Shift & Thrive: CEO Insights on Driving Change

Natalie Nathanson: Today's guest is no stranger to shift and thrive. She first joined us on episode 18 where we explored how systems and documentation fuel business scalability. I was eager to invite her back because of the critical relevance of her work around some of the core dynamics facing B2B executives today, specifically as AI reshapes how organizations must operate.

She and her firm have been at the forefront really helping clients prepare organizations for the changing world ahead. She has over 25 years of experience in the industry and has led her business process consultancy for the last 15 years. Today we're planning to explore areas, including how she and her team are using and navigating AI internally, and how executives can lead their organizations to navigate business transformation with confidence.

She is the founder and CEO of Business Success Consulting Group, ade cle. Welcome back to the show.

Adi Klevit: Thank you so much, Natalie. It's great to be here.

Natalie Nathanson: I am, uh, very much looking forward to the conversation today. And before we get into the meat of the discussion, I'd love to start with a bit of context from you because I know your work sits at the intersection of, you know, process leadership and operational change, and that you've been doing this for many years and well before kind of gen AI and the current surge of kind of automation hitting the spotlight.

So can you share a little bit about how your background and the focus of your firm. And have shaped the lens that you bring to looking at kind of AI and automation, um, and how that impacts businesses today.

Adi Klevit: Sure. You know, it's interesting. Um, it's the way I started my career. My first job was with an international consulting company. Um, my, um, education is industrial engineering. So I started my career as an industrial engineer working for an international consulting company. And we were working at a plant, a Mitsubishi plant in Oregon.

And my first job was to create the flow lines so the software engineer will come and then program the software and create the actual technology. I mean, that was, um, the end of the nineties, beginning of 2000. So it was definitely not ai, but it was still the same concept of you need to. Create the map, the process mapping and the process flow, and figure out where the bottlenecks are, figure out the input, the output, and the decision points in between so then it can be coded and create a computer system, a technology system to implement it.

And that was about almost 30 years ago. It's the same today. It's the same concept. Different tools to implement faster tools, tools that can do much better. Um, less necessitates the exact code. I mean, a code that you, I mean, you can do with no code. You can create all those um, solutions, but you still need to have that backbone.

You still need to have that process in place because otherwise. How are you gonna know what to do? What are you gonna tell the AI to do? I mean, the AI needs to be told that the AI needs to be trained, but trained on what it needs to be trained on the process. It needs to be trained on the sequence of events.

It needs to be trained on decisions more than ever. The decision tree. The decisions have to be clearer than ever because that is what will lead to the right decisions.

Natalie Nathanson: it is interesting how it almost comes, comes background full C circle, but as you say, in a very different, uh, you know, business context and technology ecosystem and all of that.

Um,

you know, and I'm aware this is, you know, for some organizations it's very much ingrained to how they've always operated. But then for others it's a newer discipline or maybe the focus on kind of processes and documenting those processes hasn't been as. Critical. Can you talk about, you know, how you're, how you're seeing that with, you know, companies that you talk to and, um, like what are those core components that an organization should be thinking about from kind of that foundational standpoint?

Adi Klevit: Yeah, so it's, um, the question I always ask is the end question, like, what is this gonna be useful? Like, you wanna document your processes,

why?

And I think that

To answer your question, that's what organizations, companies should ask themselves, even if they don't have the documented processes. Why do they need to document?

Do they need to document for training purposes, for onboarding, for returning knowledge, or for strictly for automation. I find that it is never only strictly for automation, because automation will increase the efficiency will

also

retain the knowledge because then you can.

You

extract the knowledge and then you retain it through machines, right?

I mean you, the machine is doing what, what you will have people do or that particular part of the organization, so you're retaining that knowledge, but it's really looking at the end result. That's that. That is the first step. Like why am I documented? Why am I documenting, why am I creating processes? How am I gonna use those processes, and how am I going to implement technology to. Make sure that those processes are being followed. So once you have those questions answered, then you can go back and figure out where you're gonna start and how you're gonna do it and what methodology you would use in order to document.

Natalie Nathanson: And can you talk a little bit about those methodologies?

What are the different approaches?

