Technology
AI-Enabled Growth Leadership: Performance Without Trade-offs
In this episode of Inside Assemble AI, hosts Mack and Sam explore the intersection of AI and leadership, focusing on how executives can drive performance without trade-offs. Joined by Greg Master, the...
AI-Enabled Growth Leadership: Performance Without Trade-offs
Technology •
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Interactive Transcript
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Welcome to Season 2 of Inside Assemble AI.
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I am Mack, alongside my co-host Sam.
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We are kicking off what promises to be an incredible second season.
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After wrapping up our first season with that fascinating dip dive into AI and robotics,
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we heard from so many of you asking for more practical implementation focused content.
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You want to know how do leaders actually drive results with AI?
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How do you build momentum at sticks?
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And most importantly, how do you achieve even next-level performance across profit people and carcass without sacrificing one for the others?
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That's exactly what Season 2 is all about.
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And we are calling this our growth leadership in AI racism.
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And we are bringing in battle test strategies from leaders who are getting real results, not just running pilots.
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This is a premier episode. It's called AI-in-able growth leadership, performance with our trade-offs.
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And we are tackling the big questions every executive is wrestling with right now.
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How do you turn AI vision into daily execution?
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What's the minimum, minimum available AI roadmap that actually delivers value in 90 days?
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And how do you coach teams through transformation while maintaining both speed and accountability?
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We're joined by Greg Master, co-author of Change Volume 30, an upcoming author of the book Get to the Next Level coming soon.
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Greg specialized in agile growth strategy and business transformation.
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As an experienced agile coach and program manager, he helps companies break through blockers and accelerate performance using proven PMB, Scrum and agile frameworks.
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His expertise pans IT, manufacturing, quality supply chain and finance with a track track record of delivering rapid, measurable results.
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Greg, thank you for joining us.
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Thank you for having me.
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This is awesome.
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Thanks, Greg.
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So let's talk about our first segment about the leadership performance.
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Let's start with what might be the ultimate leadership challenge.
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Many teams want next level performance across profit, people and purpose.
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What leadership behaviors most reliably compound those three outcomes without trading one off against others?
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Well, it depends on what level the organization you're at, right?
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And if you talk C-suite, it's a little different.
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If you talk middle road, part of it is not doing the work for others just because it'll be faster.
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And this is the same thing you're going to apply to AI.
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And then from a leadership perspective, giving credit to the team in public and private, right?
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So when you do get to implement AI solution, it's not your solution.
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It's the group that works for your solution, right?
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And what they have to watch out for is they're not claiming they'll get credit for it.
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They'll get promoted because it'll happen.
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Well, if you stand up in front of public and you take credit for all your people, they're not going to want to do it at it.
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So you have to just give them credit, just do it.
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And then owning things in public when they don't work, you know, when they don't go well.
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And these from a leadership perspective, if you talk about high performance teams, how outcomes is that if it doesn't go well, don't play your team.
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Because you just shut them down and they won't, you know, it'll go slower.
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Take it. So yeah, we're working as a better and explain what you're doing.
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But those are the kind of things from a next level management leadership perspective.
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And even at the CEO level and the C suite level, you have to be mindful of what credit you do take and what credit you share.
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And then what credit you blame for others, right?
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Right.
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And Greg, I completely agree with that because I am kind of, I'm kind of a big follower and huge fan of serving leadership model.
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So and I definitely, you know, give the ownership because in my team, I always try to give enough credit because at the end of the day, it's actually team game.
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It's not about an individual game.
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So, you know, I think that's a very powerful statement that what you just made.
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Now, transformations, momentum, often dies between the vision and the roofing.
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What rituals or operating mechanisms with AI have proven most effective for turning vehicles into daily habits on real teams?
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What I, when I talk about my, my flyby masters Grom show and what I do when I go meet with consulting with businesses, it's really breaking as big goals into smaller things.
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Things that everyone can see progress in.
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I mean, that alone, allowing them to succeed or fail quicker is going to get them going from that vision to whatever.
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I've been so many places where we do a vision will figure out a whole year from now.
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I'm like, we don't know what we're going to do a year.
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Hey, I change is every three months.
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And you think you're going to play where we're going to be in a year and it's going to happen.
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And then make metrics simple as possible.
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Some people want to come up with this grandiose metrics and very complicated to measure.
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And you add all this administrative weight to it to collect these metrics.
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And that also slows down meeting your vision.
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And then this more you make the habit, the good share and then share it with others.
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I mean, we're going to talk about this even just using AI.
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How do you use AI to help you in a deal like your team, your entire team?
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We'll talk about that a little bit too.
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But when they learn something, share it right away.
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I mean, I've had people where they would learn how to use certain AI to help them code better or do some coding and activities like that.
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And I was really on. I was like, look, you got to share it.
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You got to share it. Share with everyone what you did.
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Don't wait to perfect product.
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Let them all now dig into what you started for them.
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And then we'll grow even faster.
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Right. They wait for that perfect layout of what the AI should work exactly right.
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You're just not going to get there.
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Right.
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Yeah. And great. I come here with that because a lot of even in our company,
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a lot of people they think what exactly they're going to do with the AI.
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And they kind of, you know, they kind of very nervous like what they're going to learn about learn about it.
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And also at the same time, like how they're going to implement that.
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So there is always conflict and some of them all the ways,
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even sometimes including me as well, that we sometimes always wait for that what would be the perfect moment when we have the interframe of ready.
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I think, you know, best way to do it.
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Just start learning and whatever you were learning, just try to implement that.
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I think that actually will be the best course of action.
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Or what next segment for practical, yeah, yeah, options.
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I'm going to pass it over to Sam.
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Thanks, Mack.
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Thanks. Great.
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Just to piggyback on what you just said about, you know,
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the utilization of AI, even if it's a small skill thing,
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we should still do that.
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And that kind of like literally resonated with something that I've been doing for my team in last couple of weeks.
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Like I built a small coding assistant agent.
