Play
Show Navigation
Show Transcript
00:00
Play
Seek 10 seconds backwards
Seek 10 seconds forward
00:00 / 32:23
Mute
Disable Captions
Settings
Picture in picture
Fullscreen
Search in video
You can search the video captions for specific words or phrases.
Popout transcript
Hide Transcript
Skip transcript
- Our next session is The
Future of Work and ai.
Please welcome to the
stage Alex Schwartzel,
managing Director Insights at
the Jobs for the Futures Lab.
Nancy Zu, Founder
and CEO of Moon Hub, The
World's First AI Recruiter,
Aashna Kirchner, CHRO Products, Workday.
And our moderator, Susanna
Dante, Executive Vice President
of Talent Acquisition at Salesforce.
Over to you, Susanna.
- Thank you. Thank you.
Hope everyone's doing well.
Thank you, panelist.
We're excited here to talk
to you about, of course, ai,
but bringing it to life
with the future of work.
And we've heard from some
of our panelists prior
to us talking about how I,
AI is gonna change our world
and how we're leaning into it.
And so we're excited to share
different perspectives of, of,
of how we're approaching it.
Alright, so the future is
here, according to a a,
a research from the Pew Research Poll.
We know that most Americans feel
that AI will have a huge impact in,
in jobs and in their jobs.
And unfortunately the feeling is negative
in the next two decades.
You know, the, the perception
of of what they feel is coming
is significantly impactful.
So from your perspective,
how should organizations
broach this topic?
How should they communicate to employees
who are apprehensive of leaning into ai?
I, I'd love to start with Aashna.
- Yeah, absolutely. Thank you.
And I, we actually did some
research earlier this year
as well that looked at the
trust gap between leaders
and managers and
organizations and employees.
And, and it was real, the
gap, the gap was real.
A good chunk of employees, many more
so the management believe that
have, have a decent amount
of distrust and don't believe
that their organizations are
taking their interests into
to heart when they're making changes and,
and introducing AI capabilities.
And what we've seen in,
in the organizations
who are really successful
in rolling that out
with their employees are,
they're starting with the why.
They're starting with what's
in it for me as an employee?
What business problem are
we solving on your behalf
to actually change the
perception from fear to, to one
of possibility.
And then they're also being
very, very transparent about
how they're rolling out ai,
how they're measuring it,
what the intended outcome is.
And that helps to diffuse the sort
of distrust in black box sense
that I think many employees
come, come to the table with.
- Yeah, yeah. Great.
- Nancy,
- The, the, the thought
that always resonates in my
mind when I think about AI today
is this idea that the future
needs better marketing.
And I think this is, you know,
it's really true, especially
with organizations in AI today.
You know, I consider myself
very much an AI optimist.
I do think there are risks we
should be thoughtful about,
but I do feel like there's a
part of this that has to do
with how do you market
internally the role of AI
and to create a narrative internally
that gets people to buy on.
I think one of the challenges
right now is we look at a lot
of AI products and the retention
and adoption is very low.
And I think a big part of
that is for many AI products,
there's a learning curve and
you need to prove to people
that it is worth learning
how to use these AI products
before you can get them
to actually use 'em.
And that I think really is about
how do you market the product internally
within the organization.
And then I think like
more from more broader
as an organization, I think
there's this narrative of
how do you help people
really think about the role
as becoming an AI manager.
Like I think in the future right now,
we have this opportunity for
everyone to really up skill
and become an AI manager.
And I think that can be a
really incredibly exciting role
for people to take on
culturally more broadly.
I think there's a whole
dialogue to be had about what
that means for people at scale.
And, you know, something,
a thought experiment I have
there is, if you look at people
with a lot of resources today, I think
virtually everything they have
access to will be possible
to give, have access to for most people
because of ai, private
tutors, private doctors,
private healthcare professionals.
And, and the list goes on.
And you can take that and, and apply
that in the same
organizational setting as well.
- Excellent. I have really appreciated
how often talent leaders,
technology leaders
who are talking about the potential
of AI are talking in terms
of human augmentation.