Adi Klevit: Yeah, I mean, you know, we have to keep it simple. 'cause it's really simple. You have to look, you have to understand when you are documenting what is the input. What is the output and what are the decision points in between? Then you need to obviously see what, what are best practices and identify those best practices and also see what are the, um, the deviations, you know, what are the anomalies or abnormalities or what, what is the 20%, you know, what is the 80%, what is the 20%?

I'll give you an example. We were working with, one of our clients is A CPA and we were creating his. Onboarding process. We were documenting it, we were creating the workflows. I mean the, basically the, the work line, the flow line, the process mapping of it. And he started using AI to answer the phone. Now he realized that there are different things that the AI.

It's not gonna be able to answer because those are more complex questions. But what it can do as a beginning until we train it a little bit more is to answer the path of LIS resistance. You know, the path that people have straightforward questions. If the AI can answer that, and those people are actually going to get the answers and schedule an appointment without having to talk to a human, what would that solve?

How much time would that solve? Okay, good. We figured that one out and it was worthwhile to do that. So as you can see, it's a common sense methodology. We don't need to subscribe to names or complex methodologies is what makes sense. Like what can we actually save time with and cost? How much would it cost us to save that time and that money?

See that there is an ROI do that and then invest the time to. Create the other systems that are a little bit more complex.

Natalie Nathanson: yeah, it sounds a lot similar to, you know, when we're working with organizations on kind of the marketing and go to market side, knowing sometimes like it takes time to put the right, like strategic foundations in place, but then there's always like quick wins and low hanging fruit and, kind of trying to find that balance.

So it sounds like a similar kind of dynamic there.

Adi Klevit: Yes, absolutely. Absolutely.

Natalie Nathanson: Yeah. Is there anything different in how kind of processes need to be documented when you are looking at it, like through the lens of, uh, AI and automation, like knowing that that's at least part of your end goal?

Adi Klevit: So it has to be simplified. It really has to be simplified because. Complexities are, these complexities have to be simplified, so then the complexities can be built back on. On the simplification. So in the example I gave, we had to really simplify it. What is the actual path without any additives? Good, this is for sure can be done by ai.

Those are the, those are the basic decision points. Those are the basic. Inputs and outputs, what else can happen? And then you start building on top of that. So I think looking at things in a very simplistic way is very important to actually be able to accomplish solving complex problems.

Natalie Nathanson: What about the balance of kind of automating parts of a current workflow versus like rethinking workflows?

And I'm asking this question a bit selfishly because my firm, like maybe three, four years ago, we had a big undertaking, maybe actually five years ago now, of documenting all of our processes, capturing them in the right way. You know, we got all the initial benefits of that, and that has certainly served us well now in, uh, kind of the, the new kind of gen AI and automation world.

But we're now at a point of not just wanting to, uh, kinda add efficiencies to what we're currently doing and the current workflows, but like revisiting them. So can you talk a little bit about, you know, how you work with customers around that kind of, any, any guidance you have there?

Adi Klevit: Oh yeah, absolutely. Um, you know, the implement, the optimization definitely happens throughout the documentation, right? Because you experienced that. So let's say we documented the onboarding process of a new client. Okay, good. So then, then immediately you can see, well, this doesn't make sense anymore and we don't have the form for it, so let's implement a form here so it's more efficient.

Let's

think

about, especially when you are remote, you know, what is the communication and where can we store all the data? I mean, you can, you can.

Optimize throughout the documentation, but then you look at your entire organization, you look at all the processes and you go, okay, where do I, where am I losing money?

Where is the other opportunities? Not necessarily just losing bleeding money, let's say, because it's inefficient, but where are opportunities that I'm not taking advantage of right here? Okay, good. I need those and those resources I need in terms of people in terms of. Money in terms of time to learn and to know more, okay, I need, let's say those resources.

Where am I gonna take those resources from? And then you look at your existing processes from that lens as an example, where can I shave another five hours a week? So I can all, all of us can take an AI course and figure out how to take it to the next level. So point being is that, again, you have to look at the end product.

Like what do you want? Why are you going to. You wanna improve your processes right now, what are you gonna gain out of it? So maybe you're gonna gain more, more customers, maybe you're gonna be more relevant. Maybe you're doing it because you're just interested and you are an innovative kind of person, and you wanna have like the latest and the best technology, that's fine.

