Adam Larson: 00:04

Welcome to Count Me In. I'm Adam Larson and today we're talking about the human side of AI at work. I'm joined today by Dr. Gleb Tsipursky, CEO of Disaster Avoidance Experts and the author of The Psychology of AI Adoption Network, From Resistance to Results. He brings a fresh perspective on how automation is reshaping accounting and finance, not just in what we do, but in how we feel, connect, and lead through change.

Adam Larson: 00:31

We'll dive into real world examples of AI saving time in everything from reconciliations to board reports. But we'll go deeper, exploring why the biggest challenges aren't technical, but psychological. We'll break down the fears, identity worries, and even the stigma that can surround AI tools and share strategies leaders can use to build trust and a workplace culture where people feel safe and ready for the future. So, if you're curious about making AI work for both your business and your people, this episode has insights you need to move forward with confidence. Let's get started.

Adam Larson: 01:13

Well, Gleb, I'm so excited to have you on the Count Me In podcast. And today, we're going to be talking a little bit about concepts from your book, The Psychology of the AI Adaption at Work. And it's great because everybody is rolling out AI right now. And I feel like we're just getting to a point in the in the rollout process that people are realizing, hey, this is affecting people. This is affecting how their work, this is affecting how they're doing things.

Adam Larson: 01:35

And you've spent a lot of time watching companies and inside companies watching them roll out AI. So maybe you can walk back to some of the use cases you're seeing most often, especially in the accounting finance right now. Like, what are you seeing out there as people rolled it out?

Dr. Gleb Tsipursky: 01:48

Great question. So I was just doing training for insurance company. That's the insurance company of last resort in a sizable Midwest state. So it's a fair plan, and obviously, they do a lot of accounting. And they were rolling out...

Dr. Gleb Tsipursky: 02:04

They were switching from Microsoft GP to AP Flexi. So from one accounting system to another accounting system. And what they need to do in doing that is for each year to export their data, all of the claims they paid, all the invoices, all that stuff in one spreadsheet. And then transform it to a different type of spreadsheet with different columns, different headers, and so on, different data to upload it into the new system. And so during the workshop that I was doing for them, they brought up this case study, and I asked like, okay, like, how can this be done?

Dr. Gleb Tsipursky: 02:43

And so while they were working on their own tasks, so as part of the workshop, when I do a training, I have people. I train people on how to use AI tools, and then I have those them spend some time building the AI tools. And they first do some more simpler AI tool builds using prompts, and then we move on to more complex tools using agents. So during the part of the workshop that involved the simpler AI tool building, which they were doing on their own, and I was providing them with coaching. While they didn't need for me for coaching, I quickly looked up these systems.

Dr. Gleb Tsipursky: 03:18

They quickly... I asked them to send me the sample spreadsheets that they... Not the sample. The yesterday's spreadsheets that they spent about three days transforming one year into another year as samples to use. And then I put them into Claude, and I worked out what it even meant because I have no idea what the what what it means to transform from Microsoft GP to AP Flexi.

Dr. Gleb Tsipursky: 03:42

I worked with Claude to figure out how to transform one into the other. And then while they were still building, I created a new spreadsheet, a template spreadsheet that would enable them to just do this process automatically. And so it took about thirty minutes now to do what they spent three days doing previously just for one year. And so thinking about that time that you spend. So just to exporting from one system, and it's not something you do every day.

Dr. Gleb Tsipursky: 04:13

But when you need to do it, that's a ton, a ton, a ton of work for all the previous years. So it takes three days and you export into new one. And now they were able to do it so much more efficiently and so much quicker to do that major task they were working on. And so this is just an example of a task that CFOs have to occasionally face. That's a lot of hassle, and it saves them a ton of time.

Dr. Gleb Tsipursky: 04:39

That's one task, and that's a big project. But let's talk about reconciliation. So reconciliation is a task that has to be done, of course, every month, and has to be done regularly, and that takes people quite a lot of time. And during that workshop, we also set up a reconciliation system, where they just put in all the information and it reconciles it and they close the books and everything is fine. And so that what previously used to take them a bunch of time, now takes them like 85 less time to use to do that reconciliation process.

