Lisa Mulyk on AI Governance, Sales Fundamentals, and Human Judgment

Transcript

0:02 All right, we have another episode of

0:03 Tailwind. Today we're joined by Lisa

0:05 Mullik. Lisa, tell us a little bit more

0:06 about yourself.

0:08 >> First of all, thanks for having me. Uh,

0:10 my name is Lisa Mullik and I'm a

0:11 fractional CRO, which basically means I

0:14 go in and I help companies with their

0:16 sales process. um you know, soup to

0:19 nuts, do a quick evaluation of what's

0:21 going well, what's not, and then um help

0:24 them develop systems and processes and

0:26 make sure they have the right people

0:27 working with them and they're properly

0:29 trained to drive sales.

0:32 >> Um and I work with small to medium-sized

0:33 businesses, but my background is with

0:36 some rather large companies for over the

0:38 last 30 years. Um had a lot of fun

0:41 learning a ton and being a sales leader

0:44 for a long period of time. So, it's

0:46 wonderful to be able to help some of

0:47 these smaller companies really see their

0:49 value and grow.

0:51 >> Yeah. Yeah. And that background is

0:52 perfect for the topic for today, which

0:54 is sticking to the fundamentals and AI.

0:56 Uh, tell me a little bit more about your

0:57 stance.

0:59 >> Uh, it's a lovehate.

1:02 >> I'm right there with you.

1:03 >> Yeah. I mean, I think everybody kind of

1:05 feels that way. I think there's a lot of

1:06 fear attached to it right now because

1:09 it's ah, it's going to take my job. Um,

1:11 but I also think it's very exciting and

1:13 I'm gonna date myself because I'm gonna

1:15 go back to when the internet started

1:18 >> and I remember being very young and

1:20 freaked out a little bit about that. You

1:22 know, what's that going to mean for us?

1:23 You know, what does it mean for privacy?

1:24 You know, how are we going to conduct

1:26 business? You know, all the things that

1:27 we're accustomed to doing, we're going

1:30 to change and we're at that point again,

1:32 right? So, we can either embrace the

1:34 change or we can run away from it. Um, I

1:36 think we're going to have to embrace the

1:37 change. I think we're going to have to

1:39 be very careful not to over rotate with

1:41 it because I think if you read the news

1:43 and all the layoffs and all the things

1:45 that companies are attributing to AI is

1:48 going to replace, you know, some of

1:49 these functions. Um I think they're also

1:51 discovering that it's not first of all

1:54 where it needs to be to do so. And you

1:57 still need humans. I mean, we have to

1:59 direct it. It's a tool. It's a GPS.

2:02 >> So, I think if we embrace the change,

2:05 we're willing to learn. those who are

2:07 going to do that are also going to

2:10 accelerate versus those that dig their

2:11 heels in because it's not going away.

2:14 >> Um, but I also think that those soft

2:17 skills that humans have are going to

2:19 become more and more important. So if

2:21 you don't know how to have a real

2:23 conversation and connect with people,

2:24 now is the time to really learn because

2:28 >> you know the machine can only do so much

2:31 and we have to use our insight and just

2:36 generally say okay does that really make

2:38 sense, right? Because there's a lot of

2:41 things that can go wrong with AI as

2:44 well. So automate the tasks that make

2:46 sense that we can repeat over and over

2:48 and over again. take that time back. I

2:51 always used to say, I don't know anyone

2:53 in business these days or even in a

2:55 personal life that doesn't feel like um

2:58 they could use some more time in a day.

3:00 >> Mhm.

3:01 >> To sit down and actually sharpen the saw

3:02 and think,

3:04 >> right?

3:04 >> So, if you look at it that way, it's

3:06 wonderful, right? But you also don't

3:08 know where it's going to work or not.

3:11 >> Yeah. Yeah. So, I I want to get to the

3:14 positives, but I feel like if we start

3:15 with the negatives, then we can build

3:16 them in on a happy note. So,

3:19 >> what are some of what are some of the uh

3:20 the negative things that you're seeing

3:22 with AI and maybe some of the over

3:24 rotations?

3:26 >> Um, I think that there's a point now

3:28 where some people are becoming over

3:30 overdependent on it,

3:31 >> right? They don't even want to check

3:33 their email anymore.

3:35 >> I mean, it's it's literally like, oh,

3:37 I'll just have it fire back, you know?