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And I've been asking all my senior hours to my direct reports that
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hey, just go ahead and use that agent.
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See if it can help improve your running a better SQL query, optimize your code.
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Even if it serves like a 510 minutes of your time, it's still again,
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it's weird.
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We can still show that as an ROI to our leadership.
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And you know, I think that's the mindset we should have.
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We just have to go and just, you know, just get our hands dirty and try something,
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especially in this AI goal since everything is moving so fast.
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So completely agree with you.
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I'm glad you mentioned that it just triggered my memory of what I've been doing in a fast couple of weeks with my team in my workplace.
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So thanks, thanks for that.
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So moving on to the practical AI adoption of Figma.
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So now, you know, obviously we all have to get practical in when it comes to your implementation.
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It's not like just rainbow in sunshine that you know, you know,
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yeah, it's not so has it.
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Yeah, you're right about that.
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And a rainbow is now.
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So in your opinion, what is the minimum viable AI roadmap?
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Like if I ask you like, oh, can it please just define three use cases that usually produce meaningful business value within a quarter by utilizing AI,
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would you be able to share that for our listeners?
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Yeah, I want to give you a couple senior leadership and through the organization.
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Anything you can do in a senior can do anywhere else, right?
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I got this one from Dan Martell, who is one of my mentor coaches.
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I'm part of a groupie created.
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And he loves AI and he's 100, you know, $100 million whatever he's up there.
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He's the guy in the road, buy back your time.
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And he is such a proponent of AI now.
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He challenges as the CEO of his company, he challenges every person.
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Before you come to ask me a question, I want you to ask chat,
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or whatever AI system he has in place, what to do first.
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So before you come and ask me, go ask AI and he's programmed them all because they all know that's the very first question.
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He's going to ask.
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So you see how getting this adoption to the minimal viable products like,
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did you ask AI before you don't go back to ask AI and then think about it and then come back to me, right?
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So from a minimal viable product, how can you do that and save this group lots of time because I'll be honest with you.
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I do it too when we're sitting the group calls me, I have a question and you got to get some things to get done.
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A lot of times I'll go ask AI before I even get that go.
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Well, I already got the answer now because they just say,
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I and it just kind of told me what I should do.
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So I don't even have to ask the question anymore.
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It saves everyone time, right?
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It saves the man and him time and everyone else.
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Also, I would say, you know, every so often,
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hate questions, let's say you get used to it.
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This is one thing I've learned about AI platform.
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You may think at one time it was amazing.
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I was experimenting with my kids and clients.
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Oh, by the way, I'm teaching kindergarten kids up to eighth grade about AI.
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Not that they get to use it because they're banned from using the school per se.
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But I show them the capabilities, right?
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What is the possibilities?
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And so you think where you are now way to they come out 10 years of doing this stuff.
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Wait, wait, they're all, they're just going to live in this world.
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But take what you learned from when from you like and then try it in another platform.
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See if that platform is now ahead of the one you are working in or gives a better answer.
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Don't assume that the platform you picked six months ago is the best platform to do what you were doing now.
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So those minimum viable AI roadmap.
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So how often you want to change?
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Let's try this and actually plan to do it, right?
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Don't let it just all really knew you put plans and okay, take this, try it and these other.
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Find some other AIs, try it out.
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And then the other time is.
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And that really helps me a lot.
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And from a minimum viable minimum roadmap.
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You challenge everyone if they don't know what they want us to do have them like their minds blank.
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What to do?
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Having to start with the AI, right?
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It just and you just tested how many times did you ask AI?
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When you didn't have an idea or before you started to do it and track it if you need to.
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If you need to create a little metric in there, the track it just for a little while.
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And then after a while they do it enough, you don't track it anymore.
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You don't continuously and that's one of mistakes people made with these metrics.
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They establish a metric and think they got to do it.
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But no, just do it for a little bit.
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Get it and use to it.
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Make it into a habit.
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You know, they do it for 30 days.
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They pretty much know what to do after that.
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And you really don't have to remind them anymore.
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So those from those are the business value within the first quarter.
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You did those three things.
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You're going to find transformation in that process.
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Yeah.
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No, definitely.
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I totally agree with you that you know, it just starts small, then skill, even truly.
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Like if you see some result, if you if you start giving showing value of the implementation,
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you can always kill people.
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You can always invest in AI tools.
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I totally agree with you.
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So kind of piggyback on that.
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Yeah, road map question.
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There are a lot of CIOs like you mentioned, like you know, a lot of teams, a lot of companies as jumping straight into genetic AI, right.
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Not saying there's a cool thing to do or not saying it's a bandwagon, but it's also kind of like, you know, just to see just test the water in how it's going to happen.
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How is going to improve their efficient operational efficiency within the organization, right.
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Now, if you want to advise CEO or meter about why did they start AI implementation with the same.
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Whether it's in the data quality side or retrieval side or even a work floor mission.
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So I'll do actually, you know, provide advice to them so they can stage the capability maturally and also, you know, slowly adapt AI in certain areas of their operations or, you know, functions stuff.
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Well, I'm going to I'm going to very little twist.
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I actually would not suggest starting outside of generative AIs.
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If I was coming in and they don't have anything already, I'd be like, are you all using it?
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If you're not all using it, I want to make sure you're all using it before we go to the more complicated stuff, right.
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And you remember RPAs, stuff like that, where you're programming and you're taking in paper products and doing all that, did all that.
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It's like the beginning of AI and how they do it smart forms, right.
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The workflow stuff.
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The first place I would start doing them is like, you know, standard operating procedures. How do you take your product?
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Well, there's a difficulty because a lot of times when I was working with business analysts and stuff, let me go ask our business customers, what's your procedure?
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They want to have one and have the time I would hire my business analyst, the document procedure in the group, because they never wrote down. They just did it.
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So there's a little bit of that, but what's cool about that is you can have them do voice entry in the AI.
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They're procedures and you don't have to write it down.