Dr. Gleb Tsipursky: 05:16

And that's a more of a daily, everyday task. Not everyday task, but every month task that they have to do. And now it's helping them do that. So this describes the span of AI tools from your daily everyday tasks with financial systems to huge major projects that were a real, you know, Peter in the past that were a real challenge for people to do in the past, took a lot of time, a lot of hassle that you couldn't use AI to do. And we're not even talking about like all the reports, financial analysis, and financial modeling that you can use AI to do.

Dr. Gleb Tsipursky: 05:50

And do that financial modeling and then create reports based on it for the board. That was another activity that we worked on that building, like board reports that they need to produce every quarter. And so that's another activity where you combine financial analysis with textual production. So here, the AI is not producing Excel spreadsheets. It's producing a textual report based on financial analysis and modeling.

Dr. Gleb Tsipursky: 06:18

That's another use case. And so there are so many more use cases. That... That's just from one workshop. I can talk about tax preparation and so on from another workshop that I did a few days ago where there's a lot of use cases.

Dr. Gleb Tsipursky: 06:32

But let's stop there and see which direction you want to head with.

Adam Larson: 06:35

Those are great use cases, and and it's interesting as as people adopt it more and more. I guess my question to you is what effect is that having on the employees? Because obviously, they're getting... They can do things they were taking, they're doing... They were working on before faster, like the use cases you just gave, something that took, you know, days to do as it took a couple hours.

Adam Larson: 06:55

What effect is that having on folks? Because as we're taking out the busy work, we have to fill that work with other things, and what does that look like from an employee perspective?

Dr. Gleb Tsipursky: 07:04

Sure. So let's talk a little bit about some of the challenges with adoption. And so this is why my book is called The Psychology of AI Adoption Network from Resistance to Results. And it's a peer reviewed book. It's out with Georgetown University Press.

Dr. Gleb Tsipursky: 07:18

And what I did in that book is this is over a 100 consulting projects, which each of them of course involve finance to one extent or another. And some of them actually purely financial firms, like I talked about tax preparation and so on, accounting firms. And what I did was I ran focus groups. There's over 600 focus groups, many, many thousands of survey responses, looking at what kind of obstacles companies are running into with AI adoption and how to address those obstacles. And folks might have heard that there was a recent research out of MIT showing that 95 of AI pilots don't show return on investment.

Dr. Gleb Tsipursky: 08:01

And this... So they don't show return investment of the resources compared to the resources used to try to adopt AI. Now why is that? Well, because the typical approaches to technology don't work well with AI. So when you're thinking about a new technology, like, let's say, transforming to a new accounting system, it's a lot of hassle to do that.

Dr. Gleb Tsipursky: 08:23

It's a lot of hassle to learn to do that. It's a lot of hassle to learn the new system, to even get your data from one system to another. It's a lot of trouble to adopt and learn. AI tools are not like that. They are very easy to learn and adopt.

Dr. Gleb Tsipursky: 08:37

You can ask them how to do things. Like, had no idea what Microsoft GP or AP Flexi was. I just asked the AI tool and I gave it the samples and was able to do things once I described the workflows appropriately. And so this is a tool that you can easily leverage once you learn how to use it effectively. But a lot of people don't want to use it, and so you have problems that are not the result of technology, but the result of psychology.

Dr. Gleb Tsipursky: 09:07

So the previous problems, the previous patterns that leaders have that are pattern matched to AI... To technology adoption don't work with AI adoption. The change management issue, the resistance issue is very different. And there are three big blockers that I see with AI adoption. So the first big blocker is not the hassle of learning a new system, not the difficulty of getting into it, not not the stuff with people being lazy and not wanting to, like, change their workflows, but it's about fear.

