Episode 41
Scale Yourself Without Multiplying by Zero: Le-An Lai Lacaba on AI-Enabled Virtual Assistants
Le-An Lai Lacaba has spent seven years building an executive assistant agency where the differentiator isn't the assistants — it's that they're trained to manage AI. She's a self-described systems nerd, she wrote the book Scale You, and she's deeper into AI than almost any CEO you'll meet. So it's worth paying attention to the sentence she opens with: "If you multiply something by zero, it's always going to be zero."
That's the whole argument. AI doesn't add capability to your business. It multiplies whatever is already there — your documented processes, your standards, your judgment. And if those things live only in someone's head, you're not scaling them. You're scaling the gap.
In this episode we get concrete about what that looks like: the book publisher whose AI edited in 20 minutes what took human editors weeks — until two months later the work was quietly wrong, because no one had written down that a human proofreads before print. The lead-gen workflow that drafted 111 emails straight into an inbox with no way to catch the mistakes. The pattern is always the same. The win happens fast. Then it breaks in a way that reveals the standard nobody had codified.
We cover:
- Why AI is a multiplier, not an add-on — and what that means for where you start
- The moment a "brilliant" AI win turns into a liability you can't see
- Why documentation isn't the boring part — it's the whole foundation
- What Le-An believes about AI now that she didn't six months ago
- Her one piece of advice for the CEO who doesn't know what to do next
Connect with Le-an: https://www.linkedin.com/in/leanlailacaba/
Transcript
Welcome to another episode of Lead with Trust.
Speaker A:I am super excited to kick off a new mini series today where I will be interviewing 12 CEOs around their experience, the obstacles they faced and the challenges they had, but also the successes and growth stories they experienced with AI.
Speaker A:And I am so happy to kick off this series with Leanne.
Speaker A:Leanne, why don't you give us a little bit of a background as what you do and I know you're super personally excited about AI.
Speaker A:So, yeah, thank you.
Speaker B:First of all, very, very honored to be one of your very first couple of guests.
Speaker B:So for a background on me, I currently, I co founded a executive assistant business about seven years ago.
Speaker B:Now in October, we're hitting seven years.
Speaker B:And for a lot of what we do is we're basically placing a lot of operations, executive assistance.
Speaker B:And the way that we do that as well is part of the service is we add workflows and AI automations to the client's business.
Speaker B:So then for the EA, the EA is the one managing the AI.
Speaker B:EAs are trained in how to use AI, so on and so forth.
Speaker B:And I am a huge AI and systems nerd.
Speaker B:So those two kind of combined really, really well together for me.
Speaker A:It's funny how you introduce yourself because you're being very humble.
Speaker A:The way I came across, actually you, was because Dan Priestley actually recommended you.
Speaker A:And I just want to make a shout out here.
Speaker A:You wrote the book Scale You.
Speaker A:So anyone who's looking for that topic and to dive deeper into how to have a virtual assistant and how someone can really help you scale yourself.
Speaker A:Right, because that's what it's all about in your organization, then that's a great first start.
Speaker A:And I just want to mention here real quick that you and I actually worked together.
Speaker A:We started working together like six months.
Speaker B:Ago, eight months September, if I remember right.
Speaker B:Yeah.
Speaker B:Wow.
Speaker B:Wow.
Speaker A:Time flies.
Speaker A:And I think we both learned a lot.
Speaker A:I mean, I at least did a lot during that relationship because I tried to scale way faster or way too early with hiring.
Speaker A:And Ian, you and I were very honest with each other and we agreed.
Speaker A:Look, we're going to pause this for six months because we have to build the foundations.
Speaker A:And that's such a beautiful segue into AI because you and I know it takes a lot of foundation building to make AI and scaling with AI happen.
Speaker A:So why don't you kick us off And I would love for you to share three examples of how your company right now is using AI that you're really proud of.
Speaker A:Just that we get a Feel for where you are.