But whatever it is, you have to understand the reason and then find the resources within your processes where you can free it up to get to the next level and the new process.

Natalie Nathanson: And when you think about like organizational readiness, would you say like every organization is ready and it just depends on how they start?

Or are there certain kind of signals that you look for to assess of readiness?

Adi Klevit: Readiness for processes, process, documentation,

or readiness?

Natalie Nathanson: processes for the, for the benefit of them looking at how you can, let's say AI I a certain component.

Adi Klevit: Yeah, I mean, they, they have to be mature enough in terms of. They have processes that they're doing, and they know, I mean, they, they're doing it now. It's a point of documenting what exists and then taking it into the next level. So it's fast growing companies lacking consistency. Now, it doesn't mean that the processes are all defined.

That's what. Like when we help them, but it's time to define the processes, right? I mean, you've been doing something. There is a proof of concept. It's correct. It's happening. They have their marketing people want their product. Whatever it is, they are there. Now it's time to take you to the next level. And being able to serve their customers, their clients correctly.

Now they need the systems in order to get there.

Natalie Nathanson: Mm-hmm.

And are you finding, like with your clients these days, are you often kind of driving or pushing that conversation or are they coming to you, uh, kind of wanting to kind of push further on on kind of AI and automation?

Adi Klevit: Um, it's both, you know, I'm really, I mean in terms of, you know, I'm on LinkedIn very active. I put a lot of content out there. I put podcasts out there so people call and ask questions. Uh, but I. It goes both ways. But I do get a lot of, uh, Hey, we are thinking about this. I mean, I heard that I should use this AI or that ai, you know, how can you help me?

I mean, there is a lot of confusion out there for sure. So in order to maneuver or to, um, make the best out of this, in order to actually find what the points of confusions, I mean, how we can mitigate that confusion, those conversations start happening.

Natalie Nathanson: And I'm curious if there's any kind of client examples, uh, recently that, that come to mind of where an organization really has had, uh, kind of either big impact overall or like a, a, a notable win, uh, from kind of working through this with, uh, kinda within the, the, the current, uh, like again, like gen AI and bringing that to bear.

Adi Klevit: Yeah, so you know, that's CPA. That I mentioned. So definitely a lot of improvement in terms of he was working, the head of the company was working with an external answering service because he didn't wanna hire a receptionist full-time and he wanted somebody to do the intake calls. And, you know, there were mistakes.

You know, people answer the phone, you know, according to their mood, or according to some of them were better than others. You never knew what you were gonna get. There was no consistency. Changing to AI changed a lot because the easy case, I mean, and it's easy, but it's, it's not easy. It's basically the low hanging fruit.

And those are the ones who wanted to capture right away. He, he just able to capture it, but they will always get a really good experience. 'cause they weren't complicated. The AI was able to manip

to maneuver the conversation and to schedule the appointments so he got more appointments and he also, the, the clients got better service.

So that is an example of. It looks simple once it's done, but to get there and really understand the flow lines was quite something. You know, it was definitely several iterations of how do we go from here to here? But once that's done and the process was documented, including scripts, including scenarios, he was able to do that then and then to take it farther in terms of operations.

Another example also in the finance, I mean, in the same arena of finances and taxes using ai. To extract information from a tax return, upload that information, so then the tax or the financial advisor or whomever role was looking at it, will be able to make the, in the decisions based on data and correct data, as opposed to spending hours and hours scrubbing and take, getting the data and figuring it out and put it in this spreadsheet or that spreadsheet, and.

And correlating between data, so then you can take that as well. Another thing that happened on that project is like taking the data but then compare it to other data and the AI and the machine is so, so much faster in doing that. But then the decision, it's still the the advisor, but there was data to operate on.

So instead of spending five hours, they can spend 30 minutes and really do deep thinking work and move on to the next one. So that was a great example as well.

Natalie Nathanson: Yeah. Yeah, I like that. And with the example of the CPA firm that you gave, like saying it's, it's simple once it's done.

Uh, or it looks simple once it's done, but there's a lot of work and thinking that goes into that.