Dr. Gleb Tsipursky: 09:35

So the first one is fear, fear and anxiety. People are worried that they'll replace themselves. Like you're saying, Adam, what will people do after they get so much more efficient? They're worried that they are training a tool that will replace them. And I talk about that in chapter six of my book, The Psychology of AI Adoption at Work.

Dr. Gleb Tsipursky: 09:53

That's the psycho... And one of the psychographic profiles that I identified in the book is the AI alarmists. So these are folks who are really worried about AI replacing them, AI taking their jobs. So that's one. Two.

Dr. Gleb Tsipursky: 10:08

So the second big obstacle is identity theft. People aren't threatened by going from one AP, one accounting software to another, or one CRM to another, or one ERP to another, like AI technology adoption. They're not threatened by it, by having to look up and reconcile bills in one system versus another. But they feel threatened by a tool that can automatically look through and reconcile bills and do a great job at that. They're threatened by a tool that can do an excellent financial analysis and prepare a summary for the board.

Dr. Gleb Tsipursky: 10:45

They're threatened by a tool that can look through invoices and find mistakes and find issues and point them out. They're threatened by a tool that can go through a client's tax tax forms for the past year and then prepare a great tax report for this year, finding all the ways that the client could save money. They feel threatened to their professional identity, to who they are. Might be less afraid of losing their jobs, they feel threatened to who they are as they get sense of meaning from their work. And they're like, well, if I don't do this, this is not going...

Dr. Gleb Tsipursky: 11:19

I'm not going to have a sense of meaning. So that's the second group. Again, in chapter six, it's going to be the pragmatic resistors. So look those up, the pragmatic resistors. So two groups.

Dr. Gleb Tsipursky: 11:31

Those are the groups, then emotions that inhibit individual adoption. There's a third emotion and a third group that has to do with group adoption. And this is about people who feel shame, who feel shame about using AI tools to do this financial analysis, to do reconciliation, modeling, invoicing, transforming to a new software. They feel ashamed of talking about this topic, about talking about how they're using these AI tools to get all these things done. So for example, I was doing a training literally yesterday for a group of executives, and there are eight executives in the room.

Dr. Gleb Tsipursky: 12:07

This was a mastermind business group of executives of mid sized firms, and we're talking about AI adoption at their firms. One of the executives said that, shared a story about what happened to him just a few days ago. So each year, they do a sales analysis of their best client for the past year, their biggest client for the past year. So the VP of sales would prepare a presentation for all the other executives and present all the context about how they came to it, all the impacts and so on, what lessons learned and so on. And previously, what it took was prepare, it took about the executive of VP of sales about three days to prepare this presentation in previous years.

Dr. Gleb Tsipursky: 12:50

Now, this time after the presentation, which went great and went swimmingly, executives or other executives were pleased. The VP of sales privately came to the CEO and said, hey, you know how it usually takes me about three days to do this? Well, what I did this time is I handed off a task to my executive assistant, and it took him one and a half hours to pull together this presentation from all the information and examples of past presentations and so on. And so it wasn't even he who pulled it together, it was his executive assistant. But he said, I don't want you to tell the other executives about this because it feel...

Dr. Gleb Tsipursky: 13:26

It feels like I'm cheating. And they'll feel and think I'm lazy. And so it happens at the very top levels of the organization, the social stigma, the shame. And of course, it percolates throughout the organization. It's very natural that people don't talk about it.

Dr. Gleb Tsipursky: 13:42

And so what happens is that people individually are way more productive, but they don't talk about their supervisors, they don't talk about their teammates, and so they end up just spending the additional time playing on Facebook. And so that is another big problem. And so this... These are the people who experience shame and social stigma, and I call them adopters. They are adopting, but they're reluctant adopters, they don't talk about it.

Dr. Gleb Tsipursky: 14:09

So you need to address and understand and address those three big issues, those three big psychographic profiles, and the three big emotions in order to adopt AI effectively.

Adam Larson: 14:21

How how do you start? Let's look. What's the first step to addressing those issues? Because each of those issues hit people at different levels. Like, some of those issues might hit people at high levels.