Speaker B:So the main thing that I always talk to people when it comes to like using AI is AI can't is a multiplier.
Speaker B:Like it.
Speaker B:If you multiply something by zero, it's always going to be zero.
Speaker B:So like, for me like the biggest thing that I've been using AI on is mostly developing systems and workflows for a lot of people.
Speaker B:So I mentioned I'm a big systems nerd.
Speaker B:So one of the main ways that we would do is we would actually ask a client from like beginning all the way to the end, like how does your business work?
Speaker B:Like how do you get clients all the way to how you do deliver and what does your day to day look like?
Speaker B:And, and the coolest thing that we've been using cloud at this point is we put in essentially that whole transcript of talking to the client, asking them very specific questions about their business and then it spins out into this whole beautiful amazing mind map of their business from like start to end.
Speaker B:And it will flag the things because I've kind of gotten Claude to the point where I have literally kind of downloaded almost all of my systems focused YouTube videos.
Speaker B:And as well as the skill you book, thank you for showing that into knowing like what would be the things that I would be looking for, what would the things that I would critique or give feedback on and would give me a report of like, okay, this is the client's mind map.
Speaker B:Do they have SOP on this and this and this and this.
Speaker B:And so it gives me like a really good checklist that I can then go back to the client.
Speaker B:I'm like, hey, these are the things that we would need to start building within your business.
Speaker B:So that's the first one that I honestly that took so long to be able to build and figure out all the puzzle pieces, how they came together.
Speaker B:The second one was one that we originally connected on is I do have a very good workflow where I can.
Speaker B:Well now I've even upgraded it where I have a Claude skill now where my assistant can put in a transcription of a YouTube video that I have and create essentially a month worth of content it already created.
Speaker B:This is just for Instagram, this is for LinkedIn.
Speaker B:This is for TikTok.
Speaker B:If I do start using it for captions on TikTok.
Speaker B:And that one has been something that I love doing is just creating content marketing.
Speaker B:So when I was able to figure out like how to be able to do that and it did it yesterday, I did it as a test and I actually timed it.
Speaker B:It took it 20 minutes to make 30 days worth of content for different platforms.
Speaker B:So that one, I'm still buzzing because I did a big improvement.
Speaker B:I'm like, oh, that works okay.
Speaker B:And a third way that I love using AI for, honestly, I have a little bit of chronic illness that I use AI to track.
Speaker B:So anytime that I have a question of can I eat this, can I do that?
Speaker B:I have this AI that basically has almost all of my medical records that I could grab digitally, basically.
Speaker B:Um, it basic.
Speaker B:It makes it easy for me to interact and talk to my doctors about stuff.
Speaker B:It makes it easier for me to plan out how my lifestyle should be.
Speaker B:That's once on the personal note, but that's.
Speaker B:That one is one that as someone who has kind of a fear of just being sick in general just because I've gotten sick so many times in my life on the personal side, that's.
Speaker B:That's one that I love being able to kind of build a cloud assistant that I can ask for questions of like, what if I do this, what if I do that?
Speaker B:What's the best way to be able to implement this?
Speaker B:So those are the three ways or just basically systems, marketing and my health.
Speaker A:Essentially I just built this massive cloth skill as well for the same reasons, right?
Speaker A:Like cancer survivor and trying to remain in remission.
Speaker A:And these, these tiny little make me a meal plan where I can get the nutrition that I need is.
Speaker A:It's just so.
Speaker A:But the underlying theme here is really, you didn't just sit there and wrote a prompt or a better prompt.
Speaker A:You spend sometimes months extracting, codifying, structuring all your knowledge, and then put that somewhere in an AI accessible way.
Speaker A:So really cool.
Speaker A:So walk me through a moment in the last six months where AI in your company wasn't maybe doing so well or something went wrong.
Speaker A:What actually happened and how did you fix it?
Speaker B:There are two instances that pop in mind.
Speaker B:One is one of the services that I'm tweaking around with is essentially just very simply calling it the lead reviver, right?
