
In
addition,
key
topics
were
analyzed.
A
predominant
focus,
above
last
three
years,
Human-Robot
Collaboration
(HRC)
among
levels
HRI,
disassembly
processes
was
highlighted,
while
other
activities,
reassembly,
received
comparatively
less
attention.
An
unexplored
frontier
integration
Artificial
Intelligence
Machine
Learning
with
HRC
remanufacturing.
These
findings
offer
valuable
insights
for
researchers,
scholars,
industrial
professionals
aiming
advance
Язык: Английский
Navigating Uncertainty: Exploring Consumer Acceptance of Artificial Intelligence Under Self-Threats and High-Stakes Decisions
Technology in Society,
Год журнала:
2024,
Номер
unknown, С. 102732 - 102732
Опубликована: Окт. 1, 2024
Язык: Английский
Integration of Industry 5.0 and Eco-Innovation for Sustainable Manufacturing
Advances in human resources management and organizational development book series,
Год журнала:
2024,
Номер
unknown, С. 447 - 472
Опубликована: Окт. 22, 2024
In
the
age
of
Industry
5.0
(I
5.0),
manufacturing
SMEs
face
critical
challenge
balancing
technological
advancement
with
environmental
sustainability.
This
study
explores
intricate
relationships
between
technologies—specifically
Big
Data
Analytics
and
Artificial
Intelligence
(BDA-AI),
Human-Robot
Collaboration
(HRC),
Internet
Things
(IoT),
sustainable
practices
in
SMEs.
Drawing
on
data
from
466
across
key
industrial
regions,
we
employ
structural
equation
modeling
to
uncover
transformative
roles
Eco-Innovation.
Our
findings
reveal
that
Eco-Innovation
(Eco-Inn)
acts
as
a
pivotal
mediator,
translating
capabilities
into
enhanced
performance
(EP).
breaks
new
ground
by
examining
ethical
implications
within
5.0,
offering
insights
its
long-term
sustainability
impact.
By
integrating
resource-based
view
theory,
this
research
presents
novel
framework
for
digital
era.
Язык: Английский
REDECA Framework Enhancing Occupational Safety and Health Through Artificial Intelligence Applications
Sheila Michiel,
Isabelle Moissact,
Christopher Sean
и другие.
Safety and Health For Medical Workers,
Год журнала:
2024,
Номер
1(2), С. 95 - 110
Опубликована: Июль 10, 2024
Objective:
This
paper
aims
to
show
how
REDECA
Reengineering
Delphi
and
Evaluation
can
be
integrated
with
Artificial
Intelligence
(AI)
in
a
way
increase
the
influence
of
AI
on
Occupational
Safety
Health
(OSH)
by
further
advancing
risk
identification
process,
prevention
injuries,
compliance
safety
standards.Methods:
A
quantitative
cross-sectional
study
method
was
used
through
multiple
regressions
analysis
for
relationships
between
application,
identification,
injury
reduction,
culture,
compliance.
Organizational
culture
explored
as
moderator
influencing
effectiveness
OSH
systems.Results:
enhances
prediction
risk,
resulting
significant
reduction
workplace
injuries
fatalities.
AI-enabled
applications
ensure
higher
adherence
protocols
helped
building
time-tested
culture.
In
fact,
organizational
improves
AI,
serving
vital
moderating
factor
that
facilitates
lasting
advancements
practices.
points
relationship
technological
innovation
influences
better
outcomes.Novelty:
presents
an
original
integration
AI-driven
predictive
mechanisms
framework,
highlighting
role
serves
bridge
technology
adoption
behavior
advance
strategies.Research
Implication:
The
findings
provide
roadmap
organizations
not
just
invest
AI-based
systems
but
also
inculcate
strong
reap
rewards
technical
advances.
research
sends
message
fostering
transformative
approach
management,
which
sustainable
improvements
safety,
mitigation
employed
well-being
policymakers
industry
leaders.
Язык: Английский