Qualified + 15 min

AI Workers for the Enterprise

Enterprise teams have to be able to adapt quickly or risk getting left behind in the AI Workforce Era. Learn how to strategically adopt revolutionary tech from VP of AI Product Marketing at Salesforce.

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0:00

>> Okay. So hi everyone and welcome to our session.

0:02

I'm super excited to be joined by Sanjana Perulekor,

0:05

the VP of AI Product Marketing at Salesforce.

0:08

Welcome, Sanjana. Thank you so much for having me.

0:12

Thank you for joining us.

0:13

So I'm excited to get your perspective because we've talked to

0:16

a wide variety of folks at today's AI workforce summit.

0:19

We've talked to folks from smaller companies,

0:21

from the VC community.

0:23

What I really want to dive in today is your perspective on how

0:26

enterprises can embrace AI workers in the AI workforce to

0:30

really help have a sound strategy with their implementation.

0:33

So we'd love to kind of zoom out and start at the beginning.

0:36

What are you seeing as far as enterprise companies trying to

0:39

adopt AI and AI workers right now?

0:42

>> Yeah, absolutely. I think the conversation right now on

0:46

the industry is very centered around agents and digital workers and AI workers.

0:52

For me, just zooming out a little bit,

0:55

the AI conversation has been going on for so many years,

0:58

so many, many years, and everybody has been trying to grapple with,

1:02

how do we get value out of AI?

1:05

The key thing that we're seeing with enterprises is that they don't know where

1:09

to start.

1:10

You might think, okay, large enterprises means using AI to solve big problems.

1:16

I want to optimize my entire supply chain or I want to make sure

1:22

that every single application we build is AI powered and conversational.

1:27

The reality is that every company just wants to start small.

1:32

Everything from using AI to create a personalized sales email,

1:36

or to help their service reps increase CSAP by delivering a more targeted

1:41

service experience,

1:42

or creating a chatbot, right?

1:45

Chatbots are something we interact with all the time,

1:47

but a chatbot that's more conversational that can really take action

1:51

automatically in the autonomous.

1:53

The use cases are actually quite so,

1:56

they're very similar to the use cases we've seen for years.

1:59

It's just that AI workers, agents, conversational AI,

2:04

these are just new tools in the toolkit to get started.

2:08

I think that's a great perspective,

2:10

and we do feel like there's this rush to be reactive right now.

2:14

What are you doing for AI workers?

2:15

How are you employing AI workers?

2:16

What's your strategy here?

2:18

For all the enterprise folks who are listening,

2:21

how can they avoid having those knee-jerk reactions

2:24

and building out that strategy that's really impactful in long lasting?

2:29

You talked about identifying the use cases.

2:31

Can you expand on that a little bit more?

2:34

Yeah, I think use cases can feel like such a buzzword, right?

2:40

Use cases are the name of the game, though.

2:42

You don't have a use case,

2:44

you have technology in search of a problem.

2:46

We see that all too often, especially in AI, right?

2:50

AI has been around for a really long time,

2:52

but why haven't people gotten value out of it?

2:54

It's because oftentimes,

2:56

they just want to implement a technology without knowing,

2:58

how am I going to measure the success?

3:00

How am I going to know that this is working?

3:02

I think when companies are thinking about use cases,

3:06

it's important to recognize sometimes the KPIs are the same.

3:11

If you look at the service space,

3:12

it's all about measuring case deflection and response time,

3:16

and case resolution time.

3:17

The KPIs are the same when you're implementing

3:20

an AI use case for service.

3:21

That's not different whether you're using a rules-based engine

3:24

or an AI worker,

3:26

but you've got to look at those KPIs with some consistency

3:29

as they relate to your use case,

3:31

otherwise you're just implementing things to implement them.

3:34

I think as I mentioned, these use cases can be everything

3:38

from as simple as summarizing a record.

3:41

I mean, our most widely adopted AI product right now

3:45

is Slack AI.

3:46

I use it every single day.

3:47

I use it to summarize channels.

3:49

I use it to keep up with everything that I do at work.

3:52

I use it to just keep up with my daily workflow.

3:56

And it's so important to have AI that is in a use case

3:59

that people are going to use every single day

4:01

that they relate to.

4:03

I think that's fantastic.

4:04

In one of our earlier sessions,

4:06

we were talking about learning to treat AI as a teammate

4:09

and not a tool.

4:10

So just something that's kind of riding alongside you

4:12

in your every day to help you be faster and skilled.