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And you just have your business analyze kind of this is monitor what's going on and what's being entered and making sure the AIs picking up all nuances, or you may ask a follow question as you're going through.
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So what about that and they'll expand on it and then the system has it in there already, right.
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You don't have to go type it in and then go take in the other system and put it on your directly in the AI. Now the AI will have that procedure.
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And then you can ask it to help analyze and make it more efficient, right.
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And he may even have it. How would you, you know, that's fine. We're not eating anymore.
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So I got lots for everything. But anyway, but that is a way of getting that information in there and making it more efficient without spending a lot of time.
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But that's what I would start first. Now let's see your your restaurant or like a service operation, right.
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And you have a process, you know, just ask AI if it would recommend any changes to your process or offer new ideas to your, your stuff, automating items, you know.
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I mean, I was trying with one of my coffee shops that actually helped somebody kind of own part of it a little bit.
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And I was just implementing QR scanning cards, where they didn't have to do anything. They were in a system of customers.
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They would just QR scan it, get billed, never had to talk to the barista. If they just wanted the good coffee, right.
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And then the barista would just spend their time making the fancy coffee. It's like they really, they weren't hurry.
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We'll get that go, go to work, whatever. But those are the kind of things that you know, you can ask AI and come with ways from a time perspective.
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But you can have to collect that data, right. And that's all.
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No, I think you just literally mentioned to practical use cases of AI Greg and I totally agree with you on the standard operating procedure part because we have seen in the industry world.
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People just don't have time to write documentation and they don't know that how valuable that is, you know, when in terms of knowledge transition or orientation, I'm kind of stuff.
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And I believe AI can certainly help us documenting some of the stuff either through voice agents or you know through something like.
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I could literally just take a code and probably just put it to an AI agent and that can provide all the step by step instruction for the coding, right.
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So I think I can definitely agree with you that standard operating procedures are really a viable use case, especially in the industry world, it tends to have AI implementation.
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So thank you for your perspective Greg. So moving on to the next segment stakeholder, alignment and team dynamics. I'm going to pass it over to Matt.
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Thanks, and Greg, wonderful and I really love the conversation that we're just going I actually really love actually both of your perspective on that.
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And one other thing I definitely I must say actually that when I didn't came that I actually think that it's my guide. So it's my newer guide.
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So you four years back that when every time I need to ask Google or you know sometimes I had to take some calls to my seniors or to my managers, you know that is something that I need some advice on it.
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Now when LLM came and you know chat GPT perfectly CD GROC so many information that we have.
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So you know we don't need to be dependent too much, even though for any technological stuff, any architectural stuff, any security, anything, any research, everything that we can at least have some ideas just to get it done from LLM.
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So I completely, but isn't it that what you just said and having said my next question is you often emphasize turning nose into a smaller yes.
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Can you share a story where this mindset mindset shifted a registered stakeholder group and unlocked measurable results?
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Yeah, I'll just give an example one of my clients when I first got there, they had a project and they're going to revamp their whole back end system.
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Pretty large system and there are saying it's going to take two years.
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Right. And I'm like, well, no one can be patient for two years to see what comes out. It doesn't exist anymore. I don't care what anybody says.
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So really about like in the ad joys, I made them break it down a smaller module. I said, what kind of modules, what do you all want to do? How would you group the stuff and you could use AI to help you do that to right.
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If you just I like to be honest with you, I'll blur it out everything there is.
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I said, I said, four matter for or separate the idea, see what the conspore and then I'll go back and look and see if that makes sense. And sometimes it'll hear something like a child that you did not realize you said and you go, I need to think about that. That's a good point.
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Right. So in that before I had them break it down a small modules and then we started delivering the modules working module stakeholders. Now you can apply the same thing with AI.
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Figure out all we want to do this. Okay, start with small things show progress, deliver something that they can see. And that's just like a requirement or a wish list. And by the time we're done, we kept delivering every month, a new, you know, and it doesn't have to be every two weeks.
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It may take a month or maybe it's a couple times cycles iterations to get to where you want and then you share it.
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It's fine. It's it's not going to kill you, right? It's not going to hurt.
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They were so happy with actually seeing product where they didn't see product before that they kept funding it. So the CIO kept getting funded from the board because we were delivering people were touching things that they could demonstrate.
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Hey, we did this module. Look what it does. Oh, cool. That's cool. We're more, new more modules, right? And then I got and the end you talk about like unlocked it.
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So one of the quotes that got from the executive EP was like, I don't know what we're he says he's like, I don't know what we were doing before from an Azure perspective.
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But I clearly know it wasn't agile, whatever they taught him was it was an agile. And I'll tell you one of the we're never going back to the old way of not, you know, doing what we're doing, cycling and up demonstrating giving product, putting their hands.
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They were like we're not doing that again because everyone's so happy. I'm someone complain that wasn't like everything.
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But you have to get them used to seeing something, right? They're so used to not seeing anything they asked for everything and then they get nothing.
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So that's where that small little modules that you give them and they work. Oh, I got something that's giving me 10 minutes of my time back.
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I mean, and another one just example, we did one thing.
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It wasn't 100% right? It was all these forms, you know, you work with thinking you fill these forms of fill it in. It's like government documentation and legal documentation and they were able to get it where 50% of the documentation was now automated, right?
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It wasn't 100% and was like, dude, you just saved 50%. If we had a people with staff of 10 people, you just have free up five more people to do other things or process more forms to get even quicker so that the customer is not waiting longer.
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This sounds good. And it's not 100% okay. It's better was like a month ago.
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It's amazing people and have this as everything or nothing. I'm like, what are you nuts? I said, how much money we just saved? How much time and people?
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And now you're tying AI into that process that was more different wasn't as quick as it is now. It's a crazy great. I completely isn't with that because I was having a similar kind of situation.
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A few years back, I was talking to my data enterprise architect teams and the task was they will have to create the bunch of data's historical data and for they had to create some data models.