Adam Larson: 14:31

Some of the other issues might hit people at lower levels. And it... It's like you can just do one training and say, hey. If this hits you, let's talk Like, about do you address that in in an org... As as a leader?

Adam Larson: 14:41

How do you address those things?

Dr. Gleb Tsipursky: 14:43

Yeah. So each of those psychographic profiles needs its own handling. And I talk about that in chapters seven, eight, and nine. So chapter six is about this. The profile seven, eight, and nine are about how to address them.

Dr. Gleb Tsipursky: 14:53

So let's talk about them in turn. So the AI alarmists, how would you address them? The first step, if you can do this, you should do this, is to tell them that you won't be cutting jobs because that you're improving company efficiency due to AI. So just because you're more productive doesn't mean you'll be cutting jobs. Instead, you'll focus on growth.

Dr. Gleb Tsipursky: 15:13

And this is definitely a viable step. So we have research coming out, recently a peer reviewed study showing that companies that are using AI effectively compared to others in their industry. So accounting companies and any other companies are growing 10% faster in their headcount, and they're growing their top line and bottom line even faster. They're taking market share in other words, away from other companies that aren't using AI effectively. They're having more revenue and more profit compared to how much headcount they're adding.

Dr. Gleb Tsipursky: 15:44

So they're not adding as much costs, they're adding more revenue and and profit as a result, and they're growing. So you can definitely... Your company is on the position where they can take market share, they can definitely follow that strategy. So I recommend following that strategy and saying that you'll be hiring less people or no people, but you will be focusing on growth rather than cost cutting. So that's one, if you can do that.

Dr. Gleb Tsipursky: 16:10

Most companies can, some can depending on like if you're an accounting company in a very limited market and you're dominating the market, might not be able to. But most companies can or most companies can make that commitment. But the commitment that all companies can make, that's a carrot commitment, is more of a stick commitment than saying that, hey, if you learn how to use AI effectively, your job will be safe and secure. Now, this is just the reality of the situation. You'll be much more effective and productive if you're going to be using AI effectively and successfully compared to the other accountant next to you who is not using AI effectively and successfully.

Dr. Gleb Tsipursky: 16:48

And so you'll just be... This is absolutely a true statement. Every company can make that commitment. And so that commitment helps flip the script for AI alarmists. Right now they're thinking, I'm training I'm training my own replacement by using AI.

Dr. Gleb Tsipursky: 17:04

Well, I need to get them to think is that, hey, by not using AI, I will be replaced. That is the script flip that you need to have. And it helps when you have the carrot of making a commitment, preserving jobs, but you definitely need a stick of, hey, your job will be safe if you will use AI effectively. And naturally the other side of that is that if you don't use AI effectively, you will not be successful in this company. So that's for the AI alarmists.

Dr. Gleb Tsipursky: 17:33

Let's talk about number two, the pragmatic resistors. What they feel threatened by is not job loss, but they feel threatened to their identity, their professional identity of the tasks they really like to do, and they find meaning. So the mistake that financial professionals make, accounting companies make is trying to automate the tasks that people really like to do. And that's a problem. So you don't want, let's say, you're a tax preparation firm to do the...

Dr. Gleb Tsipursky: 17:58

Let's say, have initially have AI find ways that clients can save money and like finalize the tax... The taxes, do the taxes for the clients. Because that's what people like to do and they feel that's what they're professionally proud of. You don't want to do that. That is not what you want to focus on.

Dr. Gleb Tsipursky: 18:16

Instead, a survey and ask people, what are the tasks that are the most hassle for you? What are the tasks that you hate, that you find frustrating? Where do you have to search across many systems and pull information together in order to do the things that you really like to do? Like let's say, having to find all the information, like communicate with clients and tell them that, hey, this is the information that's missing from your tax report, from your taxes, and please send me this information. Nobody likes to do that.