4:16

There's a big craze that's going on right now

4:19

and probably this sense of urgency to go

4:21

and just buy all of the AI technology

4:24

you can get your hands on.

4:25

We've talked with a lot of folks today

4:27

who feel the sense of urgency to have a strategy in place

4:29

for how they're implementing AI and AI workers

4:32

would love to get your perspective on to build or to buy.

4:37

Where should people look?

4:38

Or how should people approach kind of investing

4:41

in AI technology?

4:42

That's a great question.

4:44

It isn't all you can eat AI buffet right now.

4:47

Everything feels available, possible, purchasable.

4:52

And it just feels like a really confusing space.

4:56

Everything from the way we're seeing VC funding

4:59

to the way that companies are buying products,

5:02

where they're investing, it's super overwhelming.

5:06

And we get into this build versus buy concept a lot

5:09

because it can be hard to understand,

5:12

should I just sit back and pay for a bunch of compute power

5:16

and pay for a bunch of AI credits

5:19

to use some sort of large language model

5:21

and create my own use case?

5:23

Or do I buy a platform?

5:25

And I think from the Salesforce perspective,

5:27

we have always been customer company.

5:30

We've always been focused on connecting with customers

5:34

and enabling customers to do that

5:35

in new and interesting ways.

5:37

And so for us, AI is about inserting that technology

5:42

into those daily workflows.

5:44

I try to recreate that.

5:45

You try to recreate CRM.

5:47

You try to recreate a large platform.

5:51

Could you do it?

5:52

Sure.

5:54

Should you do it?

5:55

Probably not.

5:56

That is a waste of time and resources

5:58

when you could go faster with something

6:00

that your existing employees can use,

6:03

aka a low-code platform,

6:05

and something that already speaks

6:06

the language of your business.

6:08

Already knows the workflows that are important to you.

6:10

Already has access to the right data

6:12

because why recreate the wheel

6:14

when you can just use a platform

6:16

that does all of that AI goodness for you?

6:19

I'd love to expand on that a little bit

6:21

because in one of our earlier sessions,

6:23

we talked with Matt Millen,

6:24

he's the founder of Reggie,

6:26

and he talked about this concept of agent washing

6:29

to be aware of over the next year,

6:30

which is a lot of AI workers and agents that are out there

6:34

that are saying they can do all of these things,

6:36

but they might not have all the data,

6:38

all the infrastructure that they need

6:40

to be really successful.

6:42

Would love to hear your point of view

6:44

if a company, an enterprise company

6:46

is looking to make a longer-term investment in an AI worker,

6:49

what else should they be looking out for?

6:50

We talked about integration into your data.

6:52

I know trust is obviously always a P1 for Salesforce.

6:55

What are some of those things they should be thinking about?

6:58

Oh, there's so many elements.

7:00

And as a marketer myself,

7:02

the marketing is wild around agents.

7:05

I mean, it's just everywhere.

7:07

And I think there are some really key things to look out for.

7:11

I mean, number one, first and foremost,

7:13

above everything is trust.

7:15

These AI workers, we have no idea

7:18

if we're honest with ourselves

7:19

what the next five, 10, 20 years are gonna look like.

7:22

I mean, we couldn't have predicted the last two years

7:26

with the best AI technology,

7:28

helping us predict things in our business.

7:29

We could have never predicted what LLMs would do.

7:32

And so I think trust just has to be at the center

7:35

of your strategy and trust can take far from Sony.

7:39

I think for us, trust means a few different things.

7:41

It's not sharing our customer data,

7:44

making sure that people know that their data is not our product.

7:47

We don't use their data for any sort of creation

7:50

of our own products.

7:52

It's about keeping our customers' customer data safe.

7:56

So knowing what they can use,

7:57

the latest and greatest,

7:59

coolest cutting-edge AI technology without compromising.

8:03

And it's also in some of the stuff that people don't think about

8:06

as they're seeing these exciting AI innovations.

8:09

It's like testing AI solutions in a sandbox.

8:12

You gotta do that.

8:13

You can't deploy these things in a production

8:14

without testing them first.

8:16

Absolutely have to do that.

8:18

And then there's, of course, governance and regulatory

8:21

kind of measures included there.

8:22

And I think a quick plug from Salesforce

8:26

is one of the things that I've always found

8:28

really inspiring is that AI regulations continue to change.

8:31

We don't know what's gonna happen.

8:33

And so it's important that companies

8:35

are a part of that global conversation

8:37

of how will we audit and regulate these AI systems.

