WEBVTT

aba13217-f9a7-4b7b-adbb-12eb34f133da-0
00:00:00.560 --> 00:00:02.298
Yeah,
there's a lot of talk about this idea

aba13217-f9a7-4b7b-adbb-12eb34f133da-1
00:00:02.298 --> 00:00:03.800
that we're going to have AI employees.

61750bdc-29df-495f-9612-ac94ed1fffc0-0
00:00:04.160 --> 00:00:05.280
I think it's a bad idea.

81b9f7e4-9929-4e25-8c25-711b45b455fd-0
00:00:05.680 --> 00:00:07.480
I don't think that's the right way to
think about AI.

9d8d3bb6-b0f1-4ed9-b375-a688ff8ca907-0
00:00:08.160 --> 00:00:10.440
Matt, Lucas,
thank you so much for being here.

71ebc1c4-9e8e-43f6-ae69-46ded8b33fcc-0
00:00:10.800 --> 00:00:12.360
Matt, this first question is for you.

63b506d2-292b-476b-b109-860669b799b8-0
00:00:12.440 --> 00:00:16.975
There's so much conversation around AI,
but are organizations really unlocking

63b506d2-292b-476b-b109-860669b799b8-1
00:00:16.975 --> 00:00:17.320
value?

d631547a-6e56-471d-9f0e-664670de374d-0
00:00:17.640 --> 00:00:18.760
Yeah, it's a great question.

251b9432-19bc-4a4c-8603-d3a1b16fe0e7-0
00:00:19.200 --> 00:00:22.576
So I've talked to a lot of executive
teams and everybody's doing a lot of

251b9432-19bc-4a4c-8603-d3a1b16fe0e7-1
00:00:22.576 --> 00:00:25.360
experimentation, but then they're saying,
where's the value?

14c4de52-bcc3-4ae3-96d7-9922562abb5f-0
00:00:25.360 --> 00:00:27.920
Am I actually seeing it coming to the
bottom line?

2142eae3-c838-4dd2-842b-abc807359b06-0
00:00:28.960 --> 00:00:30.040
The answer is yes.

3479c79b-7c06-4854-aa60-f783dc75680a-0
00:00:30.080 --> 00:00:34.200
There is a lot of value being created,
but we're still very early.

e4d64cb0-60d6-492f-a1e7-1548b19b8b87-0
00:00:34.200 --> 00:00:38.467
And so organizations need to move from
small experiments to really focusing on

e4d64cb0-60d6-492f-a1e7-1548b19b8b87-1
00:00:38.467 --> 00:00:42.087
what are big initiatives,
what are the few big rocks that they can

e4d64cb0-60d6-492f-a1e7-1548b19b8b87-2
00:00:42.087 --> 00:00:44.680
focus on that are really going to create
value.

ee92e19d-5dc1-474a-9f4f-1166fc1e13c6-0
00:00:44.880 --> 00:00:47.834
And we're absolutely seeing that value,
and it's only going to increase over the

ee92e19d-5dc1-474a-9f4f-1166fc1e13c6-1
00:00:47.834 --> 00:00:48.600
next couple of years.

d57eac04-4636-4aad-ba35-daa405175a85-0
00:00:49.200 --> 00:00:51.952
Lucas,
what is the role of leadership when

d57eac04-4636-4aad-ba35-daa405175a85-1
00:00:51.952 --> 00:00:52.720
adopting AI?

645a5fc8-b860-4ce3-8d5c-e68c052adf4a-0
00:00:53.800 --> 00:00:55.160
Yeah, it all starts on the top.

a3654855-a46b-46f6-8ec8-8e8902b3260f-0
00:00:55.160 --> 00:00:59.880
Company leadership has to establish clear
principles around when to use AI and what

a3654855-a46b-46f6-8ec8-8e8902b3260f-1
00:00:59.880 --> 00:01:01.960
to use it for and when to not use AI.

f7f686f1-0049-4dd5-9984-7075876ac190-0
00:01:02.120 --> 00:01:05.300
And then also think about guardrails,
what types of data should go into AI

f7f686f1-0049-4dd5-9984-7075876ac190-1
00:01:05.300 --> 00:01:07.760
tools and what types of data should be
off limits for AI.