I wanna come back to that theme maybe a bit later because I think there's a, there's a lot of interesting things around, around the dynamics there. Um, but I'd also love to shift gears a bit. And I know you're not only advising clients in these areas, you're really leading your own team through it. And so, being kind of a fellow, uh, leader of a professional services firm would love to, to delve in. And maybe starting with, you know, how have you or are you enabling your team to adopt and experiment, uh, with AI in your work?

Adi Klevit: So I definitely encourage that. Um, I mention it, I encourage that I, um, give them resources so I am part of.

AI

Collective. I subscribe to different groups and I give them the resources of, you know, available courses, available training, and I encourage them to do that. I hired recently, my latest, uh, our last latest hire was a VP of growth, and one of the prerequisites is that he's gonna be, I mean, in this case it's a he, but before I hired, you know, that.

They're gonna be very knowledgeable in AI and very much adapted to ai. And the person I got on board, he is and he is very good at it. So we started looking at all of our systems. 'cause that's one thing that I also tell our clients, you know, you have, there's so much tech stack, you know, there is like, you know, we,

there is an app for that and there is an app for that and there is an AI for that.

And before you know it, you have so much. So we need to really. Adjust and adjust the amount that we are using in terms of like, okay, how we can consolidate or maybe we don't need to consolidate, but we need to make sure that we understand what we have. So we looked at our entire tech stack and now we are going through it and we are optimizing the use of.

Every piece of it. So for instance, internally we use Clickup as our task management software and we are optimizing it and it's beautiful, but we are consolidating, we are basically using, also integration between that. And we use Slack for communication. So we use that like an integration of that. How do we.

Integrate our email. So it comes into Clickup and everybody will have visibility and per client, um, different projects we are working on. So there is visibility and there is accountability and we also 100% remote and that allows us to be in really good communication and run our projects very efficiently.

So that's an example. We are also in, I mean, of course we're using AI marketing and you wear. I guest on my podcast and we talked about it quite extensively, but it will never replace a marketing firm. It will never replace you or your team. It will never replace the high level, but it does make things faster, so long as you are continuing and being in control and understanding what the output is.

So that is, but we are using ai, but we're using it intelligently.

So

we that, that is another example. We are definitely looking at how to use AI with what we do in terms of the actual deliverables to the client. We, that's definitely still needs that human touch, human hand, you know, asking the questions, et cetera.

But we will use that definitely like in terms of building sentence like Grammarly or any other software that will allow us to write better. We absolutely use that as well.

Natalie Nathanson: Great.

I would love to hear a bit more about this VP of growth role and really like hear more about kind of what is in that role. And you talked about kind of the AI knowledge being critical.

So can you talk about that person's skills and responsibilities, um, and kind of what were the areas that were important for you? Um, specifically hiring that person. Now, let's say instead of like five years ago or something.

Adi Klevit: Right. So, um, probably should have hired five years ago Now I realize.

So to answer that, I

mean, you know, that's the only way to grow and scale is to actually have the executives under me that I need to have the leadership team, the people that are drivers, not just me. So that's, you know, after having a VP of operations. The VP of growth made sense because they're in charge of the marketing initiatives, the sales, you know, the growing the organization, putting in all the workflows, et cetera. So that's, that's really what that push is. But I realized that in order for us to grow correctly, we have to have all of our communication.

Right. Like we have to have the right communication and the, and the lines where the communication flows have to be all correct. So if we have clickup it all, it can be a mess. It has to be very, very organized. And that's part of putting the order in. So I already started even before that. I mean, we have policies and procedures on how to use Clickup, how to write a task.

How to do even the name convention for the task. Otherwise it becomes too random and too chaotic and nobody wants to use it because then you start making lists in another place like your to-do list. So then you start communicating about it in Slack. And part of the VP of Growth is really monitoring is like where the communication goes, where does it flow, where does it, where is it stuck?

You know, what do we need to do in order to create, um, a better system? So it's really creating also the systems internally.

Natalie Nathanson: It sounds like a strong mix of both kinda the operational, uh, acumen and expertise and that kind of revenue and kinda growth, uh, component.

