How Companies Get Culture Wrong — and How AI Corrects It with James Leavesley's

You can't pick and choose how you want to analyze your organization's culture. What we've done is to say it's generic and as a result it means that we can compare kind of organizations across different sectors, different sizes because it's all the same question set and and as a result because there is an element of standardization we can then bring that down bring the cost of that down so that actually it becomes more affordable. Hi, my name is Dmitri Bonichi and I'm a content creator, agency owner, and AI enthusiast. You're listening to the AI agents podcast brought to you by Jot Form and featuring our very own CEO and founder, Idkin Tank. This is the show where artificial intelligence meets innovation, productivity, and the tools shaping the future of work. Enjoy the show. Hello and welcome back to another episode of the AI Agents Podcast. In

this episode, we have James Leley, the CEO and founder of Cultivative. How you doing today, James? >> I'm good, thanks. How are you, Demetri? >> I'm doing awesome. Well, just to kind of get things started, um, I really want to get a little bit of background on you, you know, how did you get into AI in the first place? Um, and, you know, tell us a little bit about, you know, what that story was like for you. And then we'll get into more about Cultivative. >> Yeah. So I I guess they're you know they they come together anyway uh because that was my journey into uh into AI. So um the you know I was kind of hugely passionate about uh organizational culture you know having had experiences of kind of running a business where the culture through no kind of real deliberate action you

know became a little bit siloed and uh you know maybe a little bit toxic um >> and then we turn that around and uh and then I've then also been on the receiving end toxic cultures and whatnot. And I'm sure you know many people have uh been in kind of similar situations. So what I really wanted to do was to to to find a way of quickly uh cheaply um and creatively to quantify and analyze an organization's culture, you know, and pretty much the only way that you can really do that is actually through using AI. And that was really our kind of entry into the the world of of AI which was actually just around kind of analyzing a you know a large data set that had been collected deliberately um in order to that blends kind of quantitative and qualitative information um to

build a a comprehensive picture of kind of what's going on within an organization's uh workplace culture. >> Interesting. Okay. So just kind of like getting into that, what was the main aha moment that you know kind of uh triggered everything for you? >> So like probably going back kind of like six, seven, eight years maybe. Okay. And it it was a journey where you know you kind of you know as a CEO you you rarely get to see the organization in its kind of roarest form because when you walk in the room, you're in a meeting everybody's on their best behavior. You know that's just the way it is. you're the boss. So the >> Yes, you are. >> So for what what what I ended up witnessing one day was a bit of a breakdown breakdown between teams. You know, you could see some

animosity, see people weren't on the same page. You know, I realized we got some issues. Um so, you know, I called my mentor uh and said, you know, this is what's going on. What do we do? And he said, you've got some issues with the culture. you know, let me come in. Uh, so he interviewed everybody, uh, built up a report around what's going on within the organization and, you know, it was um, you know, wasn't great reading. You know, I think it was it was, you know, you felt pretty vulnerable because I think as every CEO, you are actually also the chief culture officer. >> So, >> sure, that's a good point. So, so you are the person that is residing over the organization's culture whether that is that you've you've set it up and you know and you're deciding about really how important

that is and the work that you want to do where does it sit in the kind of priority order and um >> so you know it was a it was a a moment of apology to the organization you know it was technically a you know I'm residing over the culture and it's not great you know that's what's come back and the feedback. So what we need to do is we need to go on a journey and I really want to ask for your help. We went on that journey um prioritized the the culture, built it into the systems, built it into processes, you know, it changed how we interacted with each other and it just created a better place to work. And you know over a 12-month period you know it was you know it was a it was it was like night and day

in terms of the the organization um and it was a better place to work. We were more productive. We were innovating better commercially more successful you know all the metrics were leading to the um were in a you know moving in a positive direction. And that really was the the kind of aha moment of the importance of workplace um culture. You know, we then exited that uh business and that went into an organization where culture kind of not great. Um and you know it was really obvious where what we had and what we had gone into. And I think so it was probably a combination of seeing a not great culture, going on a journey to to in to embed a good culture, positive culture into an organization and then going back to seeing a not great culture again, you know, was probably the you

