What's Next in AI: a conversation on AI and the workplace
Summary
TLDRThe IBM chief HR officer discusses how IBM is using AI to augment human intelligence in the workforce. Key principles guide their AI efforts like having humans in the loop for decisions, transparency, and ethics. AI is handling repetitive tasks to allow more strategic work, improving experiences. AskHR chatbot handles 1.5 million conversations a year with high satisfaction. Automation also optimizes promotion cycles, saving significant time. The focus remains on the human workforce with care to build trust and comfort with AI. Experimentation and an ethical mindset are encouraged to start realizing AI benefits.
Takeaways
- 😊 IBM has over 250,000 employees participating in the AI revolution across various roles
- 💡 IBM sees AI as augmenting human intelligence rather than replacing it
- 🔒 IBM does not allow AI to be the sole decision maker in internal processes
- 🤝 IBM believes data and insights belong to the creator, not to the AI systems
- 👩💻 IBM is using AI chatbots to handle high volume basic HR queries, freeing up human resources for more complex questions
- 👍 IBM's AI-enabled HR assistant handles 1.5 million conversations per year with high customer satisfaction
- 🚀 IBM is achieving one grade level increase in average HR role complexity due to AI automation of basic queries
- ⚙️ Suggests starting small with AI automation and iterating based on feedback before scaling
- 🎯 AI can consolidate data from disparate sources to aid decision making in talent evaluation processes
- ✅ An IBM automation project saved 12,000 human hours in a single quarter for one promotions process
Q & A
What principles does IBM have around AI and the workforce?
-IBM has principles that AI is meant to augment human intelligence, AI is never the decision maker, and data and insights belong to the creator.
How can AI help create more jobs?
-AI can take over repetitive and administrative tasks, freeing up more time for employees to focus on innovation, creativity, and value-adding work.
What are some key things HR departments need to consider with AI?
-Key considerations are having principles around ethics, testing through experimentation, and implementing in small steps before scaling.
How is IBM using AI in HR processes?
-IBM is using AI chatbots and automation for basic HR queries and transactions as well as bringing in data to help with talent management decisions.
What benefits has IBM seen from implementing AI in HR?
-IBM has seen improvements in Net Promoter Score to +35, handling 1.5 million more HR conversations per year, and elevating HR professionals to more strategic work.
What advice does IBM have for starting with AI in HR?
-Start with either a digital assistant for basic queries or automation focused on talent life cycle processes that involve lots of data consolidation.
How does IBM ensure AI models are trustworthy?
-IBM focuses on principles of robustness, explainability, transparency on data sources, and evaluating fairness to build trust.
What is IBM's perspective on concerns about AI taking jobs?
-IBM believes AI will augment jobs by automating repetitive tasks, allowing more time for innovation and value-adding work.
How can companies reskill workers along with AI adoption?
-Provide opportunities to experiment with the technology over time to build skills through hands-on experience.
What is key for a successful AI implementation?
-Having a thoughtful, ethical approach focused on augmenting employees' abilities along with gradual experimentation and scaling.
Outlines
🎤 Introducing the discussion on AI, automation and the future of work at IBM
Ray Juan interviews Nicole Lamro, Chief HR Officer at IBM, about how IBM is handling AI and automation in relation to reskilling its over 250,000 employees. Key points - AI and automation will augment human intelligence rather than replace jobs, AI tools can make mundane work easier to allow employees time for more creative and fulfilling work.
😊 AI seen as a net job creator despite concerns
Nicole emphasizes that AI will be a net job creator by taking away repetitive tasks and allowing more time for innovation and creativity which is good for business. She agrees with Ray that AI also presents opportunities to fill talent gaps.
💡 Recommendations for successful AI implementation
Key recommendations include - being open to experimentation with AI while ensuring ethical safeguards, starting small then scaling what works, building advocate communities to provide user feedback, and integrating AI in bite-sized increments.
🤖 How AI is changing the HR function at IBM
AI chatbots are handling high volumes of routine employee queries and providing 24/7 self-service, freeing up HR staff capacity. This has improved employee experience with higher NPS scores. AI has also enabled automation of tedious HR processes like promotion cycles, saving significant time.