Dr. Gleb Tsipursky: 18:43

So this is something that's very easy to get the AI to draft those emails for you. And then you'll just check them over before you send them. So that's a use case that I was doing with one tax preparation firm recently, for example. And so that... And there are many, many other use cases like this for accounting professionals that they don't like to do.

Dr. Gleb Tsipursky: 19:03

Nobody likes to do them. And so those are the things you need to focus on automating. And by automating, I mean, creating prompts that are going to be prompts that people can use to automate those tasks in AI and training your team on using those prompts effectively. So that's going to be the way that you address the pragmatic resistors. You need to have the survey, figure out what tasks they hate to do, and focus on automating those tasks.

Dr. Gleb Tsipursky: 19:31

It might not be the most efficient thing for the company. It might be more efficient for you to get to have the AI tool not only pull together all the information for a tax, but also prepare the taxes and have your tax preparer just review it. But in the short term, it might be less efficient, but in the long term, you know, you go slow to go fast. In the long term, it will get people to actually adopt the AI tools for the things that they hate doing. So maybe in in the beginning, you'll automate 30% of their tasks.

Dr. Gleb Tsipursky: 20:01

Eventually, they'll expand and they'll do other tasks using AI tools because they see how effective and quicker AI tools are. And it'll go into 40%, it'll go into 50%, but start with a 30% they hate. And so that is where you want to start. So that's going to be the pragmatic resistance, the second group. The third group, the social stigma, the shame.

Dr. Gleb Tsipursky: 20:22

You need to, as a leader, really focus on addressing the modeling. So that leader who the VP of sales was like, oh, don't talk about it. You need to talk about it. You need to be proud of it. The CEO needs to talk about how she is using these tools and how she is proud of using these tools and how they're saving her time for her presentations, board reports, so on.

Dr. Gleb Tsipursky: 20:42

You need to set that culture for other organization, need to talk about to other executives, to all of your subordinates to be proud and model the use of these tools. So that's one out of three things you need to do. The second is provide the training. So this training is... It's gonna address the pragmatic resistors as well as the reluctant adopters.

Dr. Gleb Tsipursky: 21:02

Because what you do at that stage is you set a baseline of like, okay, we agree that we're using AI to do all of these things. And so now people know that AI is being used to do all of these things, so that helps address the social stigma and shame of using AI. So that's two. The third thing you need to do is have a public channel where people share about their AI accomplishments and you praise and reward them for it. So have a Teams channel or a Slack channel where people can talk about, hey, I did this thing using AI.

Dr. Gleb Tsipursky: 21:36

Here's the prompt for it. And I did that thing using AI. Here's the agent for it. So talk about how you're using AI effectively, encourage people to use AI effectively. And then the leader needs to praise them and ideally have some kind of reward for prompts that other people can share, can use to improve their efficiency.

Dr. Gleb Tsipursky: 21:57

So the way that you incentivize people essentially to do this, that's the word language that the company speaks in money. But the leader needs to speak in words at least, praise them. Of course, not all companies can do that, but if you can have a small amount of reward, that's great. So those are the three things you need to do for the reluctant adopters. Leadership modeling, baseline training, and public channel sharing and praising of their activities.

Adam Larson: 22:23

As you were explaining each of those, it... The underlying concept that seems to be consistent with all of those is that idea of safety, you know, safety in my job, feeling safe about what I'm doing. And, you know, when disruption comes, disruptors like AI come into our workplace, that seems to be the biggest underlining factor. You know, can we talk a little bit about the psychology of safety a little bit, you know, and especially when it comes to implementing AI and helping deal with these, you know, helping work with these employees who are are the different adopters that you mentioned? Sure.

Adam Larson: 22:53

So you need to really focus on the psychological safety element of it as you talked about,

Dr. Gleb Tsipursky: 22:59

as you highlighted, and have that concept in your head. That people need to learn to... That they are safe using AI, that they will not be replaced. That's their jobs will not be replaced. And that they are...