3:40 Thank you. Um,

3:43 if you become over reliant on anything,

3:46 you lose some basic skills. So, I'm

3:48 going to use that GPS example again.

3:50 >> Yeah.

3:51 >> Right. GPS was great and I remember when

3:54 it first launched and and there were

3:55 times when it literally brought you down

3:56 a dirt road and you were about to go off

3:58 a cliff because it just wasn't accurate.

4:00 >> Yeah.

4:00 >> We're in the same boat, right?

4:02 >> Um, so you have to use common sense,

4:04 right, with everything. Um, so I

4:08 purposely will shut off the GPS and not

4:11 use it just to make sure I still have a

4:14 sense of direction. And um, that's

4:17 actually something that I didn't have

4:18 when I was younger at all. I got a job

4:21 with a company car and they said,

4:22 "You're going to have to go see all

4:23 these people." And my parents were

4:25 panicked, right? She can't find her way

4:26 out of a shoe box, right? But I learned,

4:30 >> right? So you still have to have those

4:32 skills even with the tools that we're

4:35 using whether it's AI or anything else.

4:38 So just make sure that you still have

4:40 those tools that you can still think

4:42 that if your phone dies you can

4:44 function.

4:45 >> Yeah.

4:45 >> Right. So I think that that's that's one

4:48 important kind of note on the negatives.

4:52 But the positive if we're going to think

4:54 about that man can I get some time back

4:57 and I can research something really

4:59 really fast. Mhm.

5:01 >> And I become I can come into a meeting

5:03 much more prepared

5:05 um to knock through the things that need

5:07 to be covered and have a much more

5:10 intelligent conversation. And it didn't

5:12 take me a half a day to do it. So I love

5:14 that. I mean the efficiency gains are

5:17 huge. It's what we take from those

5:19 efficiency gains and what are we doing

5:22 in place of that

5:24 >> to get more done.

5:26 >> Yeah. Yeah. I mean, the whole having an

5:29 AI bot respond to my emails for me,

5:32 that's wild,

5:33 >> especially if I'm in a sales role

5:35 because it's like, hold on, that's when

5:36 my if like my clients or my prospects

5:38 are trying to talk to me and I'm

5:40 ignoring them. Like the the last thing I

5:43 want to do is not take that opportunity

5:44 to connect with them, you know, when

5:46 they're actually actively reaching out

5:48 to me at some point in time. Um, you

5:51 know, do you have any uh, you know,

5:53 you're talking about, you know, hey, it

5:55 can make me overreant, but then I can

5:57 also be have a superpower. Do you have

5:59 any like guidance on like kind of ways

6:01 to figure out how to draw the lines on

6:04 am I being overreliant or am I leaning

6:06 into the reliance zone versus like

6:08 leaning into the superpower zone?

6:11 >> I think you learn as you use it.

6:13 >> Yeah.

6:14 >> Right. Um, because it's changing every

6:16 day. Um, so things that you thought were

6:18 going to be really simple when you first

6:20 started

6:21 >> learning how to prompt properly,

6:23 >> um, you might do it again and it could

6:25 come back completely different because

6:28 it's learned and it's going to give you

6:29 something different. And I find there's

6:32 times when you're literally like I don't

6:34 know if you remember when like Alexa was

6:36 launched, you know, when Amazon, you

6:38 know, put the spy in your house.

6:39 >> Um,

6:40 >> that's why I don't have one, but that's

6:42 a whole conversation.

6:44 >> Yeah. My children got me one for for

6:46 Christmas one year. I'm like, "Thank you

6:47 for sending me another spy aside from

6:49 the phone. You know, they know

6:50 everything that I do now." Um, but I but

6:53 I joke around about it because there's

6:55 definitely frustration points where

6:57 there was a whole Saturday Night Live

6:58 skit that I remember watching with like

7:01 older people arguing with Alexa. I'm

7:04 finding that I'm arguing with chat GPT

7:06 sometimes going, "That's not what I

7:08 wanted. Was I not specific enough?" Um,

7:11 so you can waste a little bit of time

7:13 there. Um, you know, no joking aside,

7:16 but I I do think, like I said, it it's

7:18 fantastic for research. Um, I'm finding

7:20 that it's also if I think back through

7:23 my sales career, some of even the the

7:25 concepts and the training that I went

7:26 through, um, I couldn't remember all it,

7:29 but I'm like, "Yeah, that was really

7:30 useful." So, I can go back and reference

7:32 it and dig it up. It's almost like

7:34 having a superpowered librarian, you

7:36 know? Um, it's the next generation of,

7:40 you know, what we use Google for when

7:41 you think about it.