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The problem was that they came up with some ideas, different ideas and it took for them just to create the data models at the three months at least.
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Now, if I have different CSBs and if I had uploaded it to the chat, DBS or part of the city or whatever, if I can tell them that created a data model, it will give us the infrastructure of how we're going to design the data model.
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I'm saying it's it, it do not need to be 100% accurate. Even it's 70% accurate. Still a 30% if we have the knowledge about how to do the data models, we can easily do that.
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And definitely it is not going to take three months. I mean, you know, we can wrap it up maybe seven days, maybe you know, 10 days, maybe 15 days max.
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So I think that's definitely, I mean, it's kind of a revolution, I would say.
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Yeah, definitely. And now my next question is that leaders grapple with coaching versus commanding.
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How do you decide when to coach, when to direct, how to communicate the difference? So team stake empowered and accountable.
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So it can be trot difficult for managers to not command control, right?
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I try to coach them if you feel like you need to command and you need to dictate what to do.
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You know, you as a leader need to assess why, why is your urge there to have to drive it? What, what, what is causing you to do that?
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And then I would suggest sharing with the team, what is pushing that driving? Don't think you have to insulate other people. Why, why you're asking for it, right?
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Um, is it, is it that? And then the other thing is where I see it happen is they do what I would call helicopter management.
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They drop in, give you something, walk away and come back.
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They, they, they say, all your self organizing team, you figured out all together. Well, that's not really how it works.
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It's self organizing with guidance and, and, and coaching from the leadership.
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Is this not let them go unless they are experiencing it. I did it 50,000 times and you don't have to do it once you get there.
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But if they got there, you don't have to command a control.
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So what I worried about is that where you see the problem, where is they, they don't do anything.
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Then they try the coaching thing later on.
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And then because it's not a successful, they come in and do command control because they'll meet a deadline and they have outside forces forcing something.
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And the problem was they never started coaching from day one.
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Right. So in order to avoid that in the first place, before you get yourself boxed in to have to command what you need to do, you need to start coaching from day one, even pre day one.
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The more often you do that, the more you wouldn't have to be in the command control structure.
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I mean, I just give example years ago, I had a team from Georgia Tech, bunch of PhDs, super smart people did stuff that doesn't exist at that time.
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And now you kind of see it, but we were doing it 20, 25 years ago.
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So what you're seeing now, we were doing 25 years ago, I didn't exist in the market and I wasn't smarter than them.
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Right. They were PhDs. They knew more things about the micro, micro circuits and all I ever know, my goal was just to say, what do I need to help you get what you need done.
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Right. As a leader, it's not tell you what to do is like, what do you need? What can I get you?
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What do we need any time and then again, sharing constraints that you know about with the team.
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So they are understanding that and they're not surprised. Right. And that really, it's coaching is a long game approach.
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And you have to take it how much time do I realistically have right if it's something quick turnaround and they need your expertise, you become a team member.
spk_0
Right and help answer questions that they have and set them up first.
spk_0
But you have to be aware of that as a leader. Can I apply a long game approach or is it a short game approach.
spk_0
Right. Don't wait to the last minute.
spk_0
And then you fall back to all bad habits and my goal is to keep from doing go bad habits.
spk_0
Yeah. And and one other thing that I have experienced actually not one time but multiple times that let's say we have delivery and someone was on board it new in a team and they don't know how to deliver it.
spk_0
We are simply going to rush and they in act you know even though we are trying to coach them but we do not have the time because we have the pressure from the upper level management that we need to deliver it.
spk_0
You know we have this time frame and we do delivery within that time frame right so sometimes and even though that you know someone is coachable sometimes even though we have the resources to coach them.
spk_0
But we are unable to do it. So I mean it's sometimes it's actually getting very tricky.
spk_0
Yeah and and and that's probably as having a conversation they were talking about they were calling somebody like an assistant developer which I hated the term don't like it.
spk_0
They're smart people that you know they can do their own thing but we were talking about AI and the senior people using AI to provide coaching for the people coming on board so maybe you don't have time but maybe if you were
spk_0
trying to do it as a formula because at the 10 80 10 rule your leader or senior person and the same thing applies to AI.
spk_0
I got my cat bubbles. She's here.
spk_0
Any time I go online she just finds me. I don't know if she wants to be in the shows.
spk_0
Here bubbles there's bubbles. There she's happy now.
spk_0
If you want to do this so the first 10% you give guidance. Here's what I want same like AI you give your your boundaries and all your details on what you're thinking how you're going to do it.
spk_0
And then your person came on board or AI does 80% of the crunch time but then you only have to do last 10%.
spk_0
You have to review what comes out of AI or with your people and that's the same thing when it comes to this concept where you're coaching you coaching beginning let them work it and then you make sure you come in the back that what they did is what what you said and the smaller you can make it out here's the
spk_0
little bit of ad report the smaller you can make that gap between where you start and go the better don't quickly get grasped if you wait too long until like the day before it's due and you go check with the junior person was going to do your host.
spk_0
Right now I guarantee you as a pride you probably like oh my god what did you do can't do that like a day before we're do you you should do it like every week.
spk_0
You know love that rig and for the next segment rapid growth executions I'm going to pass it over to Sam thanks thanks Mac.
spk_0
Thanks great you know I feel like the this conversation is shaping up really well and I would definitely encourage all these seniors to probably just dive into more about how you can use AI to build your growth leadership as great as we mentioned in for the past 25 minutes.
spk_0
So thanks great for your and I do actually agree with your your 10 80 10 principle because I remember I was watching a Steve Jobs video once and he kind of like coin that principle as well and know how difficult it is some time for leadership to break their their team into that using that physical logic so so thank you for your first big effort I feel like in our our listeners are not only gaining some insights from AI in about both your issues stand fund but they're also gaining some leadership.
spk_0
Some lessons from proportion of 14 stand fund so thank you for everything great. Yeah, I'm not quiet the people and AI that's yeah, you know it's AI is like a child.