Speaker B:Would go through every single booked calendly call that I've ever had and essentially writes up emails for those who follow up with those people.
Speaker B:And in concept, it's super, super cool and it's something that we've now been able to really develop.
Speaker B:But I remember when I first started creating it in March, it drafted 111 emails into my inbox and I had no idea which one was what.
Speaker B:So that was.
Speaker B:That sent me back a lot because it.
Speaker B:It went through the whole Cycle of looking at the, the lead, basically researching them online, then drafting the email right off the bat without a backup.
Speaker B:Like I didn't have it write the drafts inside like a Google Sheet or a Google Doc.
Speaker B:And that's essentially the tweak that I had to make was I needed a way to capture what it created before putting it into Gmail, because by the time it went to Gmail it had like duplicates.
Speaker B:It had the wrong person for the wrong email.
Speaker B:It was a mess because mostly because I didn't have a way to catch it before I actually pushed it out into my Gmail.
Speaker B:That was the first one.
Speaker B:The second one was also a little bit similar where we do have a database where we have of course matching the client and their EA's name.
Speaker B:And there was this weird glitch.
Speaker B:I think someone just touched something on the sheet.
Speaker B:We couldn't figure it out, where all of the EA's names move downwards and the emails that were generated were to the wrong EAs.
Speaker B:And we were like, oh no.
Speaker B:So we had to really fix it really quickly and we had to apologize to the clients.
Speaker B:Luckily we only set it up to four and then I caught it because I was cc'd in all of the emails.
Speaker B:I'm like, something's wrong.
Speaker B:So there's times like those where just because something, either a human touched it or there was just a missed step when it came to developing something in AI, then we were like, oh, okay, this is just.
Speaker B:This just needs this fix.
Speaker B:And then now it works.
Speaker A:So a lot of this, what I'm hearing is missed standards and guardrails that we might have not even knew we needed before.
Speaker A:And now we know how do you fix that from not happening again?
Speaker B:Part of it is not being afraid to start from scratch.
Speaker B:It's, it's.
Speaker B:So I remember when I started building with AI, that was the hardest part for me.
Speaker B:It's like, okay, do you have to like actually start from scratch of like having Claude wipe all memory of this project?
Speaker B:And I kind of had to do that a couple of times where I kind of had to re write my prompting, how I was thinking about it, how I wanted to communicate with AI?
Speaker B:Because that's one of the things where a lot of people again are scared.
Speaker B:I was the same way of like, do I have to start from scratch?
Speaker B:I'm like, I'm so tired.
Speaker B:Like I worked hours on this only for it not to work.
Speaker B:So that's one that I've, I've kind of really been better at.
Speaker B:Is like one Capturing what was the original prompt that I put in and then what was the next iteration, next iteration, and what was the results.
Speaker B:So that's part of the guardrails that I have.
Speaker B:And then afterwards the main thing that I have, oh, this is the thing that I had started doing because of that I have AI because it's connected to, well, quad.
Speaker B:And that's just my notion.
Speaker B:I. I will actually have it kind of like a project manager.
Speaker B:Give it the updates.
Speaker B:Like, hey, can you update your own documentation?
Speaker B:Can you update your own report?
Speaker B:So anytime that I do have to kind of start from scratch, I can have it look at that report and look at what went wrong.
Speaker B:It will have an errors log and be able to do it better than the last iteration that I had to do.
Speaker B:So that's the main thing that I've now started doing more and more is having that log system where it creates a report for its future self.
Speaker A:Basically, yeah, that I'm toying with something similar.
Speaker A:But a simple version of that that anyone can just start doing now is I've developed a scratch pad, just skill within cloud.
Speaker A:And it just keeps decision logs, right.
Speaker A:It's just a live.
Speaker A:It just keeps updating itself on the decisions that we make and then why do we make those decisions?
Speaker A:So that we can then have a record of that.
Speaker A:So, so that's, that's easy fix for right now if you not want to go so sophisticated as you have.