Dr. Gleb Tsipursky: 23:13

Especially the case is if they're more successful using AI, they're safer. That they will be more guaranteed to keep their job. And even let's say something happens to the company. Of course, if they have the AI knowledge, they'll be safer elsewhere. They'll be more able to find a job elsewhere.

Dr. Gleb Tsipursky: 23:30

Then for the pragmatic resistors, when you need to understand that they feel a threat to their professional identity, So their safety will come from them not automating tasks that are central to their professional identity. And so they will feel safe when they automate the manual tasks, the annoying tasks. And AI is this incredibly flexible tool. It can be used to do almost anything in the white collar digital world. And so you can definitely focus on those things and go slow to go fast.

Dr. Gleb Tsipursky: 24:00

And of course, the social stigma, has to do with safety. How safe are you to talk publicly about your usage of AI and you need to reinforce people using it effectively and getting praise for it. So safety is definitely critical for all of those folks.

Adam Larson: 24:17

It really is because when you're... When things disrupt your work, you know, you have to you have to find a way to get those people to feel safe again so that they can be productive again, which is important. And I appreciate how you broke down each of the different groups of people because we all kind of find ourselves in one way or another within those groups as we're trying to

Dr. Gleb Tsipursky: 24:35

Yeah.

Adam Larson: 24:35

Roll this out. And it and it can't be easy, you know, as a... From a leader's perspective to have the different groups and also trying to learn yourself and you might fall in one of those groups as a leader. You know, so what does that look like from

Dr. Gleb Tsipursky: 24:48

a leader's perspective? So a leader needs to, of course, figure out not only her or his own usage of AI, but how to channel and influence other people effectively. So they need to have all of this in their head about the psychology of AI adoption, what's going on, what are the concerns. And then I go in-depth into in the chapter seven, eight, nine about the ways to address each of these groups. But of course, leader needs to be self reflective and identify what are their own emotional blockers, which is the question that you're asking.

Dr. Gleb Tsipursky: 25:22

So if they are reluctant to use AI, what are the emotional blockers that cause them to be reluctant? I've definitely seen leaders who are... They're less about the AI alarmist. I haven't really seen much of that among leaders, but I've definitely seen leaders who feel proud of the activities they're able to do, like use... Create a board report and not wanting to use AI for that even though it saves them a great deal of time.

Dr. Gleb Tsipursky: 25:47

And they can just like tweak it and evaluate it and improve it over time. Or that they feel like the leader who I talked about earlier who felt shame, social stigma around talking about how they're using AI. And so that needs to be a culture change. So they need to change their culture internally. They need to internally within themselves, meaning change to get that mindset shift to saying, okay, I understand that this is something I feel proud of.

Dr. Gleb Tsipursky: 26:14

But this is not the skill of the future. Preparing a board report from scratch is not the skill of the future. The skill of the future is not generating the initial content. The skill of the future is evaluating it, the quality of it, and editing it, and getting it into a good shape. That's the skill of the future for all sorts of activities.

Dr. Gleb Tsipursky: 26:31

For whether it's a reconciliation, whether it's a tax preparation, whether it's preparing a board report, or many, many other tasks. And the same thing for social stigma that they need to get on the same page with other members of the leadership team and discuss how to address the social stigma through leadership modeling. So leaders need to understand that. And it's it's a very tricky issue because another member... Another leader from the business group for which I presented was talking about how they had a change recently in their company where previously the executive, the CEO was reluctant, not reluctant.

Dr. Gleb Tsipursky: 27:09

He would feel like, oh, using AI an AI tool is just cheating. It's not like you're not doing your best and so on. And now that he discovered Cowork, he realizes how powerful Claude Cowork is as a tool and how much it's able to do. And he's like, well, yeah, we we really need to use this tool. We really should not be thinking about it as cheating.

Dr. Gleb Tsipursky: 27:28

But he himself was reinforcing that message earlier, that negative message. So this really needs to be a change from the top level down that you need to change that. And if you're a mid level leader, you need to talk to your CEO about changing that. And if you're a top leader, you need to change that culture throughout the company.