Mindmap
Keywords
💡AI automation
💡reskilling
💡AI ethics
💡augmentation
💡experimentation
💡personalization
💡complexity
💡automation
💡productivity
💡adoption
Highlights
IBM has over 250,000 employees participating in what they call the AI Revolution
Reskilling for AI is not a "big bang", it will happen gradually over time as people experiment with and get comfortable with the technology
Key AI principles at IBM: AI augments human intelligence, AI is never the decision maker, data and insights belong to the creator
Other important AI principles: robustness of models, explainability, transparency, fairness
AI is meant to take away repetitive and administrative parts of jobs to allow more time for innovation, creativity and value-add
AI tools can help find workers where population dynamics are shifting
Recommend starting small with AI experiments, use principles as guard rails, build internal advocates and get user feedback
AI allows optimizing where to use human talent, dealing with complexity by providing information, and enabling customization
AskHR AI assistant handles 1.5 million conversations/year with 35+ NPS score, freeing humans for more complex questions
Basic questions go to AI assistant, routing more complex ones to human experts faster than before
Professionals handling AI assistant queries have moved up a level, doing higher value work
An AI automation example in promotions process saved 12,000 hours in a quarter
Consider an AI assistant for basic queries or start automation in talent processes to merge data sources
Have to be open to experimentation with AI but balance it with principles and guard rails
Focus on humans first with ethical AI approach, but don't be afraid to get started
Transcripts
[Music]
hi everybody I'm Ray Juan with
constellation research and today I have
the pleasure to be here with nicool
lamro the chief HR officer of IBM hello
great to be with you Ray hey this is a
very interesting time we are at a point
where AI automation human labor are all
coming to a close of trying to figure
out what's next where do we go forward
and you're one of the most dynamic
companies going through this change so
let's start with the first question here
real quick what's going on with
reskilling AI automation like how are
you handling that and especially given
the number of employees remind everybody
how many people you have in the
organization so Ray this is a great
question because as you say there's a
lot going on in the technology space
around Ai and people tend to focus on
the technology aspect of it but there is
so much to focus on when you think about
reskilling how it's going to impact the
workforce here at IBM we have over 2
50,000 ibmers participating in what we
call the AI Revolution they may be
building products or helping clients
with it or even the internal staff
functions they're practicing using it
how can it re-engineer their processes I
think the important thing to think about
when you think about reskilling on the
AI space in general is it's not big bang
it's not going to just happen overnight
what you've got to think about is how do
you give people the opportunity to play
with the technology experiment with the
technology and experience it and then
over time you're going to see them
building skills no and it's crazy right
we're seeing like in every business
process in every organization there are
four things going on when do do
intelligent automation when do we
augment the machine with the human and
that's probably the most important job
like like why do you make an exception
right why did you break the rules why
did you do it differently right and
these systems are learning from us and
then of course when do you augment the
human with the machine so we can make
faster decisions and then every
organization is trying to make that
important decision when do you add the
human touch so I think this is really
important and you know again the
technology itself is pretty amazing but
thinking about when and where to use it
and when you don't use it I think are
equally important business decisions
here at IBM we have some really clear
principles about AI in the workforce AI
in the workplace the first one is is
that AI is meant to augment yes human
intellig and I know we've heard this
said before if I could go back in time I
would not call it artificial
intelligence I would call it augmented
intelligence and I think that is a key
tenant for us here the second thing that
I think is really important principle
for us at IBM is when we're using AI in
our internal processes AI is never a
decision maker no so you have so human
in the loop is Key Human in the loop is
really really key and I think that's an
important part we also believe that data
in in ins sites belong to the Creator so
again this is not about AI running wild
it is also not about us learning from
data that could be proprietary or your
competitive advantage and so as we think
about those processes those are some
principles that we have that are pretty
key here you that's really important
right you've got built-in AI ethics
you've got some really interesting
principles about working with machines
and Automation and Ai and that makes it
a very very safe environment and also a
very inclusive environment I I think
it's really true and you know you talked
about principles so we we talked about
some of these core tenants that we have
about AI not being a decisionmaker but
regardless of where you're using AI we
often think about some other principles
you have to have one is robustness the
robustness of the models this is what
makes them scalable this is what makes
them stand the test of time as the
models are working are they learning
