คำบรรยาย (82)
0:00I think one of the mistakes many
0:02organizations are going to make is to
0:04focus too much on the technology and not
0:06enough on the people. So, it's actually
0:08comparatively pretty easy to go out and
0:09[music] get new AI tools for your
0:11workforce. What's really hard is helping
0:13people understand how to use those tools
0:15and helping them feel [music] supported
0:22Hi, [music] I'm Hannah Calhoun and I'm
0:24vice president for AI at Indeed. The one
0:26thing that is constant in this space
0:28right [music] now is that everything is
0:30changing. We are imagining a future
0:32where AI is one of many [music] tools
0:34that our people use to get their jobs
0:36done every day. We decided really
0:38[music] early that we wanted to have a
0:41central transformation office for doing
0:43this work. We have taken a very
0:46functionspecific [music] approach where
0:48we go into different departments to
0:49sales to marketing to finance and we say
0:51what are your big problems? What are the
0:53metrics that matter? [music] or the
0:55places people feel stuck. We sort of
0:56look at those and we say, "Okay, like
0:57which ones do we think AI could be a
0:59help for?" And so I think what we're
1:01going to see in tons of different places
1:02all across the [music] company is that
1:05the AI can take some of these more road
1:07or routine tasks and do sort of like the
1:09pre-work, but the human with their full
1:12context, their decision-m, their
1:13understanding of the organizational
1:15dynamics, the problems to be solved is
1:17then going to take that input and be
1:18able to make the decisions and take the
1:20actions that are really going to have an
1:21impact on the [music] business. Every
1:22week I get an email, the new next best
1:25coding assistant for software engineers,
1:27right? We would drive our engineering
1:28team crazy if every four weeks we said,
1:30"Hey, new coding assistant, time to
1:32learn a new system." The way we're
1:34trying to get around that is by being
1:36really intentional to build tools and
1:39services that we can put together, like
1:41building blocks. And so the goal is then
1:43if we need to swap one of the blocks out
1:45[music] that we can take that block out
1:46and replace it with another service that
1:48does the same thing without having to
1:50deconstruct all of the [music] rest of
1:51the pieces. That notion about everyone
1:53owning this journey of it being on AI. I
1:56think it also just means like everybody
1:57gets to own more of the experience
1:59[music] of delivering the product,
2:00delivering the service. I am optimistic
2:02about the future of work. [music]
2:04There's a really exciting opportunity
2:05ahead for us to take parts of people's
2:08jobs that they maybe don't like doing as
2:10much or that fill [music] up a lot of
2:11time without adding a lot of value and
2:13give those to the AI. But I think we're
2:15going to see some blurring between the
2:18lines of what people in different roles
2:19can do. [music] You know, you're the
2:21people that know the client best. You're
2:22the people who spend the most time in
2:24the product every day. We're going to
2:26let you help us make the product better
2:28and own making the product better.
2:29[music] I hope that's going to end up
2:30being really exciting and empowering for