spk_0
It's a do you know do you know do you know do you know do you know do you know do you know do you know what you can make me try it.
spk_0
And certainly it'll be it'll know a lot more but yeah it can definitely take any person us. Yeah.
spk_0
So thanks great yeah so let's move on to the next segment this is actually the rapid growth execution and as you've been a professional coach for decades you walked into so many like small medium large scale companies but let's assume that if a meat market company give you 90 days to show growth traction.
spk_0
But two or three leader they were livers would you pull first and what leading indicators would you watch weekly and I'm going to add a little twist there do you think that strategy has changed in last couple of years due to you know the strategic execution of AI.
spk_0
So what do you so I thought about it is the same way I can solve anybody when I identify errors or growth right that that's in the business.
spk_0
Walk through it ask some questions.
spk_0
And then ask the team how they might get there.
spk_0
Like come on with all that thing but what would they want to do the reason why I do this because I want them to own it I'm not going to do the work for right and you shouldn't be as a leader is I want to do the work you want them to say hey I want to use this and not as an as an AI expert I will offer tools or say
spk_0
here's some tools we can use but even before we got to that I would have them as a group incorporating AI so as they come up with the solution okay how might we do AI and they might even do some research on their own who knows even if it's a restaurant or whatever got all kinds of managers that always a commitment something sales people.
spk_0
But then come out weekly goals so take that make some week goals make plans I plan every day for myself to make every week.
spk_0
And I don't always make them but I do plan it and then demo and have daily check ins and then scrawl module type things or even we used to do when I worked on F 18 and F program we had daily stand ups for first flight it's the same thing.
spk_0
Have them check in where they're at how they're progressing check ins and what's going on maybe somebody did something maybe do it all demo hey I learned this yesterday faster you can do that faster it's going to grow and then do you can come up with sprints every do but demo weekly like progress say implemented this AI or implemented this new solution with AI here's what I got right and do it weekly and also do weekly retro because you're talking about 90 days.
spk_0
So we're crunchy it down so I want to do a retrospective what worked what didn't work and we take this idea and give it to them like they do it in the week I did this then it worked better yes okay can we the next week we apply to everyone in the organization right so it's a quick rapid good okay train everybody next week in the week after that maybe we have an implement it everyone right train the trainer type thing and within a sure amount of time everybody's doing that but it really is a great thing.
spk_0
It really comes down to weekly time boxes not forever and you make sure they understand that pace and the sooner you're getting a pace even if it's big small things they get used to that pace and as soon as they get used to that pace the sooner you get more change in that time period is there so many ways to try this stuff out and one of the big things is you can't do them all once because then you'll know you not know what work.
spk_0
Right so you're better off trying one or two and just trying it and see how it worked and then if it doesn't work don't do it anymore.
spk_0
Yeah so no that that's how I would do that and getting them to that growth traction that first 90 days 90 days ain't long and it's amazing it's a quarter right be amazed how fast that 90 days goes.
spk_0
Yeah definitely up and I just feel like you know like you mentioned it's all about that mindset you know like you have the 90 days you know it's it's a short time period but just go try something doesn't matter if you feel or not you know you still going to learn something from there and maybe that you can apply beyond the 90 day periods you never know so thank you for you know sharing that perspective and you sure all these winners are taking notes of some of these key points and some some some wisdoms that great sharing.
spk_0
Yeah so I'm going to start with the next question about this podcast moving on to the next question in this segment how do you balance efficiency plays like whether it's a cost to serve or cycle time.
spk_0
Especially with expansion bits like new segments pricing partnership and there are other factors like profit and loss improves right so how do you how do you actually you know kind of balance it out we especially in this era of Jane AI that how do we can make sure that the moment and it's keep going and we're also making that balance sheet checked whether we're going into profit or direction or you know we're just going down in the last direction how do you do that.
spk_0
If you can share your view on some of the great so we all know cost is a big driver right money money talks right I think the group or the leadership group needs to come up upfront if you do save time or you save money how much of that time or money you reinvest back into the AI process and you agree to that upfront don't try to as much as you can agree to it like a whatever we say in that maybe 80% goes back in the end of the day.
spk_0
AI and 20% goes back to the right something like that we're a majority that I mean every time I talk to the always say when you start making money this reinvested in a process just get it back or expand it try something to and that's how you get that met him grow I think that's really important and then it also gives a realistic expectation right because some people may think we're going to get all the savings and maybe it don't or you know 100% of the money you see.
spk_0
Save is going to go right into this other thing and has nothing to do with AI and that's just kind of destroyed the momentum that you had they saved all this money and it just went to something else right so you got to do that and then be prepared to retrain people right we're springing somebody knew you talked about having a new person come on board like I was saying in the one place we did a 50% improvement in processing paper.
spk_0
So in theory that's five people that wouldn't need to do that anymore but they know what we do so rather than hire somebody else from the outside have them help with the new process in the company right and that's also how you save on that PNL because if you bring someone new in your culture your business and everything you got to give them all the culture training you got to do all I never could understand that when they would lay somebody off here and then hire somebody I wonder what is just transfer to person was here you already spend.
spk_0
You know the money and your overall company culture and what you do and then you got to do that all over again when new people come over I never could understand that you know to my mind that they know one thing they can probably learn something else and it'll probably be go quicker and they probably know your operation procedure all your administrative stuff that you got to do and we all complain about the admin stuff right I mean that's that's a big complaint so that's how I those two things figure out your investment your return on.
spk_0
What you're going to reinvest in it upfront and then try if you do save any people you're not where they can go or start training them along the way with that to new stuff.
spk_0
Yeah no totally agree with you especially it's more important in this AI era is like everything is so prevailing like the automation can be done easily with AI so we probably to figure out what is best for my company is it like you know should I retrain my existing work forces so they can do a better job.
spk_0
Using AI where I'm going to just hire someone from outside and train that person about company policy business professionals and all kind of stuff and also trying to train that people to learn about.