from the right data sets yes
explainability mhm transparency yep
really really key do you know where the
data is coming from do you know what
it's doing so Lage veracity so important
we also think about things like um is it
fair so much is talked about in uh AI
around biases and how does that get
built in and so these principles for us
are really key as we're using it as
we're experimenting with it and also
building trust with our users that then
are at the end of this process oh I
really like this mindful approach and I
think it's really important that you
have a mindful approach now let's talk a
little bit about AI tools right and how
these tools are adding value to the
workforce because you know there A lot
of times we work on things that are so
boring so monotonous right you're like I
wish I had something to help me with
this or sometimes it's really hard to
find things and you're wishing like oh I
wish I had someone to help me find
something or give me institutional
knowledge and putting that into place oh
I'm so glad you asked the question this
way because as you know there's a lot of
negative maybe even doomsday perspective
out there about AI is it going to take
human jobs what's going to happen and as
I talked about I believe and we believe
at IBM that AI is actually going to be a
net job creator for exactly the reason
that you talked about what AI is going
to do is it is going to take away the
monotonous the administrative the rot
parts of people's jobs to allow more
time for Innovation for cre creativity
for the things that add business value
so this is about humans having more time
to do those things which is eventually
going to just be very good for business
yeah no I agree with you and and we're
definitely seeing the opportunities for
people to actually take the time to
think and things they wouldn't be able
to do before and we also have a lot of
cases where we're not finding enough
workers right or in countries where
population the population Dynamics are
shrinking as people age so a lot of new
opportunities been created there so
what's needed from Enterprises today to
ensure that they get the most from this
Ai and AI experience as we augment
intelligence in humanity the first thing
is you have to be prepared to experiment
so you have to be open to try things
there are going to be places where you
try to put AI in and it's a huge benefit
there going to be places where you try
to put AI in and it doesn't make that
much of a difference so we are in this
experimentation phase but the second
piece of this and that's really
important is you balance risk within
experimentation is you've got to have
these principles that we've talked about
what are the guard rails what do you
want the AI to do what don't you want it
to do particularly for HR leaders but
also for some other lines of Business
Leaders when we've thought about other
technology
revolutions they've been big platform
place they have been technology that
we've put into our processes that cost
several million dollars that might be a
two or threee implementation
and what's happening now with AI is I
think about it a little differently
rather than kind of buying the whole
house you can experiment lines of
business with small blocks and you can
try one thing at a time so this start
small see what works and scale it is one
of the power that the AI tools are now
giving you and I think that's also
extremely important no I love that uh
definitely check experimentation don't
stay in the background like test it out
um don't do it without principles
because that's really important because
you need that as your guard rails and do
it in bite-sized chunks yeah I think
it's really important and and then again
for line of Business Leaders don't
forget to get some Advocates try things
in pipelines again AI right now is
rarely going to be something that you
can just start using Enterprise ride
right away you're going to have to build
that momentum you're going to have to
have the models learn from each other
you're going to have to make sure that
you're putting it at the right Pro part
of the process
and so as you're doing that
experimentation build Advocates along
the journey with you get feedback from
your users about what is really
unlocking value or not and then scale so
how is AI then changing the Enterprise
in general oh from my perspective and I
think this is true for a lot lot of line
of business owners there are really
three things that are hitting us
particularly in the HR department one is
we're being asked to make sure that
we're making optimal investment ments
for every dollar that you spend are you
getting the best return Y the second
thing that's happening is the
environment that we're operating in is
getting more and more complex so you can
see how those first two things are
actually in conflict with one another
and then finally in the workplace
employees are expecting consumer grade
customizable personalized experim
experiences so all three of these things
are hitting us here in the the workplace
and just as you said AI is our ability
to unlock all of that how are we going
to make sure that we are using human
Talent where human Talent is needed the
most that's how you're optimizing AI is
also allowing human talent to deal with
very complex situations by giving you
information that you need real time and
the automation that you talked about is
exactly what is giving our employees
those custom customizable experiences
well then that means the HR function is
changing as well because of AI what are
you doing in that area we're doing a lot
in this area and you know just just a
couple examples as we think about it as
we are servicing our employees and