7:43 um just to go and dig and find some

7:45 things that that spur my brain to go,

7:47 "Oh, yeah. I kind of like that angle. I

7:48 I think I can especially with my clients

7:52 in some cases if they're just learning

7:54 um even sales concepts, it helps to kind

7:57 of rejigger my brain, go, "Oh, yeah. I

7:59 remember doing that and it's really

8:01 useful and let me go share it with

8:03 somebody." Right? So, that's just an

8:05 example of one way that I that I've used

8:07 it. Um,

8:10 and I just lost my train of thought.

8:12 >> It's all good. No, so as you were

8:14 talking through it, you know, one of the

8:16 big uses I have for it is research as

8:17 well. I think it's one of those

8:19 opportunities where if I'm going to go

8:21 into a conversation,

8:23 >> um, I can figure out a lot more in a

8:25 shorter period of time because I don't

8:27 have to spend a bunch of time googling,

8:29 taking notes, doing all that. And one of

8:31 the things that I found too is that if I

8:33 require whatever, you know, tool that

8:35 LLM tool that I'm using to provide

8:38 citations, that really makes it a little

8:40 bit more accurate, less likely to

8:41 hallucinate. And if anything looks

8:43 fishy, I can go, "Well, where'd you get

8:45 this from?" And I can go click on the

8:46 citation and go read it for myself. Uh,

8:49 which, you know, at times been like,

8:50 "Oh, no, that's legitimate." Or, "I

8:52 don't know if I trust this source. Like,

8:53 this is a Reddit thread. I'm not going

8:54 to I'm not going to run with this. Not

8:56 to say there's not good information

8:58 there, but I want to work from a little

9:00 bit more of a place of understanding and

9:02 uh, you know, reliability than some

9:04 people's opinions.

9:05 >> That is a great tip, by the way, which I

9:07 always use as well, is like, please

9:09 provide citations like where did you get

9:11 this from? Because then I can go back

9:13 and I can double check

9:15 >> and say that looks right. This

9:17 something's not sitting right with this

9:18 piece of it. And and sometimes even the

9:21 language, don't copy and paste

9:22 everything that you get. Like,

9:23 >> oh, please no. Yeah. use human language,

9:26 you know, think about what you're

9:27 saying. Um, it can definitely reward

9:30 some things in a beautiful way, but you

9:32 really need to have your own voice in

9:34 there.

9:35 >> Um, you know, if you're somebody that's

9:37 a little bit more direct, then you

9:38 probably want a little more direct. If

9:40 you're a little softer, it probably

9:41 should be said in a different way.

9:43 >> Yeah.

9:44 >> So, you know, again, great tool, but you

9:46 still have to spend the time to go look

9:49 at it. Um, the other thing that's been

9:52 interesting and I was actually just in a

9:53 round table meeting with a bunch of

9:54 other CRO and we were talking all about

9:57 all the different tech stacks and the

9:59 different pieces of AI that flow into

10:01 any process.

10:03 And one of the questions was, you know,

10:06 and and of course they they called on

10:08 me. I'm like, why'd you call on me

10:09 first? Um, was, you know, what

10:11 particular tech stack are you using

10:13 mainly with your clients right now? And

10:15 I just paused and I said it depends on

10:18 where they are,

10:19 >> right? So that's always another thing

10:21 that's really important is where are you

10:24 in the journey?

10:26 >> You know, if it's a bigger company

10:28 that's got some of the tools like CRM

10:30 systems in place and things like that

10:32 and they're just refining their

10:34 strategy, they might need different

10:36 components of AI to drive the system a

10:39 little bit faster, more accurate, etc.

10:41 But if they're just starting, like I've

10:44 got some some some little clients,

10:47 >> they're just starting. I'm like, you

10:49 can't sell them a Mercedes when they

10:51 don't even have understand how to key

10:52 like turn the key to the ignition. We

10:54 don't even have those anymore, right? We

10:56 have FOBs.

10:57 >> But, you know, that's precisely my point

10:59 is you just have to know where you are,

11:02 how much you know about it. I mean,

11:03 everybody wants to have say they're

11:05 doing AI, but do you really understand

11:07 where you are? Do you have an AI policy,

11:10 which is really important? Like, how are

11:12 you allowed to use it within your

11:13 business?