that really was the the aha moment because yeah, that meant that it was I just had a passion for that area, you know, and this became, you know, The journey that we then went on was to build out a framework um build some tech to be able to help organizations to understand the culture they have so they can build the culture they want you know and that's really the the most important point is where are you today you know because actually you can't build a culture unless you know what your what your starting point is and um and there are so many influences you know Most organizations just don't ask the right questions. So as a result, you you just never really know. So most especially in kind of scaling businesses you know the culture is heavily influenced by the CEO the founder and you

know as you start to grow then you know the culture becomes diluted because less and less people get to work with the CEO um all the time and therefore they can't emulate and and copy that person's behaviors and um and understand what's important to then so it's about you know helping helping the CEO to really understand what's going on within the organization so then you can fix the leaks you know build on the strengths etc etc and and that's that's basically what we've done >> okay and do you feel like a lot of companies are kind of like dropping the ball when it comes to this thing >> with like culture >> I mean in the context of the the CEO being connected to it probably would be the most fair question >> I think you know you I think It's culture tends to fit,

you know, within the kind of like the kind of the human resource department. Yeah. The people department. Um, and and it can sometimes be, you know, like in the UK we call it engagement, you know, and can sometimes can be a like a box ticking exercise, you know, we're doing this just to check like are people still happy and actually the the questions aren't inspiring the information. They're not really gathering kind of the the real information. We're not asking the gritty questions. So, actually, you don't really know what's going on. So you're getting a a pretty bland, yeah, we're okay and you know that can mean we are genuinely okay, you know, things are good. We're we're pretty motivated or it's a we're just telling you that because actually I can't be bothered to to go into any level of detail because I know that

you're not going to act on it. So, you know, because we're not we're not given the opportunity to tell you the information that, you know, about how we're feeling, you know, what's happening, etc., etc. So, so you kind of get to see trends, you just don't get to see what's actually driving those trends. And that really is what we've what what we've uh what we have done is to then basically just ask a different set of questions um gritty questions get underneath the skin of the business find out what's really going on and then build that picture back up you know into a full written narrative you know and then present that to the um to the leadership team. >> Yeah. No that that makes a a lot of sense. And just out of curiosity, I mean, you guys, you've been around since November 23,

right? Is that correct? Okay, very cool. Um, how did you kind of get up and running and off the ground so quick? I feel like you've made some uh, you know, solid waves. I feel like you have like a good um, uh, what's the word I'm looking for? Like when I took a look at your website, I feel like, you know, you've already established yourself so well in the last two years. like is that a part of the culture that you're trying to build just being fast moving or what what does it kind of look like internally that you've been able to kick the ground running so fast in in only two years? >> Yeah. So, so I think the you know the like we didn't spend any time writing a business plan you know which is uh you know and that was kind of

you know there was a that was a kind of deliberate move really because all we want to do was bootstrap the business. So, you know, I kind of So, I pulled together my old kind of tech team and some new individuals, you know, explain the vision of what we were setting out to do. >> Achieve and um and then we just got on to building stuff. So, you know, and and that really was the you know, so we we we and then got it into the hands of organizations as quickly as possible. you know the the yeah the big the biggest mistake is to try and sell something too early. So we were just giving it away you know getting that feedback and then iterating on that you know and I think that really kind of helped us to to shape the products you know

because we have multiple products um and also really helped us to to kind of try and decide you know what is our go-to market route and um you know and so because the original business plan was focused on targeting real organizations CEOs, you know, leadership teams and whatnot, but actually, you know, they tend to be so busy that culture, you know, it's a it's a bit of a non- entity. You know, they they they just they're not quite sure what it means and therefore, you know, it's why would I spend any time on it? Why would I spend any any money on it? And so you know so in the UK actually we have lots of kind of what we call kind of fractional kind of HRDs HR directors chief people officers who work with organizations of kind of various different sizes you know who

who actually have a a detailed understanding about kind of what's happening you know kind of how things go with recruitment what does the churn rate look like are we are we losing good people you know is product does productivity look like it's heading in the wrong ction. And these are all the kind of markers that actually are underpinned by a potentially some issues with the culture, you know, and and um and so so actually by working through that channel then actually it means that you know we can be brought in to fix a problem. um and and actually and then have somebody who can then act on that information and then support and help that business because you know one of the challenges that you know I think a lot of CEOs have is you give them the information >> and then what do I