8:40

And Salesforce is very much a part of this

8:43

in our kind of ethical, humane use group at the company,

8:46

which is really cool.

8:47

And so trust is a big part.

8:49

I'd say the other part is making sure

8:52

that you're looking for a platform

8:54

that will scale with your business.

8:55

And what I mean by that is having people

8:58

that you don't have to hire,

9:00

but that already at your company,

9:01

that are already at your company

9:03

that can take advantage of these tools.

9:05

I mean, I remember back in the day,

9:07

my first job out of college, I was a Salesforce admin

9:09

and that was my day job.

9:12

Yeah, my day job was actually, I was a marketing analyst,

9:15

but I was at a teeny time startup

9:16

and being a Salesforce admin was a part of my job.

9:19

And I didn't know it at the time,

9:21

but I was building kind of enterprise-wide

9:24

workflow automation for our entire sales team.

9:27

And our sales team grew like crazy while I was there

9:29

and I was building dashboards and workflows and dew alerts

9:33

and it was small, but when I got to Salesforce

9:36

and I was like, well, I could have been a part of this

9:38

like trailblazer community of people

9:40

that are building out all of these amazing things

9:44

for their business with real ROI with low-code tools.

9:46

And so what inspires me is seeing all of these customers

9:51

diving in the co-pilot, diving in a prompt builder

9:54

and they are building AI.

9:56

They're data scientists, they're Salesforce admins

9:58

and Salesforce developers and they are able to kind of add

10:01

that feather in their cap.

10:02

They are a conversational designer.

10:04

They are a prompt engineer now.

10:07

And I think, you know, whether it's Salesforce platform

10:10

or another, it's important to kind of look at the team

10:13

you have and think about how can I adapt their skillset

10:16

to build on these AI platforms?

10:18

Because that's ROI right there, right?

10:22

And I think the last part, and I will use the most

10:24

foreign term of all, is change management.

10:27

I mean, I've been in AI for my entire career

10:31

and I have seen companies create the coolest stuff

10:36

and if you don't put people at the center, no one cares.

10:39

So I mean, I gave the example of Slack AI.

10:44

I mean, it is designed with the human in mind

10:46

everything from where the buttons are

10:48

to the way I use it every day.

10:51

And the same is true for our co-put.

10:52

I mean, we've really thought through

10:54

how are people gonna use this in their daily workflow

10:57

when they log into Salesforce,

10:58

when they use another application

11:00

and you've gotta bring your employees along for the ride.

11:03

Otherwise you'll build this kind of beautiful thing

11:06

that no one's used and then the ROI

11:08

is somewhere down the road that you can't see

11:09

because no one's using what you've built.

11:11

So there's the three things that really come to mind.

11:14

I think that's really insightful

11:15

and we talk about this all the time internally

11:17

is a year from now what AI technology is shelfware

11:21

and folks have invested in it,

11:23

but they're not using it, they're not seeing the impact.

11:25

And then what's the AI technology

11:26

that's gonna become a teammate

11:28

and it's gonna become part of their daily lives?

11:30

I'd love to get your point of view for your customers

11:33

that are successful with adopting

11:35

kind of this new way of thinking.

11:37

It's really hard to steer a big enterprise, right?

11:40

If you're a small company,

11:41

buy new software, get rid of software,

11:43

you can roll it out to your team quickly.

11:46

Do you have any advice for your customer champions

11:48

who are bullish on AI workers in this AI technology,

11:51

but they don't know how to advocate it for it

11:53

to their manager, to their company?

11:55

I think like anything you have to show people

11:58

what's in it for them.

12:01

That's my personal opinion.

12:02

And I think what I've always believed about AI

12:06

is that we are not at the stage

12:08

where we're just gonna go and replace the human with AI.

12:12

Like if we're all honest, like that's not,

12:14

that's not what's going on, right?

12:16

We are deploying AI in situations

12:19

where humans don't necessarily shine, right?

12:22

What does alerts like what model do?

12:24

It generates language, not logic,

12:27

from a corpus of data, right?

12:29

We're really good at creating logic.

12:31

We're really good at this,

12:32

talking back and forth, empathy,

12:34

like understanding each other.

12:36

But are we really great at digesting

12:38

large amounts of information

12:40

and summarizing that information?

12:41

No, take us some time, right?

12:43

Have to read all the books

12:44

and give my point of view and write it down.

12:47

Not really great at spotting anomalies

12:50

in a large corpus of data either,

12:52

but all of these kind of skills

12:56

are things that AI is really, really, really good at.