Speaker B:Helps.
Speaker A:Yeah.
Speaker A:So what did you when you look back about six months?
Speaker A:Because AI, I would usually ask 12 months, but AI moves so fast.
Speaker A:Right.
Speaker A:So if you look back six months, what is something that you believed back then that is no longer true?
Speaker A:Like a fundamental assumption about AI.
Speaker B:Really good question.
Speaker B:6 Months ago that was very much pre true agentic AI.
Speaker B:That was pre open call, that was pre Hermes.
Speaker B:I think at that point I really thought that AI couldn't really fully do things on its own.
Speaker B:I saw a lot of the limitations of AI and I saw a lot of things that it could really do.
Speaker B:But I saw where when it came to doing quote unquote human tasks, it would still keep struggling, it would still keep having to keep tweaking it.
Speaker B:But now, six months later, we have open cloud, we have Hermes, we have cloud cowork.
Speaker B:Almost doing almost again, I call it an AI with hands was something I couldn't really imagine six months ago that I could actually now do.
Speaker B:I've seen more and more people start actual businesses, earn a lot of money and it's just them and then they're AI agents.
Speaker B:Like I have a friend who's, who's currently building that now and he's building very publicly how he's doing it.
Speaker B:But it's the, I never thought that that was possible six months ago of like, okay, this will take up, this will take a while.
Speaker B:This will not be, you know, within the next year.
Speaker B:Probably be next year or next, next year, but it's come so fast.
Speaker A:Yeah, I have this discussion a lot with people who aren't as.
Speaker A:I know that.
Speaker A:I know you personally are extre.
Speaker A:Deep in AI, right?
Speaker A:You attend AI conferences, you live, breathe and think AI all day long.
Speaker A:But someone who is maybe a CEO of I don't know, business, like a just normal business having a day job when they read the quote of Microsoft is CEO saying most of the white collar work will be automated in the next 12 to 18 months.
Speaker A:Right.
Speaker A: , so by now we're talking mid-: Speaker A:What would you say to them in terms of it's just because you're so deep into it, is that something that you believe will happen?
Speaker A:Like everyone needs to be sort of prepared for.
Speaker B:I.
Speaker B:It's kind of, it's, it's that toss up.
Speaker B:Right.
Speaker B:Like six months ago they didn't know that AI would be this fast.
Speaker B:But I also don't believe that it'll be as fast as everyone else is saying it.
Speaker B:And the reason why is there's always going to be human work that still needs to be done.
Speaker B:Human.
Speaker B:Like where I lived for basically more than a decade, I was basically facing all of the buildings for all of the call centers where you would call up Wells Fargo, you call up Amazon, you're actually calling someone from across the street in Cebu, Philippines.
Speaker B:So that was one of the things that they were like, oh, call centers are going to be dead.
Speaker B:They're not going to be there anymore.
Speaker B:But I still see people hire, hiring.
Speaker B:People are walking into those buildings.
Speaker B:People are still taking up calls, even though it was one of the first things that they said that AI would totally just replace.
Speaker B:But until now, again, there's still those jobs.
Speaker B:It's, it's just evolved now.
Speaker B:It's, it's not them taking on the primary first call, it's them getting to the call of the, getting to the root of the problem with the person.
Speaker B:If they couldn't, if the AI couldn't solve the first part of it, then it, it goes to the human.
Speaker B:So it's, that job has evolved.
Speaker B:So I'm seeing it the Same for like white collar jobs.
Speaker B:And now all the things that you know AI is going to replace, it's just going to evolve, it's just going to change.
Speaker B:It will still need a human to know what is correct and what's wrong to be able to manage and tell if it give it feedback, if it's screwing up or if doing really right.
Speaker B:But that's how I see it.
Speaker B:It's just evolving.
Speaker B:It's like, oh, it's not anymore a human right away, as you call it, is a human maybe five minutes later when the AI can't solve your problem.