do how do I take this forward you know and and I think the you know there's the the concept of self-reference criteria you know I was when I when I got hold of this information. I knew exactly what I needed to do to to build out the culture, you know, to put things back on track, to put the systems in place, etc., etc. So, but I pretty quickly learned that not all CEOs are programmed like that. They don't have an interest in, you know, in that particular area. And so, therefore, what they need is like a helping hand to be able to do that. And actually, I didn't want to build a consultancy. So, you know, what I didn't want to do was build uh a consultancy where we're using the tech and then having the people because actually I needed scale and to get

scale, you know, it it really had to be uh um easily accessible by organizations um you know, that could be by the CEO, could be by the the anyone in the in the leadership team, but also can be used as a tool in the toolkit by kind of fractional uh chief people officers and um and and and HR and leadership consultants. >> Yeah. No, absolutely. Uh I I did have a question actually about, you know, what you're doing um in two different ways. First, this is more of a general question about your company. How does it feel kind of like you're in the UK, right? Obviously, um a lot of people are in, you know, like more Silicon Valley, um those type of places when they're in tech. What is it like kind of working as a company like yourself in this spa AI space?

um not only not being in this the Silicon but not being in the states because I feel like that that's where maybe a lot of the innovation is if not if if and maybe I just don't have the insight of what it's like over there in the UK to be honest with that >> I think the um I mean you know we are never been asked that question before the the uh >> yeah know it's just a just curiosity thing >> I've never worked in the in the US so it's going to be a little difficult So I I think AI is yeah you we're obviously a little bit behind the curve you know compared to the US or that's what on the news and um and whatnot you know all the all the big innovations you know are obviously coming out of the US

and and to some extent kind of China now but actually there's a there's a lot of organizations now in the UK that actually are utilizing AI maybe in only a small way but actually to create efficiencies in, you know, or and bring a a kind of fairly niche product, you know, to market, which is technically what we're doing. So, you know, we are we're we're solving a problem or a number of problems. Um, it just so happens that we're we're using AI. So, you know, and I think people are now broadly aware of uh what AI can does and and can do. Um, I think there's still a bit of skepticism as well. Also, we still meet people where, you know, they they either don't trust it or um uh and whatnot. So, you know, I mean, that's, you know, that's that's that's where we're

at. But, um, you know, I think I think there's there's some really good adoption, you know, and people are organizations are embracing it because, you know, it it is being able to do things quicker, faster, cheaper, you know. So, hey, why would Absolutely, you know, why would you not embrace uh you know, those those benefits? >> No, it's a very good point. And I Yeah. No, I was just genuinely curious because it seems like the most people I interview on this show are um states side and you know, like people are like, "Oh, I want to go to Silicon Valley." If I'm not if they're not there, right? Like they'll people I've interviewed people from New York, Boston, whatever. And it just it seems to be an interesting um you know, obviously there was it it's been a tech hub for a while, but with

AI especially, it seems like that as well. So that was just more of a curiosity thing. getting back to more what you're doing in your business. um you know you've talked a little bit about um you know what you guys do and just to kind of dive in a little bit more to you know culture assessments and the like right um I feel like it's almost quantifying like the invisible right like I feel like especially when I was working at a normal company like traditional c traditional culture assessments are a little bit more they felt subjective at least to me you know Um, how does your AI powered platform like actually quantify something as intangible as like workplace culture across all the key areas that it quantifies? How does it like do that? >> Yeah. So, so we we we engaged with uh some academics,

leadership professionals and whatnot and built out a um and built out >> a framework and then the question hang hang off the back of that. you know a lot a lot of what you know we are you know I think you use the phrase you know we're trying to quantify the like the invisible so um you know I think so so the so we're you know we're still asking questions you know which which you know which have numerical responses you know therefore actually it's it's the so we're you know we're asking you know to what extent is everybody in the company treated equally >> you know you give that uh numerical response but actually it's the explaining your answer. It's the that's the open bit that then sits underneath that. >> So actually what you can then do is to take take the scoring um

which you obviously get you know and then we can then underpin a narrative that sits behind that which is talking about the issues and the challenges you know and and and some to some degree quantifying uh that across the organization as as well. So, it's it's about being able to take the uh what you would have done um in in your previous life uh and and actually start to underpin that with a narrative as well. >> H no, that that makes sense to me. Um it's uh it just it seems a little bit um it seems that very valuable, don't get me wrong, but it's just got kind of hard to pin down, so to speak. Um >> yeah. Um, and I think the, you know, I think it is, it's a super intangible thing and I think that's why a lot of people don't