12:59

And so if you tell your employees,

13:01

hey, we're gonna take all of that grunt work

13:04

and busy work that frankly, you're not awesome at it.

13:07

And we're gonna make you 100x more awesome at your job

13:10

because we're gonna automate that for you AI.

13:13

That is the best, right?

13:16

There's something in it for them.

13:17

There's a clear use case

13:19

and there's a clear KPI

13:20

'cause it's already tied to the work they're doing.

13:23

So I think when we really focus on the here and now,

13:26

what AI is good at,

13:27

which is frankly the things that we're bad at,

13:30

it creates more of that trust, personally,

13:33

'cause they know it's gonna be good for them.

13:36

I love that.

13:36

And it's cool to think about the journey

13:38

'cause Salesforce has been ahead of the curve.

13:39

I remember when you guys brought Einstein to market

13:42

and you guys have been preaching this for a while,

13:43

but I feel like we're at this inflection point

13:45

where AI is becoming demystified

13:47

and we're realizing just how powerful it can make all of us

13:50

and we're seeing it really put into practice.

13:52

As we wrap up, we'd love to just ask one more question,

13:55

which is how is Salesforce thinking about bringing AI workers

13:58

and agents to market?

13:59

What's next for you guys?

14:00

Well, we have had some announcements lately

14:06

around the agent space.

14:08

We most recently kind of had our Einstein service agent

14:11

out there for folks to see from a marketing perspective.

14:15

Dreamforce is right around the corner

14:18

and you know Salesforce, there's AppStory,

14:21

there's a platform story, so wink, wink.

14:24

There'll be a lot to talk about at Dreamforce,

14:27

but I think when it comes down to

14:29

where we're going as a company,

14:31

our prominent strategy, it has been the same

14:34

since day one when it comes to AI.

14:36

It's AI for CRM and AI that is always gonna be tied

14:40

to the flow of work.

14:41

It's where we see the most value.

14:43

We're not trying to solve every problem

14:45

in the world with AI.

14:46

We want to solve our customer problems that they have.

14:49

With AI.

14:50

And so that's something you will not see a steer away from

14:53

if anything, agents are just another way

14:56

that our customers will get to achieve.

14:58

So I'm super excited for the future.

15:00

Well, awesome.

15:01

Well, this was such a great discussion

15:02

and I hope that everybody who's watching,

15:04

who's in the enterprise space,

15:05

can walk away feeling empowered,

15:07

like they can make an impact in starting

15:08

with those use cases and starting small,

15:10

even if you're big, I think is such a perfect mindset.

15:14

So Sanjana, thank you so much for joining us today

15:16

at AI Workforce Summit.

15:17

And I'm looking forward to the Dreamforce announcements

15:19

and we will see you soon.

15:21

Awesome. Thanks for having me.

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AI Workers for the Enterprise