And, and we even saw
it in the video, right?
This is an opportunity
to, to take the jobs
that we all hold and make them better.
And so that messaging is
incredibly encouraging
and I think that the most important thing
that any organization can do
that's thinking about
adopting AI in this way is
to start from the premise of
how we can create really untold,
unparalleled value, both business value
and human value by using
AI to augment the work
that their human workers
are doing and then mean it
and act accordingly.
And that's, you know, that
can be easier said than done,
and we'll talk more in this
conversation about what that looks like.
But for us, I think it's about
not just changing the terms
of the debate, but making
sure that the conversation
around AI centers in large
part around this idea, which is
that AI needs to make
life better for humans.
That's its goal.
And if it's falling
short of that goal, then
that's when it's time for us to take steps
otherwise in whatever
organization we're within.
- Absolutely. I'm, the video
definitely resonated for me
'cause you know, Einstein's
giving you a little bit more
time back with your family.
And so I think when we think
about the future of work, it's
how do we create those use
that are gonna become very real for us?
So I I love that.
So Nancy, you are a founder of one
of the first AI recruiter
digital recruiters
that has come to come to fruition.
And, you know, going
through the hiring process,
this is something that we talk about a lot
and we know that this will be augmented.
What are some of the unique
advantages that you see
by implementing AI in
the recruiting process?
In the hiring process?
- Yeah, it's, it's such a great question.
I think the first thing I'll
say is I don't think it's
humans and ai, it's not a zero sum game.
I think a lot of people
think about this as, oh,
if they're AI agents,
then I'll lose my job.
And that I think can be
very fearful for people.
And I think we need to
be very thoughtful about
that conversation.
I think the exciting part about AI,
and especially in the recruiting
and talent acquisition
space for me today, is we,
for example, we release an
AI sorcerer that helps people,
that enables talent acquisition
professionals to work
with our AI sorcerere to, instead
of maybe finding a hundred
qualified candidates a week
and reaching out to them,
be able to do 10 x more
and see a thousand qualified candidates.
And I think the impact is, is twofold.
One is as a talent
professional, you are now able
to do more of what you love,
which is spend time working
with candidates and instead
of basically, you know,
doing a lot of keyword keyboard busy work.
But I think the more exciting impact is,
it actually changes the dynamic on the
candidate side as well.
Because you are now able
to, instead of, if you're a,
if you're a person and you have an hour
to find a hundred candidates, you will go
for the easiest thing, which is like,
if you wanna find a great
software engineer, you find people
with a keyword Google
and the keyword Stanford.
Right? And I think AI will make
it possible for us to push,
from what I call keyword
centric hiring into more really
human centric hiring, spend
the time to actually do
what it takes a person to
maybe take five minutes
to review a profile, look at
all of their online sources,
really read about their prior experiences.
And you can now do that
for every single person.
And so you're now unlocking
people who are UPS drivers
who took a coding bootcamp
and no one would've thought
that person would be qualified
or they would've just never
showed up if you had a human,
you know, looking through
resumes one by one
and trying to get the easy hits.
And now you can do that with ai.
And so I, I really think that
AI unlocks an opportunity
to make not just the talent
acquisition professional,
more super powered by having
a team of AI sourcers,
et cetera, that can work for them,
but also unlock a better
candidate experience over time.
- That's great. Are you finding that as,
as your digital agent, as your
recruiting agent is out there
talking to candidates,
are candidates receptive?
Like how, you know, oh wow, you found me.
- Yeah, I think one of the, I
think at the end of the day,
it's all about putting the
right opportunities in front
of people I think is so important.
Like, we've all had that email
where, well, I'll tell you
how I got into recruiting
in the first place.
One of my grad students
when I was back at Stanford
during my PhD came to me
after we submitted a paper
and he was showing me these
emails he was getting,
and one of those emails was like, Hey,
do you wanna become a salesperson at an
ultimate Frisbee store?
And the reason he got
this email was basically,
'cause he had played ultimate in,
in ultimate Frisbee in college
and, you know, he wasn't
interested in the job.