Adam Larson: 27:45

Yeah. It really feels like everything you're talking about feels like it needs to be a culture shift. So it needs to be organization wide. You can't just implement it in your small team. If you have a team of people and you're doing it, in order for it to be successful, it needs to be a company wide culture.

Adam Larson: 27:59

And and what are some of those first steps as somebody's trying to look to change that company wide culture? You know, you've talked a lot about, you know, the different groups is like that, but you're changing the company. Call... It's not an easy... It's not an easy thing to change.

Adam Larson: 28:09

It's not something you can just say, okay, next week we're changing the company culture. It doesn't really work that way.

Dr. Gleb Tsipursky: 28:15

Yes. I need to get on the same page with other executives. That's the first step. So I often... I begin my engagement with the company with a facilitated leadership discussion.

Dr. Gleb Tsipursky: 28:23

So it's a leadership discussion about where we want to see the company in a year from now in their AI adoption policies and their AI adoption culture. And then how do we get there? And so that combines talking about all the three elements that we talked about before for the AI alarmists. You need to change your communication and your commitments around jobs. And so you can make a commitment to that, not letting people go, but you can definitely communicate about and make commitment about who will be let go if people are let go.

Dr. Gleb Tsipursky: 28:57

So that's a communication issue and the commitment company policy issue. That's one. Second, we talked about the survey. So having a survey and getting that information and providing training, not on the tasks that people value, but on the tasks that people hate. That's going to get you much of the way there with the pragmatic resistors.

Dr. Gleb Tsipursky: 29:17

And then the leadership modeling and the training, the same thing that for the pragmatic resistors, plus the synchronous communication and reward and praise for the ones who are the reluctant adopters who feel social stigma and shame. And that's a good order to go in because communication is the easiest thing to change. So how you communicate, that's the easiest thing. Then it takes more effort to do the training, of course. And then communication and leadership model, know, the easiest thing to change.

Dr. Gleb Tsipursky: 29:46

Then you have the leadership modeling and the training, and then of course, setting up institutionalization for various channels of communication later onward. So those that's the order that I would approach. And I would say that having the first thing is for the leaders to get on the same page with the facilitated leadership discussion.

Adam Larson: 30:03

Gleb, thank you. This has been, you know, this has been a wonderful conversation. I figured, you know, as we kind of wrap up the conversation, what's maybe one mindset shift that you hope someone would have when they're walking away from hearing this conversation?

Dr. Gleb Tsipursky: 30:17

The mindset shift that they should have is that it's not the technology. It's the psychology. So previous technological adoption, the difficulty was with the technology, learning it, transforming to it, adopting it. Yeah. With AI tools, they're super easy to adopt once you have a mindset shift and you learn how to use them.

Dr. Gleb Tsipursky: 30:34

It's not the technology. It's the psychology. The mindset shift is the real difficult part. And there are different people with different mindsets talking about the AI alarmist with the fear of anxiety, the pragmatic resistors with identity threat, and the reluctant adopters with the social stigma that are causing the problems that we talked about with ninety five percent of AI pilots not showing return on investment of... And for according to MIT.

Dr. Gleb Tsipursky: 30:59

And so these are the issues that financial professionals, financial leaders need to think about addressing. It's not typical for them to think about people's psychology, but they really need to because it's not technology. It's a psychology.

Adam Larson: 31:12

Yeah. That's awesome. Well, thank you so much for coming on the podcast and sharing your insights. I know that there's so much more we could have gotten into, and I encourage everybody to check out Gleb's book. There's links in the show notes.

Adam Larson: 31:22

And, you know, if you hear this on LinkedIn, you know, engage in engage in conversation. Keep the conversation going because we're all walking through this together. So thank you so much for coming on the podcast today.

Dr. Gleb Tsipursky: 31:31

And thank you so much, Adam, for having me on the podcast.

Announcer: 31:36

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