WEBVTT

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You want to have the bottoms-up support

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and the eagerness to go learn,

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but you also need the top-down support

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to go do and have that creativity.

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Lenore, Bryan, welcome.

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Thanks so much for joining us.

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Bryan, we often assume that tech companies

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are leading the way when it comes to AI

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and agentic adoption.

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Is that true?

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What's the reality?

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So yes, I believe it's true.

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I do think outside of the big companies,

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we're actually starting to
see a number of startups

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and late-stage startups
actually be built agentic-first.

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So companies like Lovable,
Hospitable, have been led

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by agent-first operating
models and resource models.

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But I also think there's
cautionary tales that organizations

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that are starting agentic-first
are actually having

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to add headcount back, right?

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Which is not necessarily
disagreeing with agentic,

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it just means the best technology

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is when human meets technology.

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Lenore for you, Salesforce
has not only advised clients

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on how to adopt AI and agentic,

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but you've also been on
that journey yourself.

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What are the best lessons
you've learned from your own

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experience as well as advising clients?

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Yeah, I really think adoption
is critical for success

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and measuring that adoption.

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So as an example, in my
revenue organization,

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we have 96.4% of adoption of Slackbot.

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That's tremendous.

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There's no brute force that
would get those results.

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That's curiosity, that's organic.

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And that's actually real value coming from

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Slackbot as a solution.

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In terms of the promise of the technology,

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we've been talking about it for years,

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how far has it actually come?

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I mean, in terms of
meaningful real-world uses,

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where is the technology
still not quite working?

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I think it's working in most places

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that you have dedicated both leadership

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and investment with
resources that have learning

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and accountability associated to it.

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When you separate those things away,

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I think the benefit
ratio starts to go down.

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I think where organizations still need

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to accelerate their learning curve is

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that agentic still is
a plausibility engine,

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a reasoning engine that
needs humans to make

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that reasoning correct and accurate.

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So I think that learning
curve, and when I say learning

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and accountability, is
something organizations are

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fundamentally learning
slower on bigger companies.

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Smaller companies are much
more rapidly picking that up.

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Lenore, would you agree with that?

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I would agree with that.

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And just to echo Bryan,

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I think sales, service,
marketing, engineering, et cetera,

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we have use cases across all . . .

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I think, from Salesforce perspective,

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certainly sales and service,
we're seeing the highest amount

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of adoption and success.

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But I also think it's because
we've gone from tinkering

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to proof of concepts to
real live production,

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high-value use cases.

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And when you get one of those,
not many--start with one,

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that's when we're really
starting to see rapid success.

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And for companies outside the
tech sector who are looking

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to the tech sector to understand

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how your journeys have played out,

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what is the bit of advice
you would give them?

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Well, one, it is a journey.

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And so step by step, I don't think all

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of everyone's problems are
gonna be solved overnight,

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but you have to start somewhere.

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And again, Bryan said it very well,

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you want to have the bottoms-up support

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and the eagerness to go learn,

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but you also need the top-down support

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to go do and have that creativity.

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Bryan?

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So the Glean Institute came out with one

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of their studies that said

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agentic adoption isn't a tops-down remit,

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it's actually a peer-to-peer, right.

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Look left, look right,
how is it working for you?

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I think the marketing and the buzz

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has done such a good job
of getting the concept

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of using these agentic
tools out in the market

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that it's actually created
a burden for corporations

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to figure out how to meet feature parity.

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And I think that type of learning curve is

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where organizations have
to continue to run towards.

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And I don't see that being
a tech industry focus,

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I see that being across
every single industry.

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Bryan, Lenore, thanks so
much for joining us today.

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Thank you.
Thank you.