Adi Klevit: Yeah, and he definitely, the person that I hired has,

um,

experience in operations, but it's not, he's not dealing with the operations for the client, like operations is client facing. It's like our production, our quality control. It's like what we produce for our clients. This is. If you will, kind of like, we are the client now.

It's like similar to us being a client. It's like you doing internal marketing for your own firm. Right? So it's different. It's not, it's not client facing.

Natalie Nathanson: Right, right. Of course. And then, you know, more broadly in your organization, you know, are, are there any kinda themes or trends around like who's kinda adopting like AI faster than others? Any like by function, certain kind of profiles? What are you seeing there?

Adi Klevit: It's, you know, I think it's pretty unif. I mean, of course some will be more inclined, but there is a lot of uniformity in terms of like. Moving forward and looking and using the tools and, and having those conversations. And that's another thing is, is really having those conversations and bringing it up to the forefront internally and making it part of what is expected will bring it, will bring the adoption faster.

Natalie Nathanson: Mm-hmm.

Are there any, um, uh, you know, guardrails or anything like that that you've put in place around, like, you gave the example with a client of freeing up five hours a week so that the team can spend more time on kind of that innovation. Is there anything like that, that you found,

uh, you

know, helpful for your organization?

Adi Klevit: Well, I found that creating the procedures and the policies and the boundaries of when we use AI and when we don't, that's helpful. I found that giving the information and the training and making it available, I found that that's very helpful. Um, I find that having that culture and that spirit in place, that it's okay and that's what we are gonna do, but also reassurance.

You know, Natalie, it's also. I found it putting in place the reassurance that, hey, so long as we are going to be ahead and we are gonna know none of your jobs are in jeopardy. And I mean it, you know, it's like none of the jobs of the people that are working with me is in jeopardy if they learn and if they understand and if they know how to, um, stay ahead.

Natalie Nathanson: Yeah, we had similarly have been reinforcing that message, uh, over and over because I think that like comfort, comfort level and safety, you know, of like, this team needs to come first. And from that point you can kind of take risks and innovate and explore and put, put new ideas out there, uh, and all of that.

Adi Klevit: That's true. Very

Natalie Nathanson: Yeah.

Adi Klevit: true.

Natalie Nathanson: Um,

one thing I've found is, you know, we've been successful bringing our whole kind of team, uh, kind of along through this journey. Been very open to, uh, experimenting, working in new ways and, and, and kind of standardizing and working in new ways as well. Um, it creates almost a bigger gap for new hires coming in that have a bigger learning curve, like coming into our organization than maybe they would've had.

In years past, I'm curious either like if you've experienced that internally or like with your clients, if that's something that you, um, and are, are navigating differently and any kind of thoughts or experiences around that.

Adi Klevit: It's a very good point because that will, you know, I hear like our processes are changing. This is changing, but it's true. It's definitely changing because none of us have really the manual. I mean, we have this great tool. It's kind of like a monster. It's like, you know, it's like this amazing tool, but there is no manual.

You do this and this will happen. You do that and that will happen. It is a lot of trial and error. And you do need to have the ability to change fast and think fast. But what we are doing is every time we are changing something, we document it so we don't forget what it is and we can actually, um, go back and exper and experiment and, and see and measure the success.

I mean, was that successful? And if not, let's change it. So it doesn't have to be a long process to document it. I mean, a long. Activity, but it still needs to be documented so you know what you're doing because you have to, you have to create points of stability within all this change because otherwise you are not gonna be able to refer back.

There will be no point of reference.

Natalie Nathanson: Yeah.

And are there any either like tools that you recommend, uh, you know, clients use for, you know, that documentation?

Any like shorthand? So I know like ultimately they wanna kinda do it the the right way, but if there's a process that's still kind of in transition or experimentation, you don't wanna kinda document something that might look different like a month from now. Any guidance around that?

Adi Klevit: Yeah,

so you know what I do is I, I just. Even use chat GPT and, and dictate what it is. You know, this is what I'm seeing and we've done this, this, and this and this, and then boom. It's just like, you know, you have it in writing and you just plug it in. I mean, you can do that. You can record videos. I mean, there is different, different ways that you can do it.