give it the kind of respect that it deserves because actually, you know, you generally don't respect things you don't understand. And what we're trying to do is to say, hey, it it's not that difficult. It's just about culture is about getting the basics right. So it's how the company is led, how people are managed, how people interact, you know, various different standards and consistencies that you have across the organization. So again, when we're playing this back to the organization, we're saying these are the basics. You do this well, you know, you will have a great, you know, you will have a good culture. >> So you know, >> well, you know, it's interesting because you seem to have you've coined a term here, the culture pull score. Is that correct? >> Yeah. Yeah. Yeah. >> Could you talk to to us a little bit more

about what that means specifically? >> Yes. >> That kind of measures. >> Yeah. So, so that is the so that's the quantifiable measure of how healthy how strong um the organization's culture is that is built from the insights that are are gathered. So that is the you know that's the that's the that's the number that the organization has that actually is is able to give them a um technically a grading of of how strong and healthy their cotter is. >> Okay. And what kind of like variables is it go back to what you just said a little bit earlier is that what kind of variables specifically kind of pop up in there? >> So so that's the single measure. So you know how that is >> no. Yeah. But what yeah the things that like get together how do I say this? like what are

they measuring in order to make or gathering in order to make that measure point? Is that the right wording? Yeah, >> I'm looking for basically building out all the responses and all of that is then feeding in and influencing that single that that that single measure. So, you know, you get the you get a breakdown, you get all the, you know, the the actual responses, all the the individual questions and whatnot, and the narrative and everything else, but the those responses and what those are made up of feeds into that um kind of individual script. >> Interesting. Okay, that makes sense. Um yeah, just trying to get like more of a understanding of that cuz it's um once again definitely a little bit intangible, which I don't think is bad. just it's kind of curious to to know how you pulled that through. Um you

know I saw that you had a case study with a company called or with Hogan Group um where you helped test assumption where you helped test assumptions um sorry Stutter City test assumptions in a family run business. What um surprised them the most about what your AI kind of revealed versus what they thought they knew? >> Yeah. So I think you know I think you you when you're leading a business you have a you kind of have a gut feel. So you you think you know um you know where the challenges are. You think you know um you know >> where the pinch points are, what the issues are, you know what you where what you do well. You know you even you will even perceive yourself as how well do we think that we lead the organization. And um and so they they start

with all of these assumptions and and and then obviously you know we they deploy our tech, gather the responses, build a picture, presents that back to the to the organization, you know, and that either, you know, it either either it either affirms that uh they're right in some areas, you know, or or the other way, which is actually, you know, that actually their their assumptions are are wrong, you know, and and you'd be, you know, surprising how many organizations just are a little bit unaware of kind of what's really going going on within their organization, you know, and and I think we kind of started this, so we went mentioned this at the at the very start, which was as the CEO or even, you know, anybody who's in a leadership position, you know, when you are around people, you know, um, you know, employees,

you know, when you're in meetings, you know, whether you're interacting with people, they're always on the best behavior. So, you don't get >> you just you don't get a true picture of what's going on. So, only certain information actually is going to make its way up to uh to to you. So you you get quite a distorted picture about what's really going on within the organization actually when when when we say you know a lot of the survey options that you know you you get are yeah you're provided with all the raw data. So which means that you can technically track down you know who said what because you've got a person's all their individual responses. So you can build a pretty pretty accurate picture of who that person is. So you know we take that away because we don't provide the raw data. We

we are then just building that picture. So when we say anonymous we mean anonymous. So it gives people a level of comfort that actually when they are providing you know real honesty in their responses then actually get a more accurate picture. So, you know, if you I mean, if you think about the scenario, you know, CEO walks into um you know, a room and and asks a whole bunch of individuals, you know, enjoying are you enjoying working here? You know, what do you think the the responses are going to be? You know, not a single person is say I I actually I'm I don't enjoy working here and actually I'm currently looking for another job. Like that that is not going to be that that's not going to happen. And so I think as a result what you get is a is a distorted view