157ab4c5-0751-418b-a067-007e6b9c7f91-0
00:01:08.120 --> 00:01:11.170
And being really clear about what those
guidelines are, what those principles are,

157ab4c5-0751-418b-a067-007e6b9c7f91-1
00:01:11.170 --> 00:01:12.200
and what the guardrails are.

46122d9b-1752-4e42-a83b-36d4ed93c128-0
00:01:12.480 --> 00:01:15.653
And then also leading by example and
using AI themselves and being really

46122d9b-1752-4e42-a83b-36d4ed93c128-1
00:01:15.653 --> 00:01:16.640
transparent about that.

655414ad-5e56-496e-8fd4-931790878ee1-0
00:01:16.640 --> 00:01:20.261
If company leaderships are using AI tools
and then sharing that with a company,

655414ad-5e56-496e-8fd4-931790878ee1-1
00:01:20.261 --> 00:01:23.656
that'll help bring everybody else,
everybody else at the company along for

655414ad-5e56-496e-8fd4-931790878ee1-2
00:01:23.656 --> 00:01:24.200
the journey.

8979a5c8-4b27-4cb0-9d1b-3b611dc3cc13-0
00:01:24.960 --> 00:01:28.177
Matt,
what is your view or take away when it

8979a5c8-4b27-4cb0-9d1b-3b611dc3cc13-1
00:01:28.177 --> 00:01:30.680
comes to viewing AI as a colleague?

dacb24d5-54dd-4acd-a534-e0d01b371ee5-0
00:01:31.840 --> 00:01:33.557
Yeah,
there's a lot of talk about this idea

dacb24d5-54dd-4acd-a534-e0d01b371ee5-1
00:01:33.557 --> 00:01:35.040
that we're going to have AI employees.

08124ad6-3b4b-47a7-8d2a-e7bd5ef85662-0
00:01:35.440 --> 00:01:36.560
I think it's a bad idea.

699435fe-9d69-46fc-b41c-830d1d30dc8f-0
00:01:36.920 --> 00:01:38.760
I don't think that's the right way to
think about AI.

c6ba6e93-ec9f-4355-8256-387c79df6211-0
00:01:39.720 --> 00:01:41.680
There's so much context in work.

4755e4af-506b-489c-8bad-7f9b5a4cb0b0-0
00:01:42.360 --> 00:01:45.280
As humans, you know,
we understand what needs to be done.

fc627e98-e0ed-4707-be87-6c8063a80ff4-0
00:01:45.280 --> 00:01:47.120
We have relationships with our colleagues.

93f85c65-27f1-4eaa-a435-1d42edefef0e-0
00:01:47.120 --> 00:01:48.360
You know, we have political capital.

3716be14-d06a-4f68-9f25-2eb65db25e82-0
00:01:48.640 --> 00:01:49.560
AI doesn't have that.

4f6a74b8-4bea-4561-acb4-08268e350616-0
00:01:49.840 --> 00:01:51.840
So AI is not going to be an employee.

df5d2dd9-4583-4d29-8977-688546bb4240-0
00:01:51.840 --> 00:01:53.480
It's not going to be a person on your
team.

82c98b86-842d-45f2-85aa-99b923916475-0
00:01:53.680 --> 00:01:55.680
But it's an incredibly powerful tool.

0855f932-a5b4-4715-879f-18114ccb88ae-0
00:01:55.680 --> 00:01:59.025
And so if we think about AI as a tool
that empowers our human employees,

0855f932-a5b4-4715-879f-18114ccb88ae-1
00:01:59.025 --> 00:02:01.270
you know,
that's where we're really going to get

0855f932-a5b4-4715-879f-18114ccb88ae-2
00:02:01.270 --> 00:02:02.920
the value from, from the technology.