The writing of it is the, is the less, you know, it's, you can have tools for that is asking the right questions. That will be my. My recommendation is like, you know, what are the questions that you're asking? Okay, so what? How am I doing it? What am I doing? What am I not certain about it? I wanna take a look, let's say a month from now to see if it works.

How am I gonna measure this process?

Natalie Nathanson: Yeah. Um, well, and I think the other benefit there is you're making it easily available to others, and so a few people are in the same role and they see, oh, you're doing it a little bit differently than mine.

And Right. You can, it helps to kind of land on, uh, kinda the optimal way or the, the variances that you need to take into account.

Adi Klevit: Yeah, totally.

Natalie Nathanson: Um,

Curious to ask. You know, the balance of uh, any professional services firm is right, balancing the day-to-day delivery and, uh, giving kinda the best, uh, service to clients and kind of moving the organization, uh, forward and kind of evolving in new ways.

Um, so how are you thinking about that balance of really great, the day-to-day delivery with some of that like bigger picture, longer term evolution?

Adi Klevit: Yeah, that's a tough one. I'm telling you, it is a tough one. That's why hiring the right people under me so I can. Actually un, you know, unload and basically get the, uh, function so they will deal more with the day-to-day and buying myself. My, my reason of doing it is to buy myself more time in order to innovate and finding better solutions.

Natalie Nathanson: I've, uh, I've worked through different approaches for myself. I think one that tends to work best, but when business is busy, it doesn't always, uh, get the time is like dedicating specific days and carving out, uh, that time.

And then all the resources that I, that I collect, um, you know, have, have a, a focus time to be working through that.

Adi Klevit: Yeah,

I know that's, that's, that's the thing is that I can't, that's what I find for myself too. I can collapse those hats into, oh, I have half an hour here and half an hour there. No, I have to have like this. Like being the in, in the zone to do that. And that's why I also, let's say I joined, as I told you, I joined the AI collective as an example.

So this is a group of entrepreneurs that we get together three times a year and it's more of a retreat or getting away. But there is downtime, there is heads down to actually create strategy and, and use those tools and learn more tools because in some ways you even, you have to extract yourself from the environment.

'cause otherwise you're gonna. I find myself that if I'm sitting in the same office, I will go into my inbox and I will start handling things and I will do things. I have to almost be in a different environment, different hat

to

actually be able to accomplish that.

Natalie Nathanson: Yeah. It takes a lot of discipline, especially Right?

If business is is good, you're, you're busy, there's a lot going on. Uh, but that's, you know, the

Adi Klevit: And And, and that's

why you say, you go like, yeah, it's good, so I'm gonna consider, but you can't just do, you have to always look at the future. You have to have that. Foresight, you know, of what is gonna happen and then do things about that. And that is, I think, our responsibility as leaders to do that.

Natalie Nathanson: Yeah.

Yep, for sure. I'm definitely feeling that, that pressure. Um, like I always say, it's a, it's a marathon, not a sprint. Um, but continuing to push on that, uh, you know, every, every week.

Adi Klevit: Yeah, totally.

Natalie Nathanson: Uh,

I'm curious from the client perspective, if you're, and of how you're talking about kind of AI in your, your offering, you know, your services, the value that it brings and kind of setting, uh, kind of clear, uh, you know, expectations around, uh, around all of that.

Adi Klevit: Yeah,

so what we do is the way that we shifted on that, I mean, we still do all of our. Core offerings of documentation for training and documentation for improvement. But we also now do documentation in order to, um, create ai. So the, the cli our clients can then take the blueprint and then they can either, either there are.

Have a new ERP system that they're implementing and we are helping with the actual workflow, or they are looking at creating agents and then they need a workflow in the process. So I think it's just we, we are still having the, the basics, the, the, the backbone for them to then implement ai. So we also partner with AI with companies that that's what they do in terms of AI consulting.

So then we do what we do and then they can, um, stack it on top of it.

Natalie Nathanson: Yep. Yep, that makes sense. Um, I think you brought this up earlier, but right where some of the, the work happens, uh, kind of behind the scenes and then, you know, the, the final product might look simple once it's done.