of the organization and that feeds into your gut feel. So you know that that's basically you know without giving away you know any kind of um bits of confidential information you know that they got a different picture compared to where what their assumptions were. you know, and that case in in pretty much, you know, any of the case studies would have always been the same, but every all all of the uh um you know, generally all assessments that we do, it's very rare to get that kind of direct mirror between um the assumptions of the leadership and then what's actually going on in the eyes, you know, through the eyes of the workforce. >> Yeah. Do you feel like it's I don't want to say always You're saying so it's distorted. Is it fair to say that those assumptions due to their experience are a

little bit rosetinted? Maybe like >> because like you know if everyone's always on their best behavior, you're not going to see the the bad vibes so to speak. Well, so I I think there's you know as as leaders you know what you know C CEOs founders you know you you are you are you know your DNA is about positivity. So you know it's a it's about overcoming the impossible. That's how you get a business off the ground. Um and therefore you you always believe that actually you're doing you know you're you're always doing the best things. However, you know, potentially that's, you know, it's not always having the right impact. Yeah, you might have the right strategy, but how you're treating people, how people are managed, how the organization is is led, you know, those those things can be and yeah based on the individuals,

but actually they will change over time and they will also change as the organization evolves because as it scales you can't have these kind of one-to-one sitdowns with, you know, kind of 100 people, 200 people, 500 people, you know, it's just it's just logistically Impossible. So, so actually, you know, you could even even if the CEO is consistent in all of their behavior and how they perceive the culture, as the organization scales, the needs of those employees will change. >> Yeah. No, that's totally fair. Um, I remember when I first started my own company and like the difference is at like a couple people versus the bigger it's gotten and and it's at a smaller scale. So, I can imagine it at those really large sizes and it I feel like you could get really it just changes so much. Um, you know, uh, kind

of going a little bit above and beyond kind of the surveys and the um, uh, the ba in the baseline, you know, lots of companies do employee surveys, right? And a lot of companies use AI. What makes your combination of those two things um the anonymous assessment and like AI analysis a little bit different from competitors in the a HR tech space? >> Yeah, I think the um I think what we've done is to we've you know we've we've created a standardized way uh to to assess. So, you know, there's um you you can't pick and choose how you want to analyze your organization's culture. Um what we've done is to say, you know, it's generic and as a result, it means that we can compare kind of organizations across different sectors, different sizes because it's all the same question set. Um and and as

a result because there is an element of standardization we can then bring that down bring the cost of that down so that actually it becomes more affordable. So you know it it I don't want to um you know don't want to use the word cheap but actually there's in in this space I think you know you you said it's um yeah culture is is can some feel kind of a little bit like you know it's it's it's an intangible um and so when there's an option to spend money or not then it's too easy to say yeah we can just spend them some money elsewhere. So what we wanted to do was to bring that in, create a generic product and then be able to push that at a price point that it becomes a no-brainer for an organization to really understand the culture they

have so they can go on and build the culture they want. >> Yeah. No, that's that's totally fair. Um, I just out of curiosity, you know, with everything that um you're doing right now, what are some of the new features inside of your product specifically that you feel like are um or things that you're doing that you're most excited about? >> Yeah. So I I I think it's the I think it's just the concept overall uh realistic and and and because you know kind of the in the way I mean you know you hear some of these horror stories you know kind of large they are government kind of organizations you know where they kind of run these sort of survey assessments and people put their responses in and then it takes six months to to get the results back. I mean, you know, actually

you just might not you just may you should have just not bothered. Um, and so I think for us it's about actually the speed of turnaround. So the ability to to get the data, analyze it, you know, again, because you're using AI, we can analyze that super quick. And that's you that's then back full written analysis and in someone's inbox, you know, within within a matter of hours, which means that you can take the information that you have, present the findings of that back to the organization, and then start with affecting change, positive change. So for us it's about the speed. So >> it's about the speed. Okay. Yeah. Um yeah, I mean that's fair. Like the longer that it's it's kind of sitting there and and kind of I I mean you know with culture I could imagine if it's going well could be

going continues to go well. But I also feel like if it's going wrong in some areas can get wrong in a hurry, right? Like and without proper like addressment of those things um you know it it can cause some real problems. Personally, I remember I worked at a marketing agency prior. Um, and there was this like overwhelming sentiment that it wasn't the same as it used to be as it was growing, right? The company kept growing, kept growing. there was like a rumor that got leaked um and then that was confirmed if you knew if you had like a paid subscription to certain like investment type websites that the company got bought out by a private equity firm and they said that they got an investment in like the internal email. So like they essentially just like didn't they didn't shoot straight with us right

