5 methods to adopt responsible generative AI practice at work
Being
able
to
catch
up
with
a
busy
Slack
channel
once
a
day
could
also
improve
productivity
and
work-life
balance,
but
those
who
make
the
plans
and
decisions
should
take
responsibility
for
making
sure
AI
summaries,
action
items,
and
timescales
are
accura
Being
able
to
catch
up
with
a
busy
Slack
channel
once
a
day
could
also
improve
productivity
and
work-life
balance,
but
those
who
make
the
plans
and
decisions
should
take
responsibility
for
making
sure
AI
summaries,
action
items,
and
timescales
are
accurate.
AI
tools
that
summarize
calls
with
customers
and
clients
can
help
managers
supervise
and
train
staff.
That
might
be
as
useful
for
financial
advisors
as
for
call
center
workers,
but
tools
that
monitor
employee
productivity
need
to
be
used
with
empathy
to
avoid
concerns
about
workplace
surveillance.
User
feedback
and
product
reviews
are
helpful,
but
the
sheer
volume
can
be
overwhelming
and
nuggets
of
useful
information
might
be
buried
pages
deep.
Generative
AI
can
classify,
summarize,
and
categorize
responses
to
give
aggregate
feedback
that’s
easier
to
absorb.
In
the
long
term,
it’s
easy
to
imagine
a
personal
shopping
assistant
that
suggests
items
you’d
want
to
buy
and
answers
questions
about
them
rather
than
leaving
you
to
scroll
through
pages
of
reviews
and
comments.
But
again,
businesses
will
need
to
be
cautious
about
introducing
tools
that
might
surface
offensive
or
defamatory
opinions,
or
be
too
enthusiastic
about
filtering
out
negative
reactions.
Generative
AI
tools
can
read
and
summarize
long
documents,
and
use
the
information
to
draft
new
ones.
There
are
already
tools
like
Docugami
that
promise
to
extract
due
dates
and
deliverables
from
contracts,
and
international
law
firm
Allen
&
Overy
is
trialling
a
platform
to
help
with
contract
analysis
and
regulatory
compliance.
Generating
semi-structured
documents
like
MoUs,
contracts,
or
statements
of
work
may
speed
up
business
processes
and
help
you
standardize
some
business
terms
programmatically,
but
expect
to
need
a
lot
of
flexibility
and
oversight.
5.
Get
over
writer’s
block,
spruce
up
designs
You
don’t
have
to
turn
your
whole
writing
process
over
to
an
AI
just
to
get
help
with
brainstorming,
copywriting
and
creating
images
or
designs.
Office
365
and
Google
Docs
will
soon
allow
you
to
ask
generative
AI
to
create
documents,
emails
and
slideshows,
so
you’ll
want
to
have
policy
on
how
these
are
reviewed
for
accuracy
before
they’re
shared
with
anyone.
Again,
start
with
more
constrained
tasks
and
internal
uses
that
you
can
monitor.
Generative
AI
can
suggest
what
to
write
in
customer
outreach
emails,
thank
you
messages,
or
warnings
about
logistical
issues,
right
inside
your
email
or
in
a
CRM
like
Salesforce,
Zoho,
or
Dynamics
365,
either
as
part
of
the
platform
or
through
a
third-party
tool.
There’s
also
a
lot
of
interest
in
using
AI
for
marketing,
but
there
are
brand
risks
too.
Treat
these
options
only
as
a
way
to
get
started
and
not
the
final
version
before
clicking
send.
AI-generated
text
might
not
be
perfect
but
if
you
have
a
lot
of
blanks
to
fill,
it’s
likely
better
than
nothing.
Shopify
Magic,
for
instance,
can
take
basic
product
details
and
write
consistent,
SEO-tuned
product
descriptions
for
an
online
storefront,
and
once
you
have
something,
you
can
improve
on
it.
Also,
Reddit
and
LinkedIn
use
Azure
Vision
Services
to
create
captions
and
alternative
text
for
images
to
improve
accessibility
when
members
don’t
add
those
themselves.
If
you
have
a
large
video
library
for
training,
auto-generated
summaries
might
help
employees
make
the
most
of
their
time.
Image
generation
from
text
can
be
extremely
powerful,
and
tools
like
the
new
Microsoft
Designer
app
put
image
diffusion
models
in
the
hands
of
business
users
who
might
balk
at
using
a
Discord
server
to
access
Midjourney,
and
don’t
have
the
expertise
to
use
a
Stable
Diffusion
plugin
in
Photoshop.
But
AI-generated
images
are
also
controversial,
with
issues
ranging
from
deepfakes
and
uncanny
valley
effects,
to
the
source
of
training
data
and
the
ethics
of
using
works
of
known
artists
without
compensation.
Organizations
will
want
to
have
a
very
clear
policy
on
using
generated
images
to
avoid
the
more
obvious
pitfalls.
Finding
your
own
uses
As
you
can
see,
there
are
opportunities
to
benefit
from
generative
AI
in
everything
from
customer
support
and
retail,
to
logistics
and
legal
services—anywhere
you
want
a
curated
interaction
with
a
reliable
information
source.
To
use
it
responsibly,
start
with
natural
language
processing
use
cases
such
as
classification,
summarization
and
text
generation
for
non-customer-facing
scenarios
where
the
output
is
reviewed
by
humans
who
have
the
expertise
to
spot
and
correct
errors
and
false
information,
and
look
for
an
interface
that
makes
it
easy
and
natural
to
do
that
rather
than
it
just
accepting
suggestions.
It’ll
be
tempting
to
save
time
and
money
by
skipping
human
involvement,
but
the
damage
to
your
business
could
be
significant
if
what’s
generated
is
inaccurate,
irresponsible,
or
offensive.
Many
organisations
are
worried
about
leaking
data
into
the
models
that
might
help
competitors.
Google,
Microsoft
and
OpenAI
have
already
published
data
usage
policies
that
say
the
data
and
prompts
used
by
one
company
will
only
be
used
to
train
their
model,
not
the
core
model
supplied
to
every
customer.
But
you’ll
still
want
to
have
guidance
on
what
information
staff
can
copy
into
public
generative
AI
tools.
Vendors
also
say
that
users
own
the
input
and
output
of
the
models,
which
is
a
good
idea
in
theory,
but
may
not
reflect
the
complexity
of
copyright
and
plagiarism
concerns
with
generative
AI,
and
models
like
ChatGPT
don’t
include
citations,
so
you
don’t
know
if
the
text
they
return
is
correct
or
copied
from
someone
else.
Paraphrasing
isn’t
exactly
plagiarism,
but
misappropriating
an
original
idea
or
insight
from
someone
else
isn’t
a
good
look
for
any
business.
It’s
also
important
for
organizations
to
develop
AI
literacy
and
have
staff
become
familiar
with
using
and
evaluating
the
output
of
generative
AI.
Start
small
with
areas
that
aren’t
critical
and
learn
from
what
works.
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