The AI Advantage That Can Transform Your Company With Dr. Gleb Tsipursky

Frank Cottle [00:00:45 ]: Gleb welcome to the Future Work podcast. Really excited to have you here. I know we’ve spoken on and off for a few years now, covering a variety of topics, and I know you’re an amazing contributor to all work in some of your written materials. So I’m very excited to have you here. And our discussion today is about the future of work. And a topic that comes up, or oftentimes, is people say distributed work, remote work. Could you define the differences between the two of them because they are quite different? Really? Sure.

Dr. Gleb Tsipursky [00:01:24 ]: And thank you again for having me on the podcast. Really appreciate it. Frank. So distributed work and remote work, they are different things. Remote work is when you work outside the office. So you work outside the office, whether from your home, work from home or from a third place, like a cafe or something like that. Maybe a coworking space, but not one that your company are in. Distributed work is when you’re working separately from your teammates. You might be working from home. You might be working from a cafe or a co working space. You might also be working from your employer’s workspace, but your team members are located elsewhere. Let’s say you’re in Texas and your team members are in California and New York.

Frank Cottle [00:02:12 ]: If you were part of a, if you were working remotely, wouldn’t you by default, be part of a distributed work group then?

Dr. Gleb Tsipursky [00:02:20 ]: Absolutely. So remote work is fully encompassed within distributed work, but distributed work also includes people who are working in the office from their company’s office, but their team members, whom they’re working are working elsewhere, not in the same office.

Frank Cottle [00:02:41 ]: Got it? Got it. Well, there are so many shifts going on in the marketplace right now, the way people are working, that we’re seeing, and I don’t think it’s going to stop. I think we’re going to continue to shift. What trends, what major trends are you seeing from the larger clients that you consult with, which is who’s who of Fortune 100. But what major trends are you seeing and where do you forecast those trends are going to go in the future?

Dr. Gleb Tsipursky [00:03:12 ]: We’re clearly seeing that companies overall are heading toward hybrid work, meaning spending some time in the office and spending some time working from home. So that’s terminology. Another term, hybrid work.

Frank Cottle [00:03:29]: Is there a percentage shift that you see that? Because we say people are going that direction, but is it 10% of the workforce, 20% of the workforce, 100% of the workforce? What do you see in terms of the magnitude of hybrid work?

Dr. Gleb Tsipursky [00:03:48 ]: So there research by the Scooplex index showing that about of all these companies, something like maybe 70% of large companies. So for example, they just had a report coming out on the tech industry and large tech companies, 76% of them have a hybrid structure, where there are some days people are working in the office and some days people are working from home. The largest companies, not all the largest companies. So Nvidia and Microsoft, for example, the two really large, huge companies, probably the largest in the world, actually have more flexibility. They give employees a lot of flexibility to work where the employees feel best. But other large companies, like Apple or Xerox or something, other companies, Allwork.Space recently asked for hybrid work only. So that’s where we’re seeing more large companies come. By contrast, smaller companies, a large companies, I mean, 25,000 and over small companies with 500 employees and less in the tech industry, over 90% of them are fully flexible, meaning employees can work wherever they want.

Frank Cottle [00:05:13 ]: Excuse me, is it whenever they want to work wherever they want? Wherever, but anytime. Any place.

Dr. Gleb Tsipursky [00:05:21 ]: I’m not sure about any time, but any place. That’s what the report, well, you know.

Frank Cottle [00:05:28 ]: The other shift that’s going on right now that is in the news and that I know you’re involved with is the application or the understanding of the application of artificial intelligence. And when we talk about the future of work and trends, remote versus hybridization, distributed, et cetera, AI has to be impacting hiring practices and the way that people are gaining their jobs and really the way jobs are being laid out and offered overall, what are you seeing in the changes in hiring practices that AI combined with we’ll say hybridization are causing to occur? And how broad a pattern do you think that’ll be?

Dr. Gleb Tsipursky [00:06:17 ]: Yes, to make the connection to the previous question, KPMG accounting and consulting firm did a survey of large companies, the hundred largest companies or so in 2023, and asked their CEO’s what they intend about returning to office. For people who traditionally work in the office corporate employees and so on. And something like 64% of them thought that by the end of 2026, everyone would return to the office full time. That was last year. They did another survey this year. Same survey, same people. Now only 34% of them, 34% of CEO’s, believe that they will return to the office full time by 2026. And so we see this transition over a year, which is kind of counterintuitive. You think that people would be less willing to have their employees work from home, work in a distributed manner, but people seem to be more willing, leaders seem to be more willing to have their people work in a flexible manner. And I think Generative AI has something to do with that. Because Generative AI, when I help companies figure out their high flexible work plans, and that’s one of my areas, I also help them figure out integrating generative AI into their plans, into their work. What we’re seeing is that generative AI is definitely enabling more people to work in distributed manner, whether they work from home, whether they work in different offices than their team members. It’s just making it so much easier. And we’ll talk about the reasons why. But that is the broader trend that I’m seeing. The generic AI is greatly enabled flexibility for workers. And so in terms of hiring people, companies are more willing to hire people who are not located in their immediate geographic vicinity more than they were before. And so that’s a changing trend as well.