that what had happened and it just felt like the vibes were different like every the margin was getting brought up all the time. And it was like a weird change and then it got to the point to where the rumor mill just got out of control and everyone's vibes were just and then people started leaving the company. Um myself included and not that I started my own company but other people were just like I don't like it here anymore. I want to go >> and I feel like that's the the issue of not addressing these things is like it can get bad quick. >> Yeah. I think I think >> cuz Vibes were good for a year like that I was there then it like then that announcement happens for a couple months it was questionable then they did a bunch of layoffs and I

and then the rumor mill came out when there was an article that was posted somewhere and you know somebody figured did like the reverse engineering is like oh my gosh we got bought up by private equity that's why got laid off not because we were doing worse right and um sorry anyways that that's my story and explaining an experience of like wow culture got bad and I don't think the leadership did anything to to >> well I think I I I think the trust is a massive influence on so when you know the example you just shared that you know when the the leadership were not honest um with the workforce um you know what people then knew I mean that is you know that that fundamentally has destroyed all trust So the culture would have taken a huge nose dive at that point because

there has to be trust between employee management you know employee leadership management leadership um and you you erase that sometimes that gets erased over time um and but I think what the example you've just show shared is that that is off a cliff you know that that is you know and and it's possible to come back from that. But actually, you you have to draw a line, admit that you made a mistake, you know, admit that you didn't you weren't fully um open about kind of what what had gone on, etc., etc. And and so you can come back from it, but actually if you if you don't do that, then you've you know, you have you just destroyed, you know, the the trust and therefore the culture is then in a nose dive uh going in the wrong direction. Yeah. No, that's um I

appreciate that insight. That makes sense. So from your perspective, what's kind of beside beyond the business metrics, what's like the cultural transformation that you're hope hoping to create in the broader business world, right? Like what what is the ethos of what you're doing here? >> Yeah. Yeah. So, we sort of set ourselves a target, you know, which was about helping 10,000 organizations build awesome cultures um because because we saw the power of, you know, having a you know, okay, not great culture, you know, and and then being able to transform that, you know, I saw how positive that was on kind of all the business metrics, but actually it just it just made for a better place to work and therefore you know which had an impact on you know the the lives of the people that you know that we employed and so we

want to help 10,000 organizations basically replicate that and the starting point is to understand the culture you've got. >> Yeah. Um totally fair. Uh I I think it's it's so valuable what you're trying to do personally. I think like just having spoken from experience just now like as you can tell like I think the company culture thing kind of like strikes a nerve with me and um you know it's it's very I'm very happy that you're you're doing stuff like this and helping people um maybe find the misses that they are um you know finding the misses uh that they they have in their system and improving it. And I I did have one funny question um in here. Um, so you're using AI to improve workplace culture at a time when AI is also disrupting jobs and um, isn't human, right? It's kind of

funny like non-human to help the human the human aspect. Has that is that irony lost on you or have you thought about that or what what are your thoughts? Yeah, I mean I think the I mean I guess I mean it's not it's not lost uh on me and I think um I think again you know you are you you're way further ahead I think in this in this in the states around you know the impact you know we we talk about it a little bit but it's you know we're not seeing it you know we're not seeing mass redundancies and and and things like this so you know what what we are doing is actually you know with the the kind of HR um and leadership consultants you know they really want to do this work because they they understand how powerful it is

but actually when they have to do this manually then they lose interest because you know they they are they people who like to strategize and then get involved in the execution they're not analysts you know they don't like analyze manually analyzing you know large amounts of data and this yeah gets dis it disrupts um it's expensive clients got to pay and so actually what this does is you know through the use of AI we're we're enabling uh consultants who really want to do this work to now be able to do it and offer it at their client to their clients to to provide real value whereas before they just didn't want to do it either the budget was just too um too excessive for the client. So they didn't want to client didn't want to go ahead or actually they just couldn't fit the time

in to be able to complete that analysis and etc etc. So so I think you know we are you know we're helping people in a small way kind of make the world a better place and and that you know whether that is for the fractional and HR consultants you know or for the organizations. So I think we're doing something that people are less likely to do currently, but AI has enabled it to be accessible. So, you know, I think that we're we're not putting people out of jobs, I think, at this stage, but I I totally get the point, you know, which is, you know, around >> No. Yeah. And that's fair. I don't think you're putting people out of jobs necessarily and I don't think honestly AI is in general right now except for some of big tech point was just like getting back