11:14 >> Very different from your personal life,

11:16 right? Um, there are probably some

11:18 things that you should be doing and some

11:20 things that you shouldn't be doing. And

11:21 you really need to think through that

11:24 along with the legal aspects of things,

11:26 particularly if you're in an industry

11:28 that's highly regulated.

11:29 >> You need to think about those things.

11:31 And you know, I think everybody wants to

11:34 dive first into it, but sometimes you

11:37 need to take a pause and say, "We're

11:38 going to slow down a little bit." The

11:40 other thing that's very tempting is to

11:42 chase the shiny new toy.

11:44 >> Yeah. Right.

11:45 >> Okay. And because there's so many

11:47 companies that are out there, and you

11:48 and I both know that it's going to

11:50 consolidate. There's, you know, the ones

11:51 that are going to do really well are

11:52 going to get gobbled up by some rather

11:54 large companies. And that's probably the

11:56 hope and the and the dream when you

11:58 start raising money to develop all these

11:59 tools. But there's this race, too. So,

12:04 um, some of the folks that I'm talking

12:05 to are saying, "Look, we're not telling

12:06 anybody to sign a contract for more than

12:08 like a month if they can do that because

12:11 there might be something that's better

12:12 that comes out later,

12:14 >> right? And then there's also a need for

12:17 evaluation. Um, I probably get 20

12:20 solicitations a day for perspective.

12:24 >> Probably a lot of them are AI driven

12:26 because I had one that hit me up 10

12:28 times in a day. Oh wow.

12:30 >> And I was very mad and frustrated like

12:32 stop it, you know, um you know, cut them

12:34 out of my inbox, but they still somehow

12:36 managed to weasle through again. And and

12:38 I will never do business with that

12:39 company because it's irritating.

12:41 >> Absolutely.

12:42 >> You know, so um I guess what I'm saying

12:44 is like you got to do the evaluation.

12:47 You got to try a little bit before you

12:50 you dive deep into it and make long-term

12:53 commitments because things are changing

12:55 rapidly. That said, it's also a

12:58 challenge, right? How much time do we

13:00 really have to play with all of these

13:03 new tools, right?

13:06 So, there's there's I don't know that

13:08 there's an authority yet

13:11 on evaluating these things, but

13:14 >> I'd agree with that. No, I think uh you

13:16 made really two interesting points that

13:18 I think go really well hand in hand in

13:20 there, which is um there was an AI bot

13:23 clearly harassing you and they're like,

13:25 "Well, I'm never working with that

13:26 company."

13:27 >> And I think there's that that risk,

13:29 which is it, you know, this idea of

13:31 having this AI SDR that's persistent,

13:33 that never takes a break, that can hit

13:35 up your entire TAM, your total

13:37 addressable market within a short period

13:39 of time.

13:41 >> Very tempting. And then on the exact

13:42 opposite side of that is and it could

13:43 burn every bridge within your

13:45 addressable market and you might have to

13:46 rename your company because some bot got

13:49 let loose and was just overhitting up

13:52 every single person. Um and you know so

13:56 it's like there's that temptation

13:58 there's that flip side and what you were

14:00 talking about is you know having like an

14:01 AI policy in place

14:03 >> and you know from an organization where

14:05 we kind of uh started natively as an AI

14:08 company we not we don't deliver AI but

14:11 we were natively delivering using AI

14:13 from the start we were always highly

14:16 aware of all the risks uh so we've kind

14:18 of had our internal one and like that's

14:20 been working for a small team that we

14:22 have now but as we grow we're going have

14:24 to have one in place, right? Like um so,

14:27 you know, from somebody who's, you know,

14:28 thought about this already, has put them

14:30 in place, you know, what are some of

14:31 your your you know, things that people

14:34 should take in consideration? What are

14:36 some guidances on, you know, putting

14:37 together a good AI policy and what does

14:40 it cover? Uh tell me somebody who

14:43 probably has put together one hopefully

14:44 as we grow a team, you know, what would

14:46 you say to me as like a starting point?

14:48 Um, I think you have to do an evaluation

14:51 of how you're using it to start

14:53 >> right now. Right? So, take some time to

14:56 take all that in. Um, think about where

14:59 you think you need to go.