spk_0
Yeah so it's just always been like a feasibility study that we need to do to the which one would actually benefit my ROI strategy better and just going that route and I totally agree with you now we I know in the industry world we've seen scenarios where people always think about bringing someone new from our
spk_0
outside and thinking about that's going to offset the laws but in reality that is not the case and I've seen that with a lot of big companies bringing in consultants from outside think about they're going to change the operation policy and that's sometimes it's always back sometimes it's back for us and I've seen that we know in my professional experiences as well so totally agree with you on that part.
spk_0
Yeah and just to add to that it's like sometimes like one of my business models is like offer part time coaching so I'm a full time coach which you don't need.
spk_0
You have to get higher part time coach in that expertise so in these AI products your team wants to do something okay higher part time coach it comes in.
spk_0
Change your existing tax staff on that particular AI platform model because there's plenty there's people out there really get it this and get them through that learning car curve further right but this outside coach or this temporary person doesn't have to learn everything about your culture to me that's like one of the best ways to do it rather than.
spk_0
hire somebody from the outside to have that and then get them through the whole process.
spk_0
Sometimes it's just getting that those insights. I did that a lot, even before AI.
spk_0
I'd have someone go to automation program, teaching people. I just bring them in.
spk_0
We'll learn automation. I'm bringing this guy in. I put him in here or this girl, I'll put him in
spk_0
and they'll teach you all about automation. You can go ask all the questions you can, right?
spk_0
Thanks, Greg. So to move on to the next segment related to AI governance and future
spk_0
writtenists, I'm going to pass it over to Matt. Thanks, Sam. Love the conversation. Actually,
spk_0
we can go on and on on all the topics. But one other thing that you mentioned, Greg, that I
spk_0
completely agree with you. So we should train our existing employees, existing people. I am very
spk_0
surprised that when I see there are Fortune 100, Fortune 500 companies, even medium-level
spk_0
companies, they are fighting people and they are bringing a lot of people from outside.
spk_0
Even though there are so many good people that they are rock stars in their company and they
spk_0
are getting inspired. I think leaders should be a little bit of concerted
spk_0
to that they can train their existing employees, existing people, how they can be more trained.
spk_0
I mean, not just AI, but in other technologies as well so that they can cope with the newer
spk_0
technologies because if there is AI maybe three years down the road, maybe something else,
spk_0
maybe quantum mathematics one knows. So now one of my favorite topics is AI governance and
spk_0
future readiness. So what governance, values, people, bosses and policy have you seen
spk_0
enable faster AI experimentation without compromising security compliance or brand?
spk_0
I want to say it in two ways. I want to say it one way where if you don't do it, you're going to
spk_0
get security issues and trademark and apply as brand issues. And the other way, how to make it
spk_0
better. Too many places in old way would limit who has access to stuff or they just do such a small
spk_0
pilot and they wait till they analyze that out of it before they release it. And I want to give you
spk_0
an example. I've been using Zoom forever. I pay for my own copy. I'm in business. I thought,
spk_0
and I had one client that was talking about they started using the AI function in their video.
spk_0
Right. And they take notes and stuff like that. And I said, I said, that's great. I'm using them from
spk_0
like, since it started for like six months, it's really cool. It really helps with when I have meetings
spk_0
and documenting stuff and everything like that. And he looks at the person looking at me like,
spk_0
how did you get it? You're not part of the group, the small group that added.
spk_0
Because I have it for myself. I've been using it. Don't think that just because you're
spk_0
putting people in this little hole, they're not going off in the AI experimenting. They shouldn't,
spk_0
but they may go ask questions on their own personal AI access because it's cheap and inexpensive.
spk_0
You need to find a way of getting that into the hands of everyone sooner or the later,
spk_0
just to minimize the risk of them accidentally messing with your brand stuff outside.
spk_0
I mean, we've had that work doing top secret stuff. People would use a system that wasn't
spk_0
classified and we're like, what are you doing? Pull it off the system right away because they
spk_0
liked it. But it wasn't cleared, right? So you got to worry about that. And then, you know,
spk_0
don't be behind the curve of your employees. I mean, your employees are coming up with this stuff.
spk_0
Your job is not to be behind them on the outside world having more advanced tools than you do
spk_0
because I said sooner or later, they're going to make fun of you as a company. They're like, hey,
spk_0
I've been using this on my own. I've been using this AI to do my tweets or my stuff for years.
spk_0
Where have you been? You know, because that will get them in that process, that problem.
spk_0
The sooner you can get it and get them behind that security wall of that. Just don't lead them
spk_0
in a dark. You don't take forever, right? Maybe maybe have them experiment with stuff or something
spk_0
be part of that. But yeah, but that's that's the simplest way to prevent security and the
spk_0
brand losses that you got to be ahead of that. You got to have a group just like you insecurity,
spk_0
like white hat, you know, make sure they're anti, you know, the hackers and stuff like that.
spk_0
You got to do the same thing with AI and new technology, right? It's the new thing. What do we need?
spk_0
What's the next thing? You know, I can go on and ever just like, browser versions, right?
spk_0
And people don't know there's like five, 10 versions up front. There's five or 10 versions below.
spk_0
And if you're really good in your system and I've seen some really good people that would just
spk_0
automatically keep an eye out for a new version release of let's say, if I want to say, I'm
spk_0
sure they're software. They go up machine would just go well actually would spin up a server,
spk_0
get it already, go up, grab the information, bring it down, throw it in the server, install it all
spk_0
and no one touched it. This is all the computer. Start all, take all the automated test suites and run
spk_0
them all. And then it would tell you if there's going to be any future potential problems with the
spk_0
browser or the application or whatever it was. And it was all automatic. It didn't do nothing.
spk_0
And then they gave me a list of sweetest things that you had to make sure that you're created
spk_0
worked. And this was a consulting company that would make add-ons to software. So they were
spk_0
making sure their add-ons were still working in the new browsers or new things before it ever came
spk_0
out to the general public. They knew months ahead of time. There's no excuse anymore. Yeah.