Speaker B:So it's that same evolution going up to the chain of like you sully the human to double check things and make sure that's right.
Speaker A:Yeah, it's, I think it was yesterday when OpenAI put a job online for a content strategist and I think they're offering to pay like $260,000 or something.
Speaker A:I mean on the other hand you can just go to chat and write a blog post for free, but it tells you what the value of that work is, right?
Speaker A:Unless you have that human strategist and utilizing AI.
Speaker A:So funny contradiction there.
Speaker A:All right, so let's talk a little bit about AI scaling.
Speaker A:What do you, what is something that you understand about AI scaling now that you could understand without having actually gone through the stuff that you've gone through over the last six months?
Speaker B:I think the biggest one is getting your people to like, if, if you have, if someone has a team, if someone even has like a freelancer that they work with, getting them to manage the AI is my new definition of scaling.
Speaker B:Like it's, it's not about necessarily hiring more, it's just upgrading the current people that you have to upskill themselves in learning how to use AI, in getting to the point where you don't have to even create.
Speaker B:Like right now I'm still at the, at that beginning point of me creating a lot of the agents for my team, mostly because I nerd out about it, but also at the same time, like they're still also kind of catching up on learning how to do that.
Speaker B:But my own assistant the other day, she's like, oh, I created this agent and she showed me how to do it and I'm like, oh, that's something I would not have thought of.
Speaker B:And only her, she could have been the only one who could create it because she's the one in the weeds, she's the one who sees the day to day.
Speaker B:I know her sops her processes, but she knows the nuances basically of the work that she does.
Speaker B:So that's kind of the next thing that I can foresee.
Speaker B:And also did not really think that that would be the next evolution of it is then having your team, your people be the one managing the AI.
Speaker B:So then for you, you start with the strategizing and creating it with them, but then eventually your people will create it themselves.
Speaker A:So it's funny how we never talk about.
Speaker A:I mean, we mentioned Claude, right.
Speaker A:But we don't really talk about tools.
Speaker A:We only come back to like systems and foundations.
Speaker A:So let's then stay with that topic of systems and foundations.
Speaker A:When you look at something that works really well in your company and you've given us a bunch of good examples, what makes it actually work?
Speaker A:What is the foundation that you have to put in place in order to not just scale with your employee using AI, but actually scaling.
Speaker A:Like when we say scaling agentic AI or AI workflows that really take a huge chunk of the repetitive work away,.
Speaker B:It kind of still goes back to making sure it's documented because the big thing.
Speaker B:So I'll give an example for one of our clients, and this was someone who we didn't hire an EA for.
Speaker B:They purely just wanted essentially what I've been calling the bullseye system.
Speaker B:Like, we blueprint their business, we organize it, systematize it, automate, and then integrate.
Speaker B:So we walk them through that whole process.
Speaker B:And they were a book publishing company, and for them, like, we were able to automate the editing.
Speaker B:What would take a human editor, like four to six weeks to edit a book.
Speaker B:Even through the first two, just two rounds of the book, not even fully finished, I could do almost in like, I think the most was.
Speaker B:It was shorter book, but it was still like it was able to edit in 20 minutes, like very, very quickly.
Speaker B:Something that would have taken a human hours of looking through the screen, making sure to catch, you know, the errors in character names or if it were not, if a nonfiction book, double checking, essentially, data the AI could do so fast.
Speaker B:But because.
Speaker B:And they were one of the very first clients that we did this with because I wasn't fast enough, or also they were the first to make sure that the setup and procedure was updated.
Speaker B:Then two months later, when I checked with them, it turned out that the AI wasn't actually doing the work correctly.
Speaker B:They were just kind of assuming that the AI was correct.
Speaker B:But then without actually adding that human, like, hey, let me proofread this before this actually goes out into print.
Speaker B:So those were different things where it starts with systems, but then it ends still with updating your systems.