0:00 - >> Okay. So hi everyone and welcome to our session. ::: 0:02 - I'm super excited to be joined by Sanjana Perulekor, ::: 0:05 - the VP of AI Product Marketing at Salesforce. ::: 0:08 - Welcome, Sanjana. Thank you so much for having me. ::: 0:12 - Thank you for joining us. ::: 0:13 - So I'm excited to get your perspective because we've talked to ::: 0:16 - a wide variety of folks at today's AI workforce summit. ::: 0:19 - We've talked to folks from smaller companies, ::: 0:21 - from the VC community. ::: 0:23 - What I really want to dive in today is your perspective on how ::: 0:26 - enterprises can embrace AI workers in the AI workforce to ::: 0:30 - really help have a sound strategy with their implementation. ::: 0:33 - So we'd love to kind of zoom out and start at the beginning. ::: 0:36 - What are you seeing as far as enterprise companies trying to ::: 0:39 - adopt AI and AI workers right now? ::: 0:42 - >> Yeah, absolutely. I think the conversation right now on ::: 0:46 - the industry is very centered around agents and digital workers and AI workers. ::: 0:52 - For me, just zooming out a little bit, ::: 0:55 - the AI conversation has been going on for so many years, ::: 0:58 - so many, many years, and everybody has been trying to grapple with, ::: 1:02 - how do we get value out of AI? ::: 1:05 - The key thing that we're seeing with enterprises is that they don't know where ::: 1:09 - to start. ::: 1:10 - You might think, okay, large enterprises means using AI to solve big problems. ::: 1:16 - I want to optimize my entire supply chain or I want to make sure ::: 1:22 - that every single application we build is AI powered and conversational. ::: 1:27 - The reality is that every company just wants to start small. ::: 1:32 - Everything from using AI to create a personalized sales email, ::: 1:36 - or to help their service reps increase CSAP by delivering a more targeted ::: 1:41 - service experience, ::: 1:42 - or creating a chatbot, right? ::: 1:45 - Chatbots are something we interact with all the time, ::: 1:47 - but a chatbot that's more conversational that can really take action ::: 1:51 - automatically in the autonomous. ::: 1:53 - The use cases are actually quite so, ::: 1:56 - they're very similar to the use cases we've seen for years. ::: 1:59 - It's just that AI workers, agents, conversational AI, ::: 2:04 - these are just new tools in the toolkit to get started. ::: 2:08 - I think that's a great perspective, ::: 2:10 - and we do feel like there's this rush to be reactive right now. ::: 2:14 - What are you doing for AI workers? ::: 2:15 - How are you employing AI workers? ::: 2:16 - What's your strategy here? ::: 2:18 - For all the enterprise folks who are listening, ::: 2:21 - how can they avoid having those knee-jerk reactions ::: 2:24 - and building out that strategy that's really impactful in long lasting? ::: 2:29 - You talked about identifying the use cases. ::: 2:31 - Can you expand on that a little bit more? ::: 2:34 - Yeah, I think use cases can feel like such a buzzword, right? ::: 2:40 - Use cases are the name of the game, though. ::: 2:42 - You don't have a use case, ::: 2:44 - you have technology in search of a problem. ::: 2:46 - We see that all too often, especially in AI, right? ::: 2:50 - AI has been around for a really long time, ::: 2:52 - but why haven't people gotten value out of it? ::: 2:54 - It's because oftentimes, ::: 2:56 - they just want to implement a technology without knowing, ::: 2:58 - how am I going to measure the success? ::: 3:00 - How am I going to know that this is working? ::: 3:02 - I think when companies are thinking about use cases, ::: 3:06 - it's important to recognize sometimes the KPIs are the same. ::: 3:11 - If you look at the service space, ::: 3:12 - it's all about measuring case deflection and response time, ::: 3:16 - and case resolution time. ::: 3:17 - The KPIs are the same when you're implementing ::: 3:20 - an AI use case for service. ::: 3:21 - That's not different whether you're using a rules-based engine ::: 3:24 - or an AI worker, ::: 3:26 - but you've got to look at those KPIs with some consistency ::: 3:29 - as they relate to your use case, ::: 3:31 - otherwise you're just implementing things to implement them. ::: 3:34 - I think as I mentioned, these use cases can be everything ::: 3:38 - from as simple as summarizing a record. ::: 3:41 - I mean, our most widely adopted AI product right now ::: 3:45 - is Slack AI. ::: 3:46 - I use it every single day. ::: 3:47 - I use it to summarize channels. ::: 3:49 - I use it to keep up with everything that I do at work. ::: 3:52 - I use it to just keep up with my daily workflow. ::: 3:56 - And it's so important to have AI that is in a use case ::: 3:59 - that people are going to use every single day ::: 4:01 - that they relate to. ::: 4:03 - I think that's fantastic. ::: 4:04 - In one of our earlier sessions, ::: 