But after looking at that,
I realized like, wow,
so many people get responses like this.
And I think the reason why
I think maybe sometimes
recruiters get a bad rep,
if we're being honest, is
because we're not personalizing
that outreach enough
and we're not really
targeting the right people.
And I think AI can make it possible
to give a better experience on both ends.
- Yes. And being a
recruiter at heart, it's not
because we don't want to, but I think
because the, the system,
the way we have it designed
is, is challenging.
So there's prime opportunity there.
You know, as many organizations
are thinking about AI
and thinking about adopting,
and we've talked about
some of the challenges.
What would your recommendations
be for people trying to
break into some entry points
and how would they go about it?
- Yeah, I, I think a
couple, couple thoughts.
You know, one, they're probably
in it already, you know,
there was somebody
talking earlier about sort
of if you wake up in the morning
and you're already using
AI on your phone, right?
They're probably in it already.
But particularly as we think
about hr, it still has to
to center around those human
centered business problems.
And I, I, I really think
that speaking to many
of the customers that, that we serve,
the problems are still
the same core problems
that we've always had
in, in human resources.
But the tool set that
we now have available
to address those problems
is, is different.
So, you know, Nancy and,
and you talked about the
challenge of talent acquisition,
sourcing the right candidate
and surfacing it in the right way.
That's a key problem that
every HR organization has.
And so sort of centering an
entry point of AI in around
that problem is one of the primary ways
that we see customers really
starting to start their journey
or continuing their journey.
If, if they're already using tools,
take the employee experience
or employee engagement problem
of how do we better engage
with our, our employees
on a regular basis?
How do we listen and make sure
that we understand their concerns
and then demonstrate back
to them as a business
that we really care about those concerns.
That is a, an age old problem
in, in human resources
that now we can use AI to enter
and help solve that problem.
And again, many organizations
are already doing that
to gather, synthesize information
and then help organizations figure out how
to take the most targeted action.
And so you name it, I,
you know, the third one
that we commonly hear as sort of ripe
for AI disruption is routine processing.
Well, there's plenty of
routine processing in,
in human resources.
And so again, really centering
on as an HR organization
or as a business, like
what are those key key
problems that I need to solve?
And, and you know, as
we touched on earlier,
those are still the same ways
that you'll bring people along
and helping to solve the problem
because everybody recognizes the problem
that needs to be solved at hand.
- Yeah, absolutely.
And I think we've probably
seen lots of opportunity
for augmentation and just
help, you know, that's right.
In some of our processes.
- Yeah.
- And
- I do, and I do think that
a lot of the HR leaders
that we work with are desperate
to do more strategic work, right?
They, they wanna be out of the details.
And so I think anything
that helps target that kind
of routine, routine work
that can be automated,
people are actually really
excited to move to ai.
- Yeah, absolutely. Alex, hi.
Given J F's commitment to
equitable workforce development,
as we're talking about AI
and the solutions that we're,
we're incorporating into
our workforce, what are some
of the things that, or what
are some of the measures
that we can in play put in place
that are gonna create an inclusive
and beneficial environment?
- Yeah, it's such an important question
and throughout the course of today,
I think we've talked about
a lot of them that are true
for AI writ large
and especially true for solutions
that touch the workforce.
Starting in the very
first panel today about
how do you bring workers along?
And at the most recent panel,
not just as an afterthought,
but from the very beginning,
from the co-creation
and co-design stage,
'cause they're seeing
many of the pain points
that you all just described.
And they will have such
profound insight into
what it looks like to use an AI solution
or platform to automate
the parts of their job
that they would like to automate a way so
that they can spend more
time in strategic work.
So making sure that everybody
has a seat at the table from
the very beginning and then
throughout the process so
that it truly is nothing
about us without us is really
essential here just as it
is in any use case of ai.
And that includes hr for instance.
You know, we hear from time to
time that HR leaders aren't,
aren't necessarily asked
to sit at the table when
it comes to AI adoption.
And we think that's, that's
just essentially your people
leaders need to be in the room.