Speaker B:Because if you do want to truly have five, basically let's say for this one, they have five different book editors managing three different agents, essentially one for the primary read through of a book, then the line editing and the proofreading.
Speaker B:There needs to be proper documentation for them to know like, hey, if this happens, double check this.
Speaker B:I'm like just troubleshooting each of their agents.
Speaker B:So then they know that they're not just accepting what the AI is saying, but they're also making sure that it is still up to par to essentially where it was even before they added AI.
Speaker B:So documentation on both ends of what did this look like before we started adding AI to it?
Speaker B:And now that we're scaling, does it still.
Speaker B:Is it still the same quality check?
Speaker B:Is this still the same what people expect, expect?
Speaker B:So making sure that if you are adding a lot of AI, you're like I said, having it report to itself, having to add documentation to itself because it's going to be so hard when you, let's say like, oh, let's now scale this to 10 different agents.
Speaker B:But the first two agents only documented this part.
Speaker B:And this huge chunk that wasn't documented, it's just going to again multiply and duplicate that part that was documented missing out on all of this other part that was actually also essentially important to get the work done.
Speaker B:So it's documentation on the before and the after of like what to look out.
Speaker A:There's so many things I want to pull apart here, but one of, one of the things that it really sounds loud and clear to me is documentation.
Speaker A:And updating that documentation is one thing, but I think what a lot of that, what you're describing is actually the human judgment.
Speaker B:Right.
Speaker A:I wrote yesterday an article on the tone of voice document we had for human writers.
Speaker A:And how is the tone of voice document for AI?
Speaker A:And that's the gap you're basically describing because for human editors, what we used to have was we have a confident, you know, we describe of aspirational adjectives.
Speaker A:We give them a directionally correct sort of go that way.
Speaker A:And the copywriter is paid big box if they're good for that human judgment, for that expertise and that skill.
Speaker A:But in AI will take everything literal, what you're saying.
Speaker A:I mean, there is context and there is, you know, learning and all that stuff.
Speaker A:With this editing example, if you're taking out that human, that judgment, those that taste that you need to constantly refine the standards and guardrails and what good looks like.
Speaker A:So you say 2.67 ratio of you versus I or kind of silly stuff.
Speaker A:Yeah, well, you have to be very specific.
Speaker B:There was a study that came out, I forget how long ago now.
Speaker B:It was a few months back where they said that most of the time people are now spending a lot of time just double checking AI exactly what you're saying.
Speaker B:It's just like.
Speaker B:Just because this was the instruction that I gave to my human assistant doesn't mean it has to be the same for the AI.
Speaker B:Because like I said, AI doesn't have that because it doesn't make mistakes.
Speaker B:It can't learn from anything.
Speaker B:That's past experience.
Speaker B:Because it doesn't have past experience versus for like a human copy editor or copywriter that I hire, they would have had seen their copy that have flopped that didn't really do any well, that they didn't really like do anything, and they would have seen the copy that did really, really well that they know works for this kind of audience.
Speaker B:But then if you swap them to a different kind of audience might not work.
Speaker B:So that nuance, I guess is still something to.
Speaker B:To watch out for when it comes to just having AI kind of run by itself.
Speaker B:Yeah.
Speaker A:And the other thing that sort of stood out from what you're saying, and I would love to follow up on that a little bit, is centralized knowledge versus knowledge that lives maybe within a personal.
Speaker A:I mean, I don't mean free plan of Claude.
Speaker A:That's not what I'm going for, but like a personal Claude and you script different and I script different or you work off this value proposition and messaging and mine is slightly different.
Speaker A:How important is it in your opinion and in your experience to really have a centralized and somewhat structured knowledge base?
Speaker B:I think for me, and not realizing that I didn't really do it as intentionally as I thought is I have for the structured part is I basically created like a 2 xu skill.
Speaker B:Like every single time throughout everyone in 2 xu, they're given a 2 xu skin skill where it has the background of 2 xu, what we do, who we work with, part of our services, the things that we do that we don't do.