4:06 - we were talking about learning to treat AI as a teammate ::: 4:09 - and not a tool. ::: 4:10 - So just something that's kind of riding alongside you ::: 4:12 - in your every day to help you be faster and skilled. ::: 4:16 - There's a big craze that's going on right now ::: 4:19 - and probably this sense of urgency to go ::: 4:21 - and just buy all of the AI technology ::: 4:24 - you can get your hands on. ::: 4:25 - We've talked with a lot of folks today ::: 4:27 - who feel the sense of urgency to have a strategy in place ::: 4:29 - for how they're implementing AI and AI workers ::: 4:32 - would love to get your perspective on to build or to buy. ::: 4:37 - Where should people look? ::: 4:38 - Or how should people approach kind of investing ::: 4:41 - in AI technology? ::: 4:42 - That's a great question. ::: 4:44 - It isn't all you can eat AI buffet right now. ::: 4:47 - Everything feels available, possible, purchasable. ::: 4:52 - And it just feels like a really confusing space. ::: 4:56 - Everything from the way we're seeing VC funding ::: 4:59 - to the way that companies are buying products, ::: 5:02 - where they're investing, it's super overwhelming. ::: 5:06 - And we get into this build versus buy concept a lot ::: 5:09 - because it can be hard to understand, ::: 5:12 - should I just sit back and pay for a bunch of compute power ::: 5:16 - and pay for a bunch of AI credits ::: 5:19 - to use some sort of large language model ::: 5:21 - and create my own use case? ::: 5:23 - Or do I buy a platform? ::: 5:25 - And I think from the Salesforce perspective, ::: 5:27 - we have always been customer company. ::: 5:30 - We've always been focused on connecting with customers ::: 5:34 - and enabling customers to do that ::: 5:35 - in new and interesting ways. ::: 5:37 - And so for us, AI is about inserting that technology ::: 5:42 - into those daily workflows. ::: 5:44 - I try to recreate that. ::: 5:45 - You try to recreate CRM. ::: 5:47 - You try to recreate a large platform. ::: 5:51 - Could you do it? ::: 5:52 - Sure. ::: 5:54 - Should you do it? ::: 5:55 - Probably not. ::: 5:56 - That is a waste of time and resources ::: 5:58 - when you could go faster with something ::: 6:00 - that your existing employees can use, ::: 6:03 - aka a low-code platform, ::: 6:05 - and something that already speaks ::: 6:06 - the language of your business. ::: 6:08 - Already knows the workflows that are important to you. ::: 6:10 - Already has access to the right data ::: 6:12 - because why recreate the wheel ::: 6:14 - when you can just use a platform ::: 6:16 - that does all of that AI goodness for you? ::: 6:19 - I'd love to expand on that a little bit ::: 6:21 - because in one of our earlier sessions, ::: 6:23 - we talked with Matt Millen, ::: 6:24 - he's the founder of Reggie, ::: 6:26 - and he talked about this concept of agent washing ::: 6:29 - to be aware of over the next year, ::: 6:30 - which is a lot of AI workers and agents that are out there ::: 6:34 - that are saying they can do all of these things, ::: 6:36 - but they might not have all the data, ::: 6:38 - all the infrastructure that they need ::: 6:40 - to be really successful. ::: 6:42 - Would love to hear your point of view ::: 6:44 - if a company, an enterprise company ::: 6:46 - is looking to make a longer-term investment in an AI worker, ::: 6:49 - what else should they be looking out for? ::: 6:50 - We talked about integration into your data. ::: 6:52 - I know trust is obviously always a P1 for Salesforce. ::: 6:55 - What are some of those things they should be thinking about? ::: 6:58 - Oh, there's so many elements. ::: 7:00 - And as a marketer myself, ::: 7:02 - the marketing is wild around agents. ::: 7:05 - I mean, it's just everywhere. ::: 7:07 - And I think there are some really key things to look out for. ::: 7:11 - I mean, number one, first and foremost, ::: 7:13 - above everything is trust. ::: 7:15 - These AI workers, we have no idea ::: 7:18 - if we're honest with ourselves ::: 7:19 - what the next five, 10, 20 years are gonna look like. ::: 7:22 - I mean, we couldn't have predicted the last two years ::: 7:26 - with the best AI technology, ::: 7:28 - helping us predict things in our business. ::: 7:29 - We could have never predicted what LLMs would do. ::: 7:32 - And so I think trust just has to be at the center ::: 7:35 - of your strategy and trust can take far from Sony. ::: 7:39 - I think for us, trust means a few different things. ::: 7:41 - It's not sharing our customer data, ::: 7:44 - making sure that people know that their data is not our product. ::: 7:47 - We don't use their data for any sort of creation ::: 7:50 - of our own products. ::: 7:52 - It's about keeping our customers' customer data safe. ::: 7:56 - So knowing what they can use, ::: 7:57 - the latest and greatest, ::: 7:59 - coolest cutting-edge AI technology without compromising. ::: 