15:01 >> Right? You also need to think about the

15:03 other companies that you're working

15:04 with, your partners. Are there other

15:06 pieces of data, you know, that you're

15:08 bringing in? I'll give you an example.

15:10 Um, I've got another person that I

15:12 talked to in a market research space.

15:16 Their business is is dependent upon

15:18 taking data from all different places,

15:22 cleaning that data, and then using it to

15:25 make some very intelligent business

15:26 decisions. But they have to depend on a

15:29 third party to work for whoever their

15:32 client is. They have to work with

15:34 whoever they're working with to bring

15:36 that data in,

15:37 >> which means there's going to be legal

15:38 documents relative to NDA's sharing and

15:41 everything else that that are going to

15:43 basically say you're allowed to have

15:45 this. this is the only way you're

15:46 allowed to use it.

15:49 >> And there are definitely some clauses

15:50 that are in there about generative AI

15:52 because everybody's very worried that

15:53 proprietary information is going to

15:55 somehow get behind the wall and then get

15:57 out again.

15:58 >> Yeah.

15:59 >> Right. So that's just a specific example

16:01 of understanding where it works in your

16:04 business, where some of the risks are.

16:06 You need to think about from a tech

16:09 security, you know, all those

16:11 perspectives, you know, where is it

16:13 going? How is it going to be? housed

16:15 safely and then also the legal

16:17 ramifications if something happens,

16:20 right? So there's it's kind of a whole

16:23 suite of things that you just need to

16:24 think about. Um and you know sales you

16:29 could say you know like what we just

16:31 talked about you know we are going to

16:33 draw a line in the sand and say we're

16:34 only going to contact somebody so many

16:36 times. We're going to make sure that

16:37 we're going to give a little space.

16:40 We're going to make sure that we're not

16:41 scraping any proprietary information

16:43 when we use it. So you can develop a

16:45 policy specifically around that, but you

16:47 really need a corporate policy that

16:49 covers all the different aspects of some

16:51 of the things that you're doing because

16:52 it's all different departments, right?

16:55 So that that would be how I would start

16:56 with a client. And then I'm I'm not

16:58 necessarily an AI expert. Yeah,

17:01 >> I know enough to be dangerous, but I

17:03 would definitely consult with somebody

17:05 and I have folks that I work with that

17:07 are in my network of referrals that

17:10 specifically work around that and

17:12 they'll work with a legal department to

17:14 say the this is how quickly it's

17:15 changing and here are some of the things

17:17 that you need to think about.

17:19 >> Right? So, it's doing an assessment of

17:21 where you are, where you want to go and

17:23 what departments are using it and what

17:25 are some of the things that are really

17:26 great that we're doing. What are some of

17:29 the things that could cause us a little

17:30 bit of a hang-up either with our direct

17:33 customers or third parties that we're

17:34 working with? That would be where I

17:36 would start. And and you brought it all

17:38 the way, you know, all the way from the

17:39 top from the super important to the

17:41 well, let's even to put requirements on

17:43 how much time like a bot needs to put in

17:45 between something like that, you know,

17:47 from a perspective of let's say I'm a

17:49 sales leader and maybe I'm I'm just

17:51 below the need worry about corporate

17:54 governance and you know, arguing with

17:55 legal all the time

17:57 >> and I'm mostly just like trying to lead

17:58 a team and trying to get them optimized

18:00 using it. Um, would you recommend that

18:02 policy being part of how that leader is

18:04 talking to their their sales team? And,

18:06 you know, do you have any

18:07 recommendations on, you know, maybe not

18:10 hard fast rules or maybe you do have

18:12 some hard fast rules on like what some

18:13 of that policy should include on what

18:15 people are allowed to or not allowed to

18:17 do with AI.

18:19 >> Yeah. I think first of all, it needs to

18:21 be socialized. We have a policy, but if

18:23 nobody understands it or signs off on

18:25 it, it doesn't matter.

18:26 >> Good point.

18:27 >> It doesn't matter. So, in general, any

18:30 any kind of corporate policy when you

18:31 think about it, you know, everybody

18:34 needs to be knowledgeable about it and

18:36 and if you're in a particular industry

18:37 that's that's got any kind of regulation

18:39 or rules, everybody needs to understand

18:40 what those are and they need to sign off

18:42 on it and it needs to be done regularly,

18:44 right? Because things are going to

18:46 change. Um, so and then if I'm leading a

18:48 sales team, you know, I need to know the

18:52 policy as a leader, but I also need to

18:54 reinforce that in my messaging,

18:57 >> in my observations, right? If I see

19:00 something that looks like it's being

19:01 done a little color, a little outside

19:02 the lines and I think it's going to be a

19:04 problem, I will bring it up.