Speaker B:So then that's the structured part that everyone gets right away.
Speaker B:But then each person inside of the team, we have our client success managers, we have our social media team, we have essentially the sales or the lead team, they will have different ways that they're using AI.
Speaker B:So the centralized thought is that skill MD of like every single time that they use the their own pod it runs that first and then it runs whatever that centralized their own specialization.
Speaker B:So it'll have their role and responsibilities in there.
Speaker B:Like, hey, this is, you know, this is aj.
Speaker B:Like AJ is a client success manager.
Speaker B:These are his specialties.
Speaker B:This is what he does best.
Speaker B:So Then for the AI looks at the 2xu file and then looks at like, who am I working with?
Speaker B:And then it looks at.
Speaker B:We also have a notion page that basically it's connected to all of the AIs where it has anything else that has been updated that we don't really want to update the skill file yet because it's not permanent because it's still floating and it's not yet solid.
Speaker B:So then it has different checks that it looks at every single time.
Speaker B:So then it's relevant to whoever it is that's using it.
Speaker B:Does that make sense?
Speaker B:Yeah, like I said, I didn't, I didn't think that that was too intentional.
Speaker B:I just, you know, one of those things I was building as, building the car as I'm running it, like, oh yeah, we're doing this, we're doing this, we're doing that.
Speaker A:Yeah.
Speaker A:I think a lot of, a lot of things that we as system thinkers are now almost not struggling with, but maybe get excited about is all those.
Speaker A:This is a meta layer, this is an instructional information layer.
Speaker A:This is, you know, what category does this fit in?
Speaker A:It should just be more static or more.
Speaker A:I find it fascinating.
Speaker A:I wrote my diploma thesis on knowledge management systems, so I've been like the last 20 something years obsessed with this topic, but now it's just on steroids.
Speaker A:I love it.
Speaker A:It's just so exciting.
Speaker B:Yeah.
Speaker B:Makes it so easy to just build because then you have that.
Speaker B:And that's something that sometimes that a lot of people think they have to develop is that systems mindset is that you have to, you have that process mapping in your head like, okay, now I know what to build versus for a lot of people, they don't have that.
Speaker B:You know, the mapping that we both have of like this is how the system.
Speaker B:Yeah.
Speaker A:And what do you need in six months from now?
Speaker A:That, that's the, you know, that's the hard thing to keep always in mind, like to make sure building not just for today, but in six months from it now too.
Speaker A:All right, so just to finish us up, what is a resistance that you faced either within yourself or within or within the company or your clients when you really got started with AI automation and maybe even agentic AI, like where are the things that you're Pushing up against and you're struggling with because you're getting resistance.
Speaker B:I think the biggest ones and this one came up over and over again.
Speaker B:Mostly when we started working with other agencies, like outside of just again the executive assistant offer started working with other agencies on like adding AI, doing the workflows of.
Speaker B:People kept asking, what do we do now?
Speaker B:Like, what would a human do now?
Speaker B:Like, what's the.
Speaker B:What's the.
Speaker B:How is my.
Speaker B:Essentially the question of like, how is my job evolving?
Speaker B:Because you've now added this AI layer in the business.
Speaker B:That was one that I kept coming up with over and over again, even within my own team of like, hey, if you know it's been fully automated where the moment that a client success manager finishes a call, Zoom cloud already grabs the Zoom transcription, creates the report to send to the client.
Speaker B:What's then the point?
Speaker B:What else does the client success manage you for the rest of their hours?
Speaker B:Like it used to take them time to go through each video, grab the notes from it and be able to send it out to a client.
Speaker B:Now AI can do that really fast.
Speaker B:So that was kind of the thing that I still do come across with, especially when it's a business that has done some AI but they haven't really fully gotten into it of their employees or their team asking like, hey, so what does, what do I do now?
Speaker B:Like what?
Speaker B:How is my role and responsibilities shifting?
Speaker B:Because we now have AI doing this and a lot of the time I'm not sure.