to the more positive which I actually you did a good job like leading me into that which I think kind of articulates how AI can actually help the human aspect of things right because a lot of people are concerned in in the matter of um you know it's like oh AI is going to get rid of um the human side of work but I don't know about that cuz I feel like a lot of work is kind of robotic you know it's a bunch like nonsense like responses to things that are pretty much like if then logic and then this kind of opens up time I think for people to be more interactive to do more in-depth things right um analyzing a huge data set right um for the average person it takes time right um compiling that data set asking the right questions takes

some time but being able to implement it on a human level I think is going to be freed up with this time that you're saving people you know Um, which is kind of the more important thing, right? Like who wants to read the data set? Like tell me what the data set says. >> And also that you know you you humans have bias. So therefore they will pick up >> Yeah. Yeah. Yeah. Yeah. Absolutely. >> Yeah. They will pick up one thing. Um and so I don't know you know let's say this let's say the people analyzing it you know have um had some experience of kind of sexual harassment. you know there's reference of that in the data set suddenly that is really going to heavily influence how how that person then interprets the rest of that data. So, so you know, so personal

experience is going to heavily influence actually the outcome and and the analysis and the direction that kind of any recommendations will will go through. Whereas it's the nice thing about AI is that it's entirely objective. So, you know, it doesn't have bias. So, therefore, you get a clean um view of what's going on within the organization. >> Yeah. No, absolutely. Um, and just kind of on a more personal note, obviously, um, you did make comments about, you know, how what you guys are doing and I think it's awesome, but just to kind of talk more about the industry at large a little bit. Um, I know she had a lot of good privacy stuff on there, right? Um, uh, like I believe SOC2, no, I saw ISO 27,0001. Yeah, >> 20 Yeah, sorry. 20. Is it always 2701 or 27,0001? 27,000 a month. >> Oh,

okay. >> It's just so it's the codes are funny. And you know, you have um it seems like anonymity is like a cordier model obviously um with getting more with AI getting more powerful. How do you kind of navigate um the line between useful insights and potential privacy concerns? Not only for your own company, but just maybe in general with everything going on in AI kind of is my main question. Right. >> So, so I think you know there's I mean there are two things in there. there's there's the data that is shared that then influences the the models themselves, you know, so pretty much all the stuff that we do on chat GBT and things like this, you know, all all goes in to feed the feed the beast, so to speak. Um and and so actually, you know, you have no privacy. Yeah.

as as an individual you you are everything that you're feeding in you are um you know is is being used to train I think when organization like ours you know when we're utilizing AI actually because of the corporate scale and the corporate nature you know we we're actually keeping our data safe and within the confines of of our systems and it is not going in to to train um any external models and and things like this. And I think I think especially in the UK, you know, we have quite a strong focus on on data security and data privacy. And you know, that's that's a level of comfort that we um that we we kind of had to do, I think, because corporates expect it. So you know to have to have a focus on information security you know we we we we built we

built information security into you know how we designed the product and actually all the systems and the architecture and and everything else. So you know it over here in the UK that is really important and I think that's always a question that comes up which is where does our data end up? So, you know, we can confidently say it stays within our systems. Um, you know, and it's not it's not being leaked into training any models or uh or any of the external um kind of systems. >> H and um it's interesting to me because you said a comment which I feel like I've made a joke at for a while because the marketing agency I I worked at, right, it was a marketing agency. So I worked at Google. They're B I worked sorry I did paid did paid Google ads um for them

and you know obviously there's always the running joke that like they can hear your phone right they can hear you which I don't think is it's up in the air on whether that's true for me personally but I don't think it is. Um but like for for example know I've been making the joke for a while that like your d no one's no one's like like you know anybody that you know that's like I am all about data privacy as an individual. I kind of chuckle because I'm like, you know, the cat's been out of the bag since like 20, I don't know, 13, 14. I'm like, what are you talking about? The second a was like, you kind of you've been tracked non-stop for a while. Um, and now with the adventation of people knowing your conversations uh in these different AI models, if