So that's really critical too.
But I think there are also some
of these more fundamental questions about
how the technology is designed
and developed from the very beginning
that we've also touched on today.
Whether that is the talent
pipeline of technologists
and leaders who are building
these tools in the first place,
making sure that they represent all of us
and can bring their
and our lived experiences into the tools
that we're designing in large part so
that we have less likelihood
of seeing adverse outcomes
that impact populations
that have historically
and systemically faced
barriers to advancement in ways
that we don't want to see.
There is a story that
many of you may have heard
that's been going around about
an early even pre generative
AI adoption of an algorithm as a, as part
of a hiring process where the
company was testing a tool
and said, we wanna use this tool
to understand our top performers,
what are their qualities
and characteristics so that
we can go find candidates
that are just like them,
completely laudable something that,
you know, is, is an
important use case for ai.
And the solution came back
and said there are two
key characteristics.
One is that they were named Jared
and the second is that
they played high school
lacrosse wrong.
Yikes answer, wrong answer.
So what, that's part of
why making sure that these,
these platforms are instituted in ways
that are thoughtful
from the very beginning
that are indexing for
opportunity and for equity
and that we're measuring
them in the right way.
That we're looking for specific outcomes
that point us in the direction
of inclusion rather than risking
leaving some folks behind.
- Yeah. And I think it's, you
know, it is a bit unchartered.
We had Paula, you know,
on our panel earlier
and certainly talking about
our ethical and humane use,
but it's also seeing those
signals as we're building
'cause we are building much of this.
Right. I'm curious, Nancy, when,
when you are talking to us,
like what are some of the
signals that we should be looking
for as we are thinking about AI
and embedding into our workforce
or in our jobs that like, you know,
we should be looking for?
- And Susanna, when you say signals,
do you mean signals in terms
of the candidate's profile
or signals in terms of
organizational readiness
- Or signals in the sense of,
you know, Alex's example of,
you know, Jared and the lacrosse.
Like how do we, how do
we catch those early?
'cause I think that that's something
that we're also really keen on.
- Yeah, so I think on the
catching the Jareds early, I like
that I'm gonna use that
code going forward.
The, I think a big part of it is you need
to make sure you have the right monitoring
and evaluation systems
for all your AI models.
I think at the end of the
day, you know, you've,
you've probably all heard
garbage in, garbage out.
It's all about the data
that you give your,
your, your models.
And I think there's the
same thing holds true here.
Now I do think, so one
is just having monitoring
and evaluation pipelines
that look on at your real time data.
That's a very technical solution.
The other piece is I think also
making sure you're bringing
in all the data that's relevant
to making the right decision.
I think historically we've
looked a lot at when you're
trying to hire someone what their title
and their prior experiences have been.
And that's great,
but if that's all you're
using to learn on things,
you're gonna find
people, you're just going
to mimic every historical hiring process
that's happened before, right?
Like you're gonna learn
how people get hired
to be software engineers at Salesforce
and replicate that going forward.
But there's an opportunity
to actually make
that process better.
And I think that comes down
to making sure you're giving
the right information.
Like maybe this person has
projects that they're not sharing
that could be relevant
and could move us more towards a
paradigm of skills based hiring.
That's an example. And I think
there, there are many examples of this.
Make sure you give the
AI the right models,
sorry, the right data.
Make sure you evaluate
and put the right guardrails
on your models themselves.
And there's a whole
sort of trusted stack of
how you do dynamic
rounding with your models
and all these other things.
And then the last piece
I will say is just being,
just being, having the
right organizational culture
to be thoughtful about these things
and realizing that, you
know, the first step is
to make sure your AI does better
or is more fair than a person is today.
And then the ultimate
step is getting to a place
where it is really
reflective of the end state
that you want, the world
that you wanna live in to look like.
- Awesome. And I should also preface this
by saying there's nothing
wrong with Jared and lacrosse.
We just, you know, we wanna
create opportunity for all.