managers typically we would have done
this in very traditional ways we would
have assigned maybe HR business partners
to certain managers to meet with them
oneon-one or for our employees we would
have had call center support that they
would have to engage in with and what we
were hearing from our employees and
managers is is there an ability for us
to get 24 by7 support oh yeah again it's
hard to have you're a global company yes
exactly so 24/7 is 24/7 it is really 247
so how do you get that around the clock
service the other thing that we were
hearing from managers and employees were
things like there are some questions
that I actually don't need a human to
answer that you know just very quick
what's the vacation policy can I take
vacation very quick easy answers they
don't necessarily need a human to answer
that but there are times when they
needed an HR professional I'm about to
go out on maternity leave is everything
all set oh yeah I'd like to move to a
new job can somebody advise me on what
to do those types of questions required
human support but what was happening in
our organization was the very basic
question questions were taking a lot of
time of humans that they couldn't get to
the higher order questions and so we put
in an AI chat bot using Watson assistant
of course Watson X of
course and uh that is now the first part
of the interactions with all employees
and managers so that means all the
people that was that were answering
those questions the same monotonous Road
questions people were waiting for that
they're now being serviced and now
elevated to the next level of support
absolutely and so here's the way I would
describe it a couple things happened as
we did this so first of all that askhr
digital layer the AI enabled assistant
is handling 1.5 million conversations a
year which you probably couldn't have
done with the contact centers like that
before no way and it's real time they're
not waiting in the queue right so
they're getting that information real
time The
NPS for our digital layer has gone up to
plus 35 o that's really high it is very
high and in some processes it's as high
as plus 70 wow and it's because they can
get that information real time but as
you said they're also getting to the
experts faster so that digital layer is
now routing them to the tier 2 human
tier when they do have one of those
questions that we want handled by a
human to put this in context for those
listening here like that's a really high
net promoter score like really really
high especially and in HR that is really
high so absolutely and this is a journey
that we've been on for for a couple
years but it's not just about managers
and employees for the profession itself
we've also seen a ton of value as you
said dealing with a net promoter score
of plus 35 or plus 70 is a pretty good
work environment to be in but the other
thing that we're seeing is that for a
lot of these processes the average level
of an HR professional has gone one full
grade or ban in our world so they are
doing that higher value work um that is
bringing kind of more career progression
for them fun HR I guess we're moving the
nine box a little bit differently now
exactly yeah so no this is great so that
means all this stuff is coming in place
so how should other chros change their
approach given that there's all this
Technology Innovation in front of them
and AI is playing one of those parts of
the role the culture is also something
that you're talking about here and more
importantly as well changing the way
people work I think about kind of two
key entry points if I think about the HR
function one is this digital assistant I
think it can add a ton of value in an
organization for basic Q&A basic
transactions basic queries and it might
be how you then want to tier your
support model a second area of Entry if
you think that's not for you is actually
around automation which you referenced
before
every HR process has a lot of processes
that underpin the daytoday talent life
cycle yeah whether it's payroll or
Talent acquisition or benefits or
careers or
compensation and so thinking where you
might want to input to get better
leverage some forms of automation one
thing that we hear from HR professionals
a lot is that as they run Talent Cycles
maybe it's a promot cycle they have to
take data from a lot of different
sources to make sure that we're making
the best decisions it's a great place to
start with automation where automated
intelligent automation can actually
bring in data from different sources and
surface it up to H our professionals and
managers and you're right for every
organization or even industry it's going
to be different right that hire to
retire to Boomerang cycle is going to
play a different play absolutely we
recently put in Watson or orchestrate
our automation tool into a promotion
process here at IBM and in one promotion
process that typically would have taken
about one quarter we saved 12,000 hours
just by some very simple automation now
can we do that with space optimization
when you move
offices maybe that could be another use
case you can write the check and we'll
see what we can do no that's very very
cool well hey this has been a wonderful
discussion with you we're looking at the
intersection of all these AI
advancements automation but remember
it's all about being human and really
building that around the culture people
have to be comfortable with it you have
to think about this with humans first a
good ethical approach in terms of your
AI design but more importantly Don't Be
Afraid get started right absolutely just
get started Nico thank you very
[Music]
much
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