19:05 >> Yeah.

19:06 >> Right. And then if it continues,

19:10 there are repercussions for that

19:11 behavior. Right. As with everything,

19:14 right? It's just another piece of it.

19:16 Right. Um, so I think you just you have

19:19 to be aware. You also have to be aware

19:20 of the changes that are coming. Um, and

19:23 make sure that everybody's aligned and

19:24 yep, we we acknowledge that we

19:26 understand what we should or should not

19:28 be doing.

19:29 >> Would you take it down even to the level

19:30 of you are not allowed to send an AI

19:33 generated message without first editing

19:35 it or do you think that there's enough?

19:38 >> I think you got to just do best

19:39 practices, right? I mean, you don't want

19:41 to be overly, you know, you don't need

19:42 to hammer it, but I I just I do think,

19:45 you know, you need best practices and

19:47 and part of that is explaining what

19:49 happens when something doesn't go right

19:53 >> like this is the potential. Whoops. That

19:56 or wow, we just caused a major issue. If

20:00 you don't think through it, that and

20:02 maybe you don't look that smart either.

20:04 just like I can tell pretty quickly when

20:07 something comes through that's

20:08 completely like there was not a human

20:10 that touched it.

20:11 >> Yeah.

20:11 >> Right. Definitely.

20:12 >> Um so it's just it's explaining um you

20:16 know and this is again the case when

20:18 whenever we have profound change you

20:21 know we learn you know I I remember even

20:23 when we were in COVID I had to do um I

20:26 had a a big team and I was asked hey can

20:29 you talk about doing effective virtual

20:31 presentations

20:33 >> and you know we all we all had our

20:35 moments there and I literally pulled up

20:38 if you go and look at epic fails in

20:40 video calls on YouTube, there's some

20:42 fantastic material that'll make you

20:44 laugh like crazy, but you don't want to

20:46 be that person, right? Um, you know,

20:49 rule number one was wear pants, right?

20:51 It just it makes sense, right? You know,

20:54 um, we're in the same point, right?

20:56 We're using more technology. We're

20:58 changing the way we do business. So, you

21:00 know, take a step back, think,

21:04 >> use it where it's appropriate,

21:06 >> make some modifications, and then hit

21:08 send. It's it's a good rule even if you

21:10 write your own email particularly if

21:13 it's something that's a little bit

21:14 emotionally charged.

21:16 >> Yeah. The one where you're like I'm

21:18 deleting that one

21:20 tomorrow.

21:21 >> Let it go for 24 hours.

21:23 >> Yeah, definitely.

21:25 >> Well, I think that's such a good

21:26 comparison too. I know that uh you know

21:29 becoming more you know zoom oriented or

21:32 you know being like you know digitally

21:34 like presenting things was less profound

21:37 to some degree than AI but that was

21:39 something that was kind of thrust upon a

21:40 bunch of people and it fundamentally

21:42 changed their business uh and some

21:44 people who adapted with it gave them

21:46 opportunities to increase their talent

21:48 pool to be beyond just certain

21:50 geographic constraints. It increased

21:52 the, you know, the deliverability so

21:54 they could do certain things where it

21:55 used to require people in the office or

21:58 in a room with them and now they can

22:00 deliver remotely or they can have, you

22:02 know, clients on the west coast if

22:04 they're east coast base because they

22:06 were able to adopt this and that's a

22:08 very recent reminder and it's like well

22:10 I got those wins. I had my stumbling

22:12 blocks and AI is I think going to be

22:14 much more transformational

22:16 >> but at least it's something that's like

22:17 hey I just recently went through this

22:19 technology like like shove less than a

22:23 shift more of a shove at that point

22:24 right

22:25 >> exactly

22:25 >> and now you're getting another one but

22:27 now you're kind of like okay what did I

22:28 learn during that period of time and how

22:30 can I apply it to this

22:33 >> nuances and differences though right

22:35 >> there are and there's um it's also

22:38 different I I I had another discussion

22:40 around the same topic It's the hot topic

22:41 of the day.

22:42 >> It is.