8:03 - And it's also in some of the stuff that people don't think about ::: 8:06 - as they're seeing these exciting AI innovations. ::: 8:09 - It's like testing AI solutions in a sandbox. ::: 8:12 - You gotta do that. ::: 8:13 - You can't deploy these things in a production ::: 8:14 - without testing them first. ::: 8:16 - Absolutely have to do that. ::: 8:18 - And then there's, of course, governance and regulatory ::: 8:21 - kind of measures included there. ::: 8:22 - And I think a quick plug from Salesforce ::: 8:26 - is one of the things that I've always found ::: 8:28 - really inspiring is that AI regulations continue to change. ::: 8:31 - We don't know what's gonna happen. ::: 8:33 - And so it's important that companies ::: 8:35 - are a part of that global conversation ::: 8:37 - of how will we audit and regulate these AI systems. ::: 8:40 - And Salesforce is very much a part of this ::: 8:43 - in our kind of ethical, humane use group at the company, ::: 8:46 - which is really cool. ::: 8:47 - And so trust is a big part. ::: 8:49 - I'd say the other part is making sure ::: 8:52 - that you're looking for a platform ::: 8:54 - that will scale with your business. ::: 8:55 - And what I mean by that is having people ::: 8:58 - that you don't have to hire, ::: 9:00 - but that already at your company, ::: 9:01 - that are already at your company ::: 9:03 - that can take advantage of these tools. ::: 9:05 - I mean, I remember back in the day, ::: 9:07 - my first job out of college, I was a Salesforce admin ::: 9:09 - and that was my day job. ::: 9:12 - Yeah, my day job was actually, I was a marketing analyst, ::: 9:15 - but I was at a teeny time startup ::: 9:16 - and being a Salesforce admin was a part of my job. ::: 9:19 - And I didn't know it at the time, ::: 9:21 - but I was building kind of enterprise-wide ::: 9:24 - workflow automation for our entire sales team. ::: 9:27 - And our sales team grew like crazy while I was there ::: 9:29 - and I was building dashboards and workflows and dew alerts ::: 9:33 - and it was small, but when I got to Salesforce ::: 9:36 - and I was like, well, I could have been a part of this ::: 9:38 - like trailblazer community of people ::: 9:40 - that are building out all of these amazing things ::: 9:44 - for their business with real ROI with low-code tools. ::: 9:46 - And so what inspires me is seeing all of these customers ::: 9:51 - diving in the co-pilot, diving in a prompt builder ::: 9:54 - and they are building AI. ::: 9:56 - They're data scientists, they're Salesforce admins ::: 9:58 - and Salesforce developers and they are able to kind of add ::: 10:01 - that feather in their cap. ::: 10:02 - They are a conversational designer. ::: 10:04 - They are a prompt engineer now. ::: 10:07 - And I think, you know, whether it's Salesforce platform ::: 10:10 - or another, it's important to kind of look at the team ::: 10:13 - you have and think about how can I adapt their skillset ::: 10:16 - to build on these AI platforms? ::: 10:18 - Because that's ROI right there, right? ::: 10:22 - And I think the last part, and I will use the most ::: 10:24 - foreign term of all, is change management. ::: 10:27 - I mean, I've been in AI for my entire career ::: 10:31 - and I have seen companies create the coolest stuff ::: 10:36 - and if you don't put people at the center, no one cares. ::: 10:39 - So I mean, I gave the example of Slack AI. ::: 10:44 - I mean, it is designed with the human in mind ::: 10:46 - everything from where the buttons are ::: 10:48 - to the way I use it every day. ::: 10:51 - And the same is true for our co-put. ::: 10:52 - I mean, we've really thought through ::: 10:54 - how are people gonna use this in their daily workflow ::: 10:57 - when they log into Salesforce, ::: 10:58 - when they use another application ::: 11:00 - and you've gotta bring your employees along for the ride. ::: 11:03 - Otherwise you'll build this kind of beautiful thing ::: 11:06 - that no one's used and then the ROI ::: 11:08 - is somewhere down the road that you can't see ::: 11:09 - because no one's using what you've built. ::: 11:11 - So there's the three things that really come to mind. ::: 11:14 - I think that's really insightful ::: 11:15 - and we talk about this all the time internally ::: 11:17 - is a year from now what AI technology is shelfware ::: 11:21 - and folks have invested in it, ::: 11:23 - but they're not using it, they're not seeing the impact. ::: 11:25 - And then what's the AI technology ::: 11:26 - that's gonna become a teammate ::: 11:28 - and it's gonna become part of their daily lives? ::: 11:30 - I'd love to get your point of view for your customers ::: 11:33 - that are successful with adopting ::: 11:35 - kind of this new way of thinking. ::: 11:37 - It's really hard to steer a big enterprise, right? ::: 11:40 - If you're a small company, ::: 11:41 - buy new software, get rid of