spk_0
Absolutely. Adding to this, looking ahead for 12 to 18 months, which capabilities will most
spk_0
change the work of product. Leaders, marketers, operations and how should leaders prepare
spk_0
talent and team style. They're all going to change. I just, I was using one thing one month. I
spk_0
didn't like what AI was doing. I didn't think the level of performance was there. One day, I was
spk_0
trying something in one of my classes with the students. And I said, let's try it again. We try
spk_0
it again and make, oh my god, I like how quick this is. You know, it was so much better, but there's
spk_0
still AI out there that's not quite there yet. And I tell people, just don't come back in
spk_0
in all the two months. And maybe it'll be better, right? But everything from large model type systems,
spk_0
just the chat GPT, this efficiency, I'm amazed looking at new entrepreneurs or building AI
spk_0
products out there and building them in every week's soon. They're just taking what they learn,
spk_0
maybe in their family restaurant business and figuring out ways to change that. So I look at AI
spk_0
every two months. I'm serious. I'm like, we look at 18 months. Us like every two or three months,
spk_0
I'm on all of them. I just, I just take what I do. I go on every, I don't know if you want any
spk_0
names, but I do them all and see if it improved or better, right? Maybe I need to switch over
spk_0
to the new system or maybe I'll go back to the other one because they just leave.
spk_0
I mean, I remember one, you know, Gwok has a new one or whatever, a blue back blue,
spk_0
everyone's stuff away and I'm like, oh god, how do they get that far? So everything from
spk_0
laying out to plans, to schedules, to efficiency, things you just haven't tried yet,
spk_0
to be honest with you every every week, every, and let me say, if you run and scrawm or agile
spk_0
perspectives and some people say you can't, but I say you can do anything and scrawm mindset or
spk_0
create AI as a story itself, not just what you're going to deliver, but insert into the system.
spk_0
We want to use AI to do X, Y, write a story. Like we want to find an AI package that will improve
spk_0
our ability to write story, improve our ability to write content ads, then prove our ability to code,
spk_0
make that a story, quit that in the backlog. So I want to want to the people on your team,
spk_0
let them go at it, right, and see what it is and you should be doing that every sprint.
spk_0
If you're not doing that every sprint, you're going to fall behind. I'm just serious.
spk_0
Absolutely. And I think, yeah, I think maybe 12 months, 18 months, I think we should even look for
spk_0
next one month, two months, things are getting, getting changed so rapidly. You know, I mean,
spk_0
and it is going to impact in every aspect, like even like, you know, hiring new people,
spk_0
even like the development strategy, then, you know, like investment strategy,
spk_0
you know, customer relationship management, all aspects that we can talk about. And
spk_0
or our last segment for today, a metric and scaling strategy, I'm your do Pasadena, what to say.
spk_0
Thanks, Mack. Thanks, Greg. I know this has been a great episode so far. And just one
spk_0
thing I wanted to say based on what you guys converse in the previous segment is that the
spk_0
change is constant. And especially in the AI era, it's never been so true. Then that statement,
spk_0
now it's right now. So you all have to be adaptive. We all have to just, you know, get on that AI
spk_0
train and just be innovative and bring some agility or whatever you can do to improve your
spk_0
operation processes or help your company to grow bigger and better. So, so love that perspective.
spk_0
And thanks for your wisdoms and sharing it. That's great. So for this particular segment, I'm
spk_0
going to I have like one intriguing question for you. And that is is that the question is kind of
spk_0
like, you know, we wanted to just tick on your experience here. Like in your experience, like,
spk_0
what do you see like the growth strategies fill most of it? Like whether it's in the assumption
spk_0
section or in the sequenishing on governance, some are things when, you know, little just
spk_0
fills with the cracks. So keeping that in mind, how do you think that we're going to keep up,
spk_0
especially in the genie era, how do you de-risk our business, our operational services and stuff
spk_0
by utilizing AI's transformative nature of, you know, or building some sort of framework that can
spk_0
put some guard roles in those areas. So we can probably save our business or, you know, just we
spk_0
can avoid some sort of risk and compliance issues in future. So what do you think, you know,
spk_0
what we should do, you know, by using AI? Really think it, basically because the way it's programmed
spk_0
and as it gets better, this way you say you start now, you don't wait, you start doing it, it's going
spk_0
to learn different things and you're going to train it. You get, it's what people don't understand.
spk_0
You just took out a train AI, you got to teach you some stuff, it just down out of the box. And they
spk_0
don't understand the iterator process. If you listen to some of these programs at all, how much
spk_0
effort there is to train these AI's, I think just making risk reduction when I call spikes
spk_0
in your system, that you have this plan, you want to make this happen, just experiments with it
spk_0
as you go and just throw that in. How do you envision, really just trying things out.
spk_0
It may not work. Don't wait to the end to see, oh, we're going to do all this,
spk_0
we're going to turn AI, no, turn AI on and on first and let it go with you through the process
spk_0
and learn as you go. So if you want to have an AI centric improvement, that AI should start when
spk_0
you start your process, not after, it's not an afterthought. It's kind of like automated code
spk_0
automation or automated testing. You don't do it anymore until I argue with me and don't fight me.
spk_0
You automate as you test and you think of it in the same process as you go. So
spk_0
as soon as you get your final product, it's 90% there and you just have the last 10%
spk_0
to sink in with what was designed. Same thing goes with AI and how to make these happen.
spk_0
Don't wait to the last minute. Let's throw AI on it and see what it thinks. Start asking the same
spk_0
questions you asked your team, ask AI, get feedback, do that that churn and help it and train it
spk_0
to think about that because then you're going to want to use it next time. That makes sense.