For sure. So Nancy, you know,
it was really interesting
hearing you talk about all those
things 'cause I'm like, wow,
those are all like different new jobs
and like, you know,
like different functions
that we probably don't
have as we're building out
the roles of the future.
When you look ahead, you
know, I have five years here,
but I'm not gonna say five years,
I'm gonna say let's say two years.
Yeah. When you look at the roadmap ahead,
how do you see a generative
AI transforming talent
acquisition and hiring?
And I'll just even say
broadly Aashna, feel free
to jump in HR
because I do think it's, it's something
that's rapidly changing.
- Yeah, I can give a quick answer here
and then Asha, feel free to chime in.
I've told you this before, Susanna,
I really think right now is
such an exciting time to be
in the talent acquisition space.
We're more broadly in the HR space.
I think there's an opportunity
right now, right now for HR
to become HAR.
So instead of human
resources, really human
and agent resources
and really sort of thinking
about the HR organization
or the talent organization.
Not just from the perspective
of managing human resources in a company
but also at Gentech
resources inside the company.
So that's one thing I I
think is really exciting.
The second is, I think talent,
and Asha said this earlier
too, is going to be one
of the first places we
will see more widespread
agent adoption.
And because of that, what
that means is, I think
for anyone who's in talent
inside an organization,
you really are at the frontier
of pushing the company ahead
and thinking about how to
use AI and how to use agents.
And I think one of the biggest skills,
and we were just talking about this right
before this talk as well,
is agents, you know,
they don't just come out of the box
and you can use 'em like
it does take some training
and learning on how to work
with an agent effectively
and to know how to tune an
agent and set up an agent.
And I think those skill sets are things
that will become very
valuable in the future.
And so if you're in a talent
or HR organization,
you really have a chance right
now whether it's using an AI
source or AI recruiting coordinator
or whatever that is to learn
how to become an AI manager.
And I think that future is very exciting.
- Yeah. Couple couple things.
And I loved, I loved what you
were saying about sort of the,
the data that you need to take into play.
You know, talent
and talent acquisition
are being completely
revolutionized at the moment.
They're really at the forefront of
where AI is disrupting is disrupting hr.
And it's really twofold.
One, it's democratization of opportunity.
We've kind of touched on this,
but being able to find people
who never would've had the
opportunity to be considered
for those roles otherwise,
both in the talent acquisition
and the recruiting space,
but even internally in the
talent management space.
And I'll give you a specific example.
A a few years back we had
launched an internal marketplace
and a number of organizations
use internal marketplaces
to post stretch projects
or gigs that employees can participate in.
What we saw inadvertently was
that it opened up again a
democratization of opportunity
where historically special
projects is notoriously Who knows
who and who gets tapped on the shoulder
to be pulled into a special project.
And what we saw from being
able to use technology
to showcase these opportunities
and allow anyone in the
organization to see them
and raise their hand
was that you democratize
that opportunity again
with that visibility.
And the same is gonna be
true in talent acquisition
where you can take more data about people
but also use AI to understand data
and context around that data.
To know in skills based hiring
for example, that you know,
these skills over here
actually translate really well
to this set of adjacent skills
and to be able to fluidly
show people opportunities
that they may not have known existed.
And, and so the the sort
of ability to democratize
that opportunity both for internal and
and external candidates,
but then also for businesses
to be able to very clearly see
and measure ROI, right,
for talent in particular,
they can see the immediate
outcomes in terms of time to fill
and quality to hire quality of hire.
And so you can make the case
internally for AI as well.
It's, it's why this space is so ripe and
and really at that cutting edge.
- Yeah, love the conversation.
And you know agents, we've
definitely been spending a lot
of time talking about agents.
I think next year we'll probably
all have an agent with us.
It'll be us plus one.
- They might not even need
us on stage next year. Yeah,
- Yeah.
Potentially. I might have 10 behind me.
I might need a little more support here.
Alex, I'm curious, working across
so many different industries
and partnering in from a nonprofit
standpoint, what are some
of the promising initiatives
that you've seen take hold
that make you really excited about AI
coming into the workforce?