software, ::: 11:43 - you can roll it out to your team quickly. ::: 11:46 - Do you have any advice for your customer champions ::: 11:48 - who are bullish on AI workers in this AI technology, ::: 11:51 - but they don't know how to advocate it for it ::: 11:53 - to their manager, to their company? ::: 11:55 - I think like anything you have to show people ::: 11:58 - what's in it for them. ::: 12:01 - That's my personal opinion. ::: 12:02 - And I think what I've always believed about AI ::: 12:06 - is that we are not at the stage ::: 12:08 - where we're just gonna go and replace the human with AI. ::: 12:12 - Like if we're all honest, like that's not, ::: 12:14 - that's not what's going on, right? ::: 12:16 - We are deploying AI in situations ::: 12:19 - where humans don't necessarily shine, right? ::: 12:22 - What does alerts like what model do? ::: 12:24 - It generates language, not logic, ::: 12:27 - from a corpus of data, right? ::: 12:29 - We're really good at creating logic. ::: 12:31 - We're really good at this, ::: 12:32 - talking back and forth, empathy, ::: 12:34 - like understanding each other. ::: 12:36 - But are we really great at digesting ::: 12:38 - large amounts of information ::: 12:40 - and summarizing that information? ::: 12:41 - No, take us some time, right? ::: 12:43 - Have to read all the books ::: 12:44 - and give my point of view and write it down. ::: 12:47 - Not really great at spotting anomalies ::: 12:50 - in a large corpus of data either, ::: 12:52 - but all of these kind of skills ::: 12:56 - are things that AI is really, really, really good at. ::: 12:59 - And so if you tell your employees, ::: 13:01 - hey, we're gonna take all of that grunt work ::: 13:04 - and busy work that frankly, you're not awesome at it. ::: 13:07 - And we're gonna make you 100x more awesome at your job ::: 13:10 - because we're gonna automate that for you AI. ::: 13:13 - That is the best, right? ::: 13:16 - There's something in it for them. ::: 13:17 - There's a clear use case ::: 13:19 - and there's a clear KPI ::: 13:20 - 'cause it's already tied to the work they're doing. ::: 13:23 - So I think when we really focus on the here and now, ::: 13:26 - what AI is good at, ::: 13:27 - which is frankly the things that we're bad at, ::: 13:30 - it creates more of that trust, personally, ::: 13:33 - 'cause they know it's gonna be good for them. ::: 13:36 - I love that. ::: 13:36 - And it's cool to think about the journey ::: 13:38 - 'cause Salesforce has been ahead of the curve. ::: 13:39 - I remember when you guys brought Einstein to market ::: 13:42 - and you guys have been preaching this for a while, ::: 13:43 - but I feel like we're at this inflection point ::: 13:45 - where AI is becoming demystified ::: 13:47 - and we're realizing just how powerful it can make all of us ::: 13:50 - and we're seeing it really put into practice. ::: 13:52 - As we wrap up, we'd love to just ask one more question, ::: 13:55 - which is how is Salesforce thinking about bringing AI workers ::: 13:58 - and agents to market? ::: 13:59 - What's next for you guys? ::: 14:00 - Well, we have had some announcements lately ::: 14:06 - around the agent space. ::: 14:08 - We most recently kind of had our Einstein service agent ::: 14:11 - out there for folks to see from a marketing perspective. ::: 14:15 - Dreamforce is right around the corner ::: 14:18 - and you know Salesforce, there's AppStory, ::: 14:21 - there's a platform story, so wink, wink. ::: 14:24 - There'll be a lot to talk about at Dreamforce, ::: 14:27 - but I think when it comes down to ::: 14:29 - where we're going as a company, ::: 14:31 - our prominent strategy, it has been the same ::: 14:34 - since day one when it comes to AI. ::: 14:36 - It's AI for CRM and AI that is always gonna be tied ::: 14:40 - to the flow of work. ::: 14:41 - It's where we see the most value. ::: 14:43 - We're not trying to solve every problem ::: 14:45 - in the world with AI. ::: 14:46 - We want to solve our customer problems that they have. ::: 14:49 - With AI. ::: 14:50 - And so that's something you will not see a steer away from ::: 14:53 - if anything, agents are just another way ::: 14:56 - that our customers will get to achieve. ::: 14:58 - So I'm super excited for the future. ::: 15:00 - Well, awesome. ::: 15:01 - Well, this was such a great discussion ::: 15:02 - and I hope that everybody who's watching, ::: 15:04 - who's in the enterprise space, ::: 15:05 - can walk away feeling empowered, ::: 15:07 - like they can make an impact in starting ::: 15:08 - with those use cases and starting small, ::: 15:10 - even if you're big, I think is such a perfect mindset. ::: 15:14 - So Sanjana, thank you so much for joining us today ::: 15:16 - at AI Workforce Summit. ::: 15:17 - And I'm looking forward to the Dreamforce announcements ::: 15:19 - and we will see you soon. ::: 15:21 - Awesome. Thanks for having me.