22:42 >> Um I had an HR company that that brought

22:45 a whole bunch of executives in from

22:47 different perspectives. You had people

22:49 that were doing hiring. You had, you

22:51 know, operations teams. You had um CFOs.

22:55 It was a group of really great people.

22:58 And we were talking a little bit about

23:00 some of the ways that AI was changing,

23:02 even things like hiring,

23:04 >> right, now that we have applicant

23:06 tracking systems. Um and I that was a

23:08 mixed bag. There were a lot of people

23:10 that were like, I can't stand it. It's,

23:12 you know, you get hundreds and hundreds

23:13 of resumes and everybody's modifying,

23:16 you know, what they did because they

23:19 want to get past that tracking system

23:21 and it's it's there's probably a lot of

23:23 candidates that you're not necessarily

23:24 seeing.

23:25 >> Yeah.

23:26 >> Um, that was just one topic that we that

23:28 we covered and we had a little bit of

23:29 multigenerational

23:32 >> teams in and very different

23:33 perspectives. So, that's another thing

23:36 that as an organization you're going to

23:37 start having to think about too, right?

23:40 >> Um,

23:42 >> you've got folks that are a little bit

23:44 older like uh, you know, my father's

23:47 actually 80 and still in a startup,

23:48 right?

23:49 >> Very cool.

23:50 >> And I'm teaching him,

23:52 >> but he's at least willing to do it,

23:54 right?

23:54 >> Yeah.

23:54 >> Um, you know, and and and his brother

23:57 also very successful, ran a whole

23:59 company, called me in and goes, "Okay,

24:00 I'm hearing all about this. I need to

24:02 keep my skills sharp." But not

24:03 everybody's going to feel that way,

24:05 right? So, you have to really think also

24:07 about generationally.

24:10 What's this going to do,

24:12 >> right? Because there's going to be a

24:14 different perspective. And I think the

24:16 younger kids that grew up with a phone

24:20 and electronics, like they grew up on

24:21 the phone and the electronics, um,

24:23 they're going to come at it a little

24:24 differently than somebody my age,

24:27 >> right? And

24:29 that's the case with a lot of things,

24:31 not just AI. So there's this whole

24:33 generational piece too which is going to

24:34 be really interesting to see how that

24:36 unfolds.

24:37 >> Yeah.

24:38 >> You know,

24:39 >> would you say that especially with AI,

24:41 it's important to put together

24:44 committees internally that include like

24:47 generational considerations uh to make

24:49 sure that you're getting the full scope

24:51 of understanding of kind of how things

24:52 are shifting.

24:53 >> I think you should be doing that with

24:55 everything that has impact on your

24:56 business.

24:56 >> That's fair. Yeah.

24:57 >> Okay. I 100% agree with you. Um, and

25:01 it's also getting to a place where

25:02 everybody feels safe to voice their

25:04 opinion. They may not agree,

25:06 >> but we also need to have some level of

25:08 understanding and difference in thought

25:09 and how, you know, one problem may be

25:13 addressed 13 different ways.

25:15 >> Yeah,

25:16 >> I personally love that. I don't need to

25:19 be around a bunch of people that think

25:20 exactly the way that I do because we're

25:23 going to knock through something a lot

25:24 faster if we got different points of

25:26 view. I may be the executive that

25:28 ultimately makes the call, but I also

25:31 want to understand where everybody's

25:32 coming from because I can miss something

25:34 really big if I'm only listening to the

25:37 same group of folks that have, you know,

25:40 that are all coming from one cohort.

25:42 >> I think that's really important and

25:44 that's also going to shape the way that

25:47 a lot of the AI tools are learning. when

25:48 you think about it, you've got all

25:49 different folks that are I can just see

25:51 where this is going

25:53 >> that are, you know, building all this.

25:56 So, yeah, I think you definitely need

25:58 different folks in the room to talk

26:00 about how we're using it, you know,

26:01 because I I do feel like it based on

26:04 just that one group,

26:07 the ones that are literally right out of

26:08 school are like, "Oh, I'm going to use

26:09 it for everything. It's going to tell me

26:12 exactly when to brush my teeth in the

26:14 morning." you know, and then and then

26:15 you've got a little skepticism when you

26:17 get in the 50 plus range going,

26:20 >> we've been through some of these things

26:22 before. I don't know if we want to throw

26:24 150% into it because we're going to miss

26:26 something. And that just comes with

26:28 experience, right?