spk_0
So the decision needs to be more autonomous, especially more in the AI era. Like you've got a
spk_0
constantly evolving with using AI rapidly as well as also thinking about what is going to be the
spk_0
outcome or how I'm going to do risk or how I'm going to avoid having any sort of compliance or any
spk_0
sort of issue. I feel like even with AI, I feel like we're more agile. As you're an agile coach and
spk_0
AI probably making us more agile and it's also helping us to scale faster than we could have done
spk_0
before. I guess that is probably kind of like the way we can wrap up this particular question.
spk_0
Yeah, and I experiment with some product owners from like laying out what we wanted to build.
spk_0
They were doing some stuff and we did it. And AI came up with some stuff that they didn't think about.
spk_0
From a quality perspective or a testing perspective, like I forgot about that.
spk_0
You know, so there is that in that process, right? It'll come back to you and say, yeah, you think
spk_0
you've covered everything. The AI just picks up on those little nuances that you may forgot.
spk_0
It's just any way you didn't say it. To all listeners, you know, so
spk_0
the AI could be a partner who's probably going to just not going to finger point to your
spk_0
mistakes, but probably going to assist you with eliminating your issues or maybe risking some of
spk_0
your operational inefficiencies in your business practices. So keep in mind that. So that's great.
spk_0
It's just one of, you mentioned that as a partner, I did a show episode where I said, you know,
spk_0
and the pair programming world, maybe AI is your new pair program.
spk_0
Possibly. So yeah, I think you know, I literally did. It's reading it. And I know what I'm saying.
spk_0
I mean, you were afraid to have a partner before. Well, maybe now your partner's AI.
spk_0
And it's just you and the AI kind of chatting. You're not worried about messing up because
spk_0
what does it care? It doesn't. Yeah. So it'll fix it.
spk_0
Because we wanted to start it seeing that that that people started even forming company with one
spk_0
employee, like one person kind of forming a company. So I guess they are using AI as their
spk_0
probably like a partner company. And we've seen that trained of kind of like, forgot the town. It's
spk_0
like single, untitranny or based company where they're using AI to do all the operational stuff.
spk_0
And human is merely just, you know, delving into the strategy. But that's where that 10, 80, 10
spk_0
rule comes and play it out. Don't trust everything. It comes out like I look at some of the Google,
spk_0
the search engine responses and it's AI generated. And it was one thing I was looking for.
spk_0
One day it had one answer. Halfway in a day it had another answer. And then the next day it went
spk_0
back to the answer. I had the first one. And what I realized it was doing what the algorithm does.
spk_0
And it was looking at social media feeds and was using as its answer the most popular answer,
spk_0
which may have not been the right answer. Right. So you need to do that. What can I be getting?
spk_0
And you need to review and go, why did you change your answer?
spk_0
Exactly. And that's why human intervention came into the picture. So you know,
spk_0
I got to keep up. Yeah. Yeah.
spk_0
What's up? Yeah.
spk_0
Illusionation, right? And that what they call it.
spk_0
Yeah. Illusionation. Hello, it's a mathematician problem. And open AI is a
spk_0
revolutionary, uh, publisher, researcher on that. So it's just like a some non-deterministic
spk_0
nature of AI. You'll always be there. So that's why we need to have human judgment to verify that.
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Yeah. And just add one more thing.
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My experience with AI is that well, some people may have it more sophisticated.
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There's a point where AI caps out. And I even hear it from the experts use it all the time.
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Caps out. You have to stop and just take a step back and stop invest, stop trying.
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Rethink your problem, figure out where you want to go. Maybe you just take from there.
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Maybe just it's not ready yet. Right. And so many people will spend hours and hours and trying
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to get it perfect. And I think no, stop. And we as humans need to tell people, stop.
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I'm trying to iterate on it. It's not going to get any better. It is what it is.
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Try it another AI or something. Take what I love is when people would take something
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and output from one AI, take it, put it another AI and tell the other AI to impose it or
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use something with it. And I'm like, my god, that's an amazing point. Love that great.
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So I'm going to talk about the Mac to wrap up the session.
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A great. This has been an incredible way to launch session two with your wisdom and knowledge.
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And where can our listeners connect with you and learn more about your frameworks for AI
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enabled growth and also leadership growth? There's a couple of ways. One is if you look up 5 a.m.
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Master's Grum, which is up there, you'll find me. If you're Tertian Greg, Master, you'll find me.
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I'm pretty, I might be called the Agile Cheerleader or something like that. And I have a company
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called Idea Communication Networks. It's actually we've figured it out. It's been around for over 25 years.
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And I'm like, Oh, wow, it's been 25 years. So it has a lot of stuff. If you look up Idea Communication
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Networks or just look up 5 a.m. Master's Grum or 5 a.m. LinkedIn. We're on podcasts. We do all the,
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you know, you talk about AI. I kind of use it every day. I do the Gary V. thing. I'm in like 30 different
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platforms every day. You might see me. They're all over the place. So there's ways you can use AI
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to be everywhere and anywhere. So just look up 5 a.m. Master's Grum,
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come Greg, Master, and you should find me. If you can't find me, let me know.
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Does that not want to know why? I design a seek to find me anywhere.
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And for our listeners, we are going to also add Greg's link so that you guys can check
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that what Greg's is doing. And if you guys can check on Greg on LinkedIn in different social
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media, so we are going to link all of them. And that's the wrap up on our season two premiere.
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We are doubling down on practical implementation focused on 10 this season. If to this conversation
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resonated, you will love what's coming next. We are diving deep into AI transformation
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guest studies, our tactical playbooks and the real metrics that matter.
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Subscribe wherever you get your podcast, share this episode with a leader who needs
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this kind of framework and join us next time as we continue exploring how to drive real results
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in AI era. From all of us at Inside Assemble AI, thanks for listening and we will see you
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next episode. Thank you. Bye bye. Thank you.
Topics Covered
Inside Assemble AI
AI leadership
growth leadership
AI implementation
agile growth strategy
business transformation
next-level performance
AI roadmap
team accountability
AI adoption
executive strategies
performance metrics
transformational leadership
AI coaching
agile frameworks
rapid measurable results