- Yeah, there are a lot
and I think there will be more every day.
And this trend of skills-based tiring,
which we were just talking about, is one
that's incredibly exciting for its promise
to open up access to opportunity.
We've been thinking a lot
also within JFF about the
potential to use AI to be able to codify
or credential people's lived experiences
or skills that you've learned
and developed even outside
of a traditional educational setting.
But one that might potentially
unlock a job opportunity
for you if your employer
is able to, if it's legible
to your employer, if
they're able to recognize it
as a developed skill.
So that idea of skills
codification to be able
to develop learning
and employability records
for instance is a really
exciting potential
for future use case of AI that we see
as broadening opportunity.
And the other one I think is just a theme
that's been an undercurrent
for today, which is the more
and more opportunities
to engage nonprofits
and other organizations
that are working directly
with populations that have
faced barriers to advancement
as again true co-creators in this space.
Both to identify the challenges that exist
but also to potentially
build new solutions.
I'll lift up one specific example,
which is a terrific organization
called Upwardly Global
that works with immigrant
and refugee populations
that's been testing AI use cases as sort
of skills translation,
but looking particularly at how
AI can do an even better job
of translating skills that are on resumes
or educational credentials,
for instance, for people trying
to work in the United States
coming in from overseas.
And often that that can be considered more
of an edge use case.
It's a little bit more
difficult for, you know,
an AI solution to really
fully understand that a skill
or an educational credential
that's expressed in one way,
in one country for instance,
actually means something specific here.
And so they've been working
with AI platforms to try to test
and improve upon their
capabilities to do that so
that the populations that
they serve, immigrants
and refugees and others are better able
to access job opportunities.
And there are examples like
that all over Salesforce is
working with a number of them
directly, which is really exciting.
- Yeah.
- So watch this space,
I think there's gonna be a lot more.
- Yeah, the hands-on
hands-on experience. Great.
And you know, for those of you
who are here with us today,
we have opportunity to build agents
and you know, get in there
and see what it takes.
Yeah, I love it.
So building on that, the
skills of the future, the,
the question of the hour.
What will we need to know?
How do we need to upskill ourselves?
Ashana do you have any,
do you, do you have the,
the golden key for us to know
what we all should be learning?
- No, no. Golden key.
But I think I'll give you
perhaps a slightly different
perspective than the one
that was shared in the,
in the last, in the last panel,
which is, I actually think
that AI will help make humans
go from kind of early career
to mid-career skill sets very fast.
It's gonna be the human skills
to really set apart those
people at mid-career to expert.
And I truly believe skills
like empathy and leadership
and you know, she talked
about managing ai,
you're gonna need
creativity in managing bots
and figuring out that extra mile
to really set, set yourself apart.
And so I can't underscore
enough the importance
of those human skills
that now are gonna be
more important than ever.
- Yeah, absolutely.
I myself tried to build an agent,
I told the team the panel earlier
and I'm like, I need some skill there.
But it, it was a great exercise
'cause you hands on and then That's right.
It actually, you know,
you start thinking about the
skills that you're gonna need.
Okay, Nancy, so you're, you know,
we have our AI recruiting agent out there
and the talent candidates are
out there in the ecosystem.
What can they do
that's gonna make them
more distinguishable,
more recognizable, be at the
right place at the right time
as we're using AI in our hiring process?
- Yeah, it's, it's a great question.
My, my Quibi take on this
would be, they should be able
to do less because AI
should do more for them.
But the, I think there's the
short term and the long term.
So the long term is a lot
about upskilling learning to,
you know, work with agents,
think about the skills
of the future, et cetera.
I think the short term is
more about going back to
what I said earlier, AI
gives us an opportunity
to look at people to take
a more human centric ones
and talent as opposed
to just keyword centric
or a couple of experiences
that we're all looking for in,
in people's resumes.
And so I think there, it's all
about being able to flesh out
and take the time
to actually talk about
your prior experiences,
those projects you've worked on.
Where traditionally I think
people just, I think a lot
of people have given up
'cause they think it's, they,
my resume's gonna go
through a keyword filter.