26:30 >> So, it's it's going to be very

26:32 interesting that that'll be a hot topic,

26:34 I think, in the next, you know, six

26:37 months or so. And then there's one more

26:38 thing that I want to bring up.

26:40 >> Oh, please. Yeah. and it's the impact to

26:43 the economy. I think we're seeing it now

26:46 because again I think we've overrotated.

26:49 >> Um I think in countries like the US

26:52 that's highly

26:54 serviceoriented. Okay. We're not doing

26:56 as much manufacturing as we used to,

26:58 >> right?

26:58 >> We're not doing as much, you know, get

27:00 your hands dirty jobs. I mean th those

27:02 those trades people are are in great

27:04 shape right now. There's it's going to

27:06 be a while before the robots can do all

27:07 the plumbing and the HVAC stuff, right?

27:10 Um, I think we're going to get hit a lot

27:12 harder than some other countries

27:14 >> with this because it has a profound

27:17 effect on some of the entry level jobs

27:21 where tasks can be automated, some of

27:23 the research jobs, all of those things

27:26 um are going to be impacted much faster.

27:29 So, we're going to feel it first,

27:32 >> right? And it's going to have to evolve.

27:34 So, we're gonna have to figure out how

27:36 we're gonna, you know, upskill a good

27:38 chunk of the folks that are out there

27:41 trying to work.

27:43 >> And it's going to be painful in the

27:45 beginning. You can see it already.

27:48 >> Yeah. Yeah, I'm with you on that one. I

27:51 think it'll be really interesting how

27:53 everything shifts. I I think though then

27:55 to the point of you know you wanted to

27:57 talk about fundamentals in the age of AI

27:59 when we started this conversation

28:01 everything we've hit along the way from

28:02 you know governance to you navigating

28:04 new technology to automation disrupting

28:08 like labor forces I mean that's already

28:09 happened in our our past many many times

28:12 I mean it seems like you know a good uh

28:15 way to think about it is okay this is a

28:17 new technology it's transformative the

28:20 fundamentals have not like shifted

28:22 they're still there. They're still

28:24 applicable. Still do the best practices.

28:26 It's a new widget per se. I mean, a

28:28 little different than that, but having

28:30 the good policies, making sure there's

28:32 coordination, multi-generational like

28:34 committees, bringing all the different

28:35 viewpoints, you know, upskilling and all

28:37 that stuff. I mean, I think if anything,

28:39 it's just kind of like making the

28:41 fundamentals even more important because

28:43 you're going to have to rely on them

28:44 more because it's such a new territory,

28:46 but they're still applicable at this

28:47 point. Yeah, we're gonna if we have this

28:49 conversation a year from now, it'll be

28:50 interesting to see what's happened

28:52 because it's going so fast.

28:53 >> Yeah, we'll book it June 30th. June

28:56 30th, 2027. Let's see.

28:58 >> Okay. Actually, I'm excited about it. I

29:00 think it's going to be fun. I think

29:01 we're going to trip on ourselves a

29:02 little bit. We already have.

29:04 >> Um but at the same time, like like if

29:07 you're somebody that embraces change,

29:09 >> it's kind of cool.

29:10 >> Yeah, it's fun. All right. Uh final

29:14 thoughts? What's the big takeaway for

29:16 somebody? What's the summary that you'd

29:17 want if somebody listened to this and

29:18 they're going to take one thing away and

29:20 apply it to their business or their like

29:22 leadership role? You know, what would be

29:24 the thing you'd say this is the one?

29:27 >> Um, I'd say lean in.

29:29 >> Yeah.

29:30 >> But make sure you know the depth of the

29:31 pool before you dive.

29:33 >> Yeah, definitely.

29:35 Cool. Well, Lisa, I really appreciate

29:37 it. This is really fascinating. I I'm

29:38 gonna have to start thinking about my

29:39 own AA policy because as we start to

29:41 grow, I'm gonna need to have more than

29:43 just a cons founder consensus on what we

29:46 all understand to be the risks because

29:47 that's not something that just osmosis

29:49 is to somebody else. So

29:50 >> yeah, sometimes you got to call in some

29:52 folks that are

29:54 >> way ahead of it that that specialize in

29:56 that. I that is not me, but I know like

29:58 where to start.

30:00 >> Maybe calling you soon hopefully.

30:03 >> Okay.

30:05 >> Thank you, Lisa. I appreciate the time.