Um, I know there's an area that, you know, I've been working through with my team that much of the kind of value that we're bringing, you know, to bear with AI is what happens behind the scenes, right? So in the face it's, you know, oh, there's all these new efficiencies to be gained and all of that. Uh, but managing the business, there's the investments we've made in kind of r and d and the team's experimentation time, and that we're not doing that experimentation on the client's watch.

Right. So the training, the testing, the security and governance, and then what you see at the end is kind of the, you know, what's, uh, the tip of the iceberg, so to speak.

Adi Klevit: That's

exactly right. You're right. And you know, one thing that you said. Really resonated with me. We had, we recorded, um, the podcast. On my podcast. You were a guest and we were talking about AI and the, the misconception of businesses in terms of like, oh, yeah, well, I can just do my marketing using ai. Why do I need you?

Right? I mean, the same thing with, oh, I can write my processes using ai. Why do I need you? But.

There are so many tools out there, so it doesn't mean that when you deliver like marketing you, you're not gonna use AI because it's, you can't say that. I mean, you know, because things are changing so fast and why not use tools that can help.

However, there's. So many tools out there and they're not being, and that's, I think the misconception is the tools are not gonna work by themselves. I mean, you do need humans to direct the tools. It's what is the AI gonna do for me? Not, um, you know, how am I gonna drive the AI not the other way around?

'cause when it's the other way around, like you mentioned, then you can get the mediocre. Um, you know, mediocre cookie cutter blog post or what, whatever it is, right? So the investment that we make is also the investment in learning those tools, and that is the new knowledge that as a professional service company firm, we are getting paid for.

I mean, that is basically what is being exchanged here is the knowledge. Just the knowledge has to be brought up to the next level.

Natalie Nathanson: Yeah. Yeah. No, I think that's a really, uh, important point. And I keep coming back to this and I think it, you know, it really does apply across different parts of the business that, like, having the right foundations in place matter more now than ever.

Right. And it can be very tempting to wanna skip over that. Right. But whether it's, you know, what we were talking about here, documenting the processes, making sure you have the right, like. Systems and tech in place to support it. Having the right kind of marketing foundations and kind of good knowledge on your, you know, ideal client and go to market approach and all of that, that you look kind of across the business and you can't really kind of reap the full benefits unless you're sure you kinda have the, the right foundations in place knowing that they might change.

Right. But at least as a, as a, a foundational, uh, anchor point.

Adi Klevit: That's exactly right. You. Yeah.

Natalie Nathanson: Uh, So Ade, I would love to, uh, talk a little bit about AI use, uh,

from

you, like as the, the CEO and leader of your company.

We've talked about

the organization and how you support clients. Uh, can you talk a little bit about how you're using it yourself?

Adi Klevit: Yeah. So I use it, um, as a strategic thought partner. So when I wanna make decisions, I will have the AI interview me. So then it's a sounding board because then I can. Extra. It can extract the, in the, um, ideas from me. If I wanna write a thought leadership article, I have it, interview as it, I said, you are a journalist.

Interview me, ask me the questions. Um, so that helps me then. Basically, it helps me formulate my own thoughts and my, and my ideas because somebody else is asking me all those questions. You know, I can even fit the questions and ask me, but then ask me other questions that I didn't think about. I like to use the AI also to looking at different viewpoints in terms of like, okay, so I wrote this article, now read it as a critical editor.

What do you see? Or now look at this article and read it as, um. CEO that is very skeptical. What do you see? What are your questions? So it helps me look at different viewpoints that maybe I didn't think about it myself and to broaden the scope of how I look at things.

Natalie Nathanson: I think that strategic thought partner is, uh, you know, the, the biggest one for me as well.

I think presumably, you know, each, uh, each of us has our own ways of, of doing that. And I think it's figuring out, you know, what works for you. Like, I, I like the, the devil's advocate that Right. Always what am I not thinking of or

Adi Klevit: or where would it

fail?

Natalie Nathanson: apart. Yeah.

Adi Klevit: That's right. I mean, here's my strategic, um, plan for the next year. Where do you see it'll fail? Where do you see the, the weaknesses? I mean, this is the strategic plan and those are the resources I'm going to use. Where, where is it gonna fail

Natalie Nathanson: Mm-hmm.