And so I've seen so many resumes
where it's like a whole page in white text
and it's just keywords, right?
And like I think that's not
gonna work in a year from now.
But I think the flip
side of that is instead
of spending a the time, write a whole page
of keywords in white text
so you can get through the,
the resume screeners.
You know, I think you should invest more
of the time really thinking about
how do you build the skills
and illustrate those skills in a,
in when you're looking for a job.
- Great. Awesome.
Alright, well we're just at time,
but I definitely wanted to
leave our viewers, our audience
with some key takeaways of what we can do
in the future world of, of
bringing AI into our workforce
and really, you know, from
a positive perspective,
how do we bring people along?
What are some of the key takeaways
or one key takeaway we
could leave everyone with?
Alex, I'd love to start with you.
- Yeah. I think it's about
finding transformative use cases
that will create business
value, create jobs,
and create opportunities for
people to use these tools
to build livelihoods.
We're seeing entrepreneurs doing this,
including student entrepreneurs.
We're seeing a real up swelling of this
that I think is the
key for us to focus on.
- Love it. I guess we'll go next.
So I think AI is not a zero sum game.
I think all of us know that
AI agents are going to happen
and they will be a part of the future.
And so I think right now the question is
how can we make sure we use
these ais in a responsible
manner and we, and we
educate people to be part of
that transition so that
everyone can be included in it.
And I, one, one thing
that I'm really excited about
in this whole AI revolution
that's happening is it gives us a chance
to fundamentally rethink
the entire labor market.
The jobs of the future will be different
from the jobs of today.
And one way you can think
about that is, you know,
you're no longer beholden to all
of the bias systems we've had
for the last 20 years
when it comes to hiring.
We can reinvent what that
system looks like. Right.
And I think that it's really
gonna level the playing field
and help us rebuild what the
future of work will look like.
- Yeah. I love it. I think
for me it just goes back
to human skills actually become more
and more important in this age.
And so doubling down not
only on how do we experiment
and learn how to work with
ai, but also continue to teach
and elevate those human skills
that will set people apart.
- Great. Yeah. Well thank you all.
Thank you for your time and
thank you for having us.
Resume AutoScroll
Link copied to clipboard
The Future of Work with AI
Learn how AI has the power to transform your workforce and the future of work.
Up Next
Questions about Salesforce+? We have answers.
What is Salesforce+?
Salesforce+ is the free streaming service for business. It’s a place to watch live events that help you grow your career and company, on your own time. Salesforce+ is produced by Salesforce, so you’ll find our company’s big events like Dreamforce here — as well as virtual learning made for your role and industry. Everything is free and unlimited.
What can I watch on Salesforce+?
You can watch all kinds of helpful, entertaining, and inspiring videos on Salesforce+. One thing our members love is our events. Whether you catch them live or on demand, Salesforce+ gives you a free front-row seat to our biggest global events, like Dreamforce, TDX, Tableau Conference, and Connections. These entertaining business shows star people in roles and industries just like yours, giving you fresh ideas for how to grow your company and do better work. The best part is, it’s all free.
Do I have to pay for Salesforce+?
Salesforce+ is free. Watch any Salesforce+ events or series at no cost. To enjoy unlimited free access to our entire library of videos, become a member by signing up for Salesforce+ with a Trailblazer account. To join us for virtual events like Dreamforce or Connections, you need to create your own Trailblazer account (it’s free!).
What is a Trailblazer account?
Your Trailblazer account gives you access to a unified profile across the Salesforce ecosystem and allows you to manage your settings and access across multiple Salesforce sites.
How do I sign up to register for live and on-demand events, like Dreamforce?
Sign up or log in to your Trailblazer account and complete a few additional details to watch Salesforce+ events live and on demand. We recommend preregistering for all events on Salesforce+ to get your own personalized journey, reminders, recommendations, and more.
Do I need to be a Salesforce customer to watch Salesforce+?
You don’t need to be a Salesforce customer to watch Salesforce+. Our virtual learning is open to everyone.