Speaker B:The question is like, we'll see because we don't know until we break something and then we need the human to come back in.
Speaker B:But that's one that I think will kind of keep coming up.
Speaker B:It's just like, what do we do now as humans?
Speaker B:Because AI has been able to do X, Y and Z.
Speaker B:That will take us hours and hours.
Speaker B:AI can do minutes.
Speaker B:What do we do now?
Speaker B:So that's the same thing with the book editors.
Speaker B:Same thing for every single kind of human.
Speaker B:Not really human, more human leaning than AI leaning.
Speaker B:People have kind of seen.
Speaker B:It's like they're kind of naturally scared of losing their job, scared of not being able to fulfill, you know, a full time role.
Speaker B:They just don't know yet how their role is evolving.
Speaker A:Yeah, that makes sense.
Speaker A:It's.
Speaker A:It's funny because I'm more afraid.
Speaker A:I'm less afraid of mass layoffs because of AI replacing the people.
Speaker A:I'm more afraid of good companies going under because they didn't adopt AI deep enough, quickly enough and build those Foundations that they need to be ready for this and then they're going out of business and there's nothing you can do about it.
Speaker A:Yeah, that's, that's the.
Speaker A:Okay, now I really suck the energy out of the.
Speaker B:Gotten really deep into AI.
Speaker A:Oh my God, what a way to finish.
Speaker A:So Leanne, we talked about so many good things.
Speaker A:There were so many nuggets that you shared and, and so many helpful.
Speaker A:Yeah.
Speaker A:Insights and pieces of wisdom here.
Speaker A:What would be the one piece of advice that you would share with a fellow CEO who is sort of maybe in the middle of this whole AI?
Speaker A:I don't know if this is, you know, I don't know where path I'm going, where, what do I do next?
Speaker A:What would be the one piece of advice that you would share with.
Speaker B:It basically just goes back to the topic that we've been bringing up over and over again of like you start with what you have.
Speaker B:You don't add AI to your business.
Speaker B:You multiply what you're currently doing in your business with AI.
Speaker B:So if you're not sure where AI can start, that's where even just like on a piece of paper with a pen, mapping out like, this is how we get clients at the moment, this is how we convert clients, this is how we deliver to the clients, this is how we take care of them ongoing.
Speaker B:Even just that process of writing it out makes it easier for you to think of the ways to add AI rather than grabbing the $27 course online.
Speaker B:Of like this is how you can add AI to your business or this is how you could do cold calling in your business with AI, but you've never done cold calling in your business at all.
Speaker B:So it doesn't work because it, it, it's not something you're currently doing in your business.
Speaker B:So if you're going to add anything, look at your current systems, look at current what your process are, what your SOPs are so then you can know what actually makes sense for your business rather than again, the AI space is so loud, being dragged a 50 million ways, seeing and buying courses, you're never going to look at PDFs that didn't actually do anything.
Speaker B:Prompt libraries or plan skills that you can buy or download, but it actually is not applicable to you and your business.
Speaker B:It's just all a waste.
Speaker B:So start with where you are and then start seeing then, then be more intentional of like the things that you're grabbing rather than just grabbing whatever is the thing that's trending.
Speaker A:So really get clarity on your processes.
Speaker A:Map them out, maybe even redefine them rather than just slapping AI on top.
Speaker B:Exactly.
Speaker A:Couldn't agree more.
Speaker A:Awesome.
Speaker A:Thank you so very much.
Speaker A:If someone wants to get in touch because they really think an AI enabled virtual assistant sounds exactly what I would need, how would they be in touch?
Speaker B:The best way is just on LinkedIn.
Speaker B:My name is very easily searchable as the online La Paba.
Speaker B:My assistant is always more than happy to respond to messages there.
Speaker B:And of course I have Instagram, Facebook, Everywhere else, but LinkedIn is the best link.
Speaker A:Awesome.
Speaker A:Thank you so very much.
Speaker B:Thank you.