Well, and

it's like

Adi Klevit: or what is not strong

Natalie Nathanson: yeah,

Like a, a sounding board or like business advisor that you can always just pick up the phone and, you know, here's my idea.

Like, help me, help me unpack this. Um, but because it's technology, you can, uh, pull it up at any, any time of day.

Adi Klevit: That's true, but you see, it's, it's a good, I mean, I still need that. I need that con, like you and I having that conversation. Because no matter the AI is not going to replace that. It's not gonna replace the human, the emotions, the creation, the all of that, that we cherish so much. So for me, you asked me also how I use the ai, but also on top of it, I've been much more.

Connected to others personally, in person and in person meetings. Like you hosted the wonderful dinner that I attended in, I mean, I flew all the way to Boston for that because I still have that craving for that human connection that you can't find anywhere else. It's not the relationship with the ai, it's not really a relationship.

It is a machine. It can extract things. It can be. It can be, instead of me talking to myself and thinking about my ideas, you know you still have somebody that in a distance and you can look at your ideas and see if it's good or not. And it can bring up, according to data that it accumulated from somewhere else, it can bring up ideas that they might not have thought of, which is great.

So it's a resource, but the connections with other CEOs, with other entrepreneurs, with other leaders is very, very important and we can't let go of that.

Natalie Nathanson: I'm very glad you brought that up because I do think it can be tempting to kind of stay in, in your own world and especially depending on, you know, busy schedules or if you're more introverted or whatnot. But you do end up in a bit of that echo chamber regardless of how well you can use an AI in those areas.

And I think in general, like we're coming from a very digital heavy, uh, mode, right? And especially looking at COVID and there's a lot of people, right, spending more and more time in front of, uh, screens, but. In times of change and disruption, uh, hearing from others and what's working for others and bringing new ideas in, um, I, I get so much value from that as well.

Adi Klevit: Absolutely. Yeah,

I agree.

Natalie Nathanson: I. I'm curious before we wrap up the conversation, as you think about, um, uh, kinda the, the demands on, uh, kind of SMB executives these days and the journey that you've been on, any kind of tips or advice, uh, for folks looking to kind of best, uh, best harness, uh, AI for use for themselves?

Maybe folks that feel like they've, they're maybe a bit behind in their adoption.

Adi Klevit: Yeah, I think it's like you have to assess and evaluate where you are at. And take the next step. I'm, I'm, I'm a big believer of the next step. Whatever your next step is, do something to a win. Like accumulate those small wins. So if you've never used charge GPT, which are, I mean, I don't know, maybe there, there maybe it is, uh, maybe you are, uh.

Maybe there is an aversion to it. Maybe it's fear. Whatever it is, start using it. If you're not, if you're using it and you feel like you're not using it enough, watch a video, figure out some prompts and start using it. It's just, it comes with use using it and have the willingness to use it.

Natalie Nathanson: I think that's great advice and I think that's a fantastic place to wrap up our discussion. Um, before we do that, can you please, uh, let our listeners know where they can reach you if they wanna get in touch?

Adi Klevit: Absolutely. So I'm very active on LinkedIn, so it's Adi CLE on LinkedIn. You can always, uh, text or call at (503) 662-2911. Email me ad@bsuccesscg.com. Uh, plenty of ways to get ahold of me.

Natalie Nathanson: Wonderful. Wonderful. Well thank you so much. This has been a great conversation.

Adi Klevit: Thank you, Natalie, for having me. It was great conversation indeed.

Natalie Nathanson: Wonderful. And thank you too to everyone listening.

I know I loved hearing so much of what Adi shared from some of the examples of, uh, how they're working with clients to bring, uh, kind of more, uh, ai uh, optimization and benefit to their organization. How a d uses, uh, these tools herself as a thought partner. Um, and the importance of the human connection at the end of all of this.

And so if today's episode gave you any valuable insights, and I'm sure that it did, please share this with someone. We know this, sharing this kind of knowledge and information helps us all grow as leaders and helps us drive successful organizational transformation. So thank you again, ADE, and this has been another wonderful conversation on Shift and Thrive.

I'll see you all next time.