2d07c63e-7fc6-4297-8100-6bef4e0ffd57-0
00:02:04.000 --> 00:02:06.227
Lucas,
what do you think employee AI integration

2d07c63e-7fc6-4297-8100-6bef4e0ffd57-1
00:02:06.227 --> 00:02:07.000
should look like?

48f71c00-7dfc-4e71-ba2b-c8cfb3c0721b-0
00:02:08.120 --> 00:02:10.137
Yeah,
I love that question because I think AI,

48f71c00-7dfc-4e71-ba2b-c8cfb3c0721b-1
00:02:10.137 --> 00:02:12.240
if it's a tool or an employee it doesn't
matter.

e0561653-bfe8-4c22-8506-bcc88ab53761-0
00:02:12.880 --> 00:02:14.876
Every, any tool,
any employee is going to have its own

e0561653-bfe8-4c22-8506-bcc88ab53761-1
00:02:14.876 --> 00:02:15.240
strengths.

c0f95eb4-af87-4b3b-80b6-d6f51430053e-0
00:02:15.240 --> 00:02:16.680
It's going to have its own weaknesses.

664d30a3-0083-4b23-b5f3-e14b560d0ab5-0
00:02:16.880 --> 00:02:17.920
And that's true for AI as well.

79fdbff2-76ac-4b40-910c-775581085eb5-0
00:02:17.920 --> 00:02:19.400
It's going to be really good at certain
things.

82d33fa8-53e2-4a26-afbd-ebf401dea08f-0
00:02:19.400 --> 00:02:23.873
It's really good about assessing lots of
large data sets and distilling signal

82d33fa8-53e2-4a26-afbd-ebf401dea08f-1
00:02:23.873 --> 00:02:24.440
from that.

eae123fa-226e-4c6d-a2a3-924fa9f97686-0
00:02:24.720 --> 00:02:27.880
It's also not so good at other things
that humans happen to be really good at.

d9ce141b-8962-405a-b4e7-2a322a6456fd-0
00:02:27.880 --> 00:02:30.424
So I think as you're thinking about when
I should use AI,

d9ce141b-8962-405a-b4e7-2a322a6456fd-1
00:02:30.424 --> 00:02:32.662
when I should use humans and talk to my
coworkers,

d9ce141b-8962-405a-b4e7-2a322a6456fd-2
00:02:32.662 --> 00:02:35.646
it's thinking about comparative
advantages and like what are humans

d9ce141b-8962-405a-b4e7-2a322a6456fd-3
00:02:35.646 --> 00:02:37.840
uniquely good at and what is AI uniquely
good at?

d00b30af-c8be-47cc-b931-74d8b3efd818-0
00:02:38.320 --> 00:02:41.931
And being really thoughtful on like, OK,
let's leverage AI for the strengths and

d00b30af-c8be-47cc-b931-74d8b3efd818-1
00:02:41.931 --> 00:02:42.600
lead into that.

3d69d6db-174d-42a8-95c3-73c724720480-0
00:02:42.720 --> 00:02:46.720
And then conversely, when AI is less good,
humans have a strength.

68321363-466b-47cc-b2d2-25b76224ca94-0
00:02:46.720 --> 00:02:50.570
Let's focus on that human interaction and
just being really thoughtful on that sort

68321363-466b-47cc-b2d2-25b76224ca94-1
00:02:50.570 --> 00:02:51.120
of approach.

18c5d6d6-84f3-4465-8d65-ee3dc234c199-0
00:02:51.680 --> 00:02:52.280
Thank you both.

4216dcb6-1636-4dd2-915e-7ad663e04a5c-0
00:02:53.080 --> 00:02:53.400
Thank you.

9e331bb2-8fe2-4d85-ba42-6030d4a822da-0
00:02:53.920 --> 00:02:54.240
Thank you.