you have topics of interest, you tend to go there consistently. You're training the models on your data. I totally agree with you. I really do think cats out of the bag, right? Kind of on >> And I agree. And I think I think as a, you know, as a as an as an individual, you know, then we're free to, you know, use Facebook, use Instagram, kind of WhatsApp, you know, any of the systems and and whatever. And, you know, you are you are exposed. I think in that way. I think organizations are extremely sensitive about their data, you know, and and and therefore and so there, you know, and and and and kind of rightly so. Um because what they they have to know where their data is being stored, how it's being looked after, you know, and um and you know and what happens

to it, you know, and and so I totally get the fact that you know, you sitting in meetings, you've all got your phones and whatever and you know and like you said, I actually do think that uh yeah, your phone is listening to you and uh uh and listening to the conversation because actually that is then generating ads and you know various other things that you know you're seeing. Um and you can test that out uh kind of anyway just to see how bizarre um things that you can talk about as a one-off and then how quickly they start coming through on Google ads and uh and and things like this. But actually I think as an as an uh in a corporate sense they just want to know we're going to provide you with this data where's it going what are you going to

do with it? So, you know, all organizations are super hot on that topic, especially over in in the UK. >> Yeah. No, absolutely. And yeah, as companies, obviously, I think there's something you can do about it, but I just think about the personal aspect. >> You got to calm like not saying people have to calm down, but sort of saying like >> you you haven't cared since you had the iPhone and you've had the iPhone for a while. And then I know I had some friends who was it was hard for them to hear this. They were like, "Hey, I don't use Apple." I think Apple's probably the best phone when it comes to um security from my understanding, at least that I know. I could be totally wrong here, but they're like, "Oh, no. Don't don't use Apple. Use Android." And I laughed and

they're like, "What? What is this?" Like, obviously, this is more significant. I'm like, "Who owns Android?" And they go, "I don't know." I'm like, "Google? How how does how does Google make all their money?" It's like because it's not from it's it you know those two things you have to scroll past every time when you Google something. Yeah. Anyways, um it's one of my little uh rants about privacy, but I appreciate your insight there. So, on a more positive fun note, just to kind of close it out, obviously everyone has um their own interests in AI and kind of how they use tools and stuff. Tell me a little bit about your favorite thing to use. Um, personally when it comes to AI, obviously have your own product, that's great. Um, but what is your favorite personal tool that you use on a day-to-day basis

to get your work done or even for personal use? >> Yeah. So, I think the you know, I use I I I use I don't I don't tend to use specific things for specific kind of actions. So, you know, for me, I kind of been super generic. You know, Chach GBT is the the one that, you know, I kind of I guess I grew up with, if that's the right phrase. Uh, you know, that was the first one out. And and actually, and that's the kind of thing, my kind of go-to thing for for most things. And if if I struggle or if I start seeing flaws within that, then I'll go and seek out other things. But, you know, for me, you know, it's a bit of good old chatbt. >> Okay, cool. I don't know. Some people like uh certain ones like one

I'm looking right now right now is uh I found out about it's called crisp AI. You can like obviously there's a lot of phone call recorders or um meeting recorders, but this one's really cool because it can um enhance the background like remove the background sound. So there's about like a noticeable like 0.5 7 second delay, but it like always cancels the any background noise on meetings. So you can kind of have like a ad hoc hectic meeting on the go, right? and it'll do a way better job than, you know, like something like these will do for blocking out the background noise. So, that's my personal one right now. Um, all right. Well, tell everyone where we can uh find you and have if you have any closing remarks, let everyone know. >> Yeah. So, find me on LinkedIn. So, James Leley, pretty unique

name, so uh you'll probably be able to get my details uh relatively easily hopefully. Dmitri, can we can we kind of put my LinkedIn profile and whatnot within um >> the description? >> Yeah, cool. >> And uh and then the website is uh cultivative.com. >> So again, we'll put the uh details in so that um hopefully you can click through. But um yeah, be uh great. Please come over, connect, and um check out our tech. >> Absolutely. Okay. Well, with that being said, everyone make sure to go to cultivative.com just so you know how that obviously it's in the link is in the description down below, but it is culiv 8 tiv.com. That's cultivate.com. Thank you so much for watching this episode. If you liked it, make sure to hit that like button, subscribe, leave a review. James, leave a review. We really appreciate that.

And um with that being said, we'll see you all in the next one. Thanks.