Frank Cottle [00:08:22 ]: So you think it’s the immediate application that larger companies, or all companies are seeing of artificial intelligence, the application of it throughout their entire work processes, that is allowing for more flexible work rather than pushback from employees and just say, I don’t want to commute anymore, so take it or leave it. You think it’s that recognition of the ability to accomplish just as much and maybe even more now, and that give the employee the option, which gives you a larger hiring pool. A friend of mine who runs a very large HR system, she said the other day that they get a five to one response on resumes for job applications if remote work or hybrid work is included within the job description. A five to one response in the battle for talent, that has to be huge. To an employer, it is huge.

Dr. Gleb Tsipursky [00:09:33 ]: And there’s a clear dynamic that we’re seeing. The survey I mentioned from KPMG, same survey, same questions, two different years. In 2023, many more leaders wanted all of their team members back in the office full time by 2026. By this year, many fewer. So two thirds compared to one third. And the difference is people were still wanting flexible work. Right. You still had one to five responses in 2023, what you talked about compared to this year, you still have one to five responses. So that hasn’t changed. What changed is generative AR. Generative AI is making it much easier for people to work in a flexible manner. So, for example, I’ll give you an example. Let’s talk about ideation. So creating ideas. The typical way that companies create ideas innovate is get people together in the same room and then have a brainstorming session where people just share ideas, have out of the box ideas. It’s a fun activity and it requires people to be in the same space. If you do it by video conference, it’s much less effective because you’re not really able to see other people’s body language nearly as much, not really able to engage nearly as much. You tend to drop too much more often. So it doesn’t work very well. Now, what about generative AI? How is that impacting things? So generative AI is enabling many more innovation tools. For example, generative AI is well known as having a problem with hallucinations.

Frank Cottle [00:11:14 ]: Meaning I’m well known for having problems with hallucinations.

Dr. Gleb Tsipursky [00:11:20 ]: Yes, all of us have problems with hallucinations when we innovate, right? Right out of the box, I guess. So it’s not a problem to use generative AI for innovation because it’s expected that everyone who innovates, who tries to create a team will have some ideas that are going to be bi, that are going to be nations. So you have AI explore the whole space of the idea options in a way that would be harder for a team to do. So you by yourself can work with generative AI to create a lot of ideas. Let’s say for a product, new product, new process, problem solving, you create a lot of ideas and then you have AI evaluate these ideas. So AI is not only good for the first stage of idea generation, but it’s also good for the second stage of idea evaluation. You can have, let’s say, if you’re launching a product, you can have a generative AI take on the role of some internal company members, let’s say from marketing, from sales, from product, from legal compliance, and evaluate this product. Then you can have generative AI on the role of number of customer segments to whom you’ll be offering the product. Again, evaluate from the external perspective of this project. And then you have generative AI business plan and a marketing plan and a pitch deck for this product. So now you have done a lot. You’ve done a lot of idea generation, idea evaluation and material preparation before. Then you share with your team your idea. Previously you had to do all that, the idea of creation, evaluation and then content creating in a room with people. Right now you don’t. And that is just one out of many examples where generative AI makes it much easier for people to work in a flexible manner.

Frank Cottle [00:13:23 ]: No, that’s really true. We see that in our own company, particularly in the marketing team. We have one individual who’s very talented, very creative person, and he’s totally adapted to artificial intelligence in his processes. And he goes in and has a brainstorming session with himself. He goes into his own room and his own thing, and he says, well, I’m going to go brainstorm for a while. And all he’s doing is running ideas past all of the various elements that you just discussed. And when he comes back with it, he created it, the artificial intelligence didn’t. The artificial intelligence gave him decision making points really, overall, but it allowed him to not have to. He could argue with artificial intelligence without insulting it, without having to step around the topic, without having to worry about his position in a meeting, just get the pure answer he’s looking for. And I don’t know that the answers are that much better than he would have gotten if we’d have gotten five people in a room. But I do know that it’s five times faster. And speed is what we’re seeing is the greatest outcome of artificial intelligence applied through various processes overall. And that’s got to have a big impact on employment again, and job descriptions, are you going to look for people that are able to use artificial intelligence and in your job description, define that? And then how do you challenge that? How do you, how do you assess that? Oh, yeah, I’m real fluent in this and this and this in your interviews. And let’s just, people like IBM global as an example, and this way global, part of their, the IBM HR structure that’s out there using artificial intelligence. How are they sifting resumes? How are they validating this skill set? It’s so new.

Dr. Gleb Tsipursky [00:15:47 ]: It is new. So to get to what you’re saying, it’s not only five times faster, but five times more flexible. You didn’t have to have everyone commuting to a central location and getting together in a room. So it’s much more flexible and much less draining because you don’t have to commute. Right. So that’s another huge benefit of using generative AI. Now in terms of hiring, it does change the dynamic pretty significantly. So. Previously, for example, the kind of talents that used to be valued in a lot of venues were idea creation. In the future, we’re using generative AI. The kind of talent that will be valued more is idea curation. Nothing generation of ideas, which the eye can do. It’s very creative. It does better than 99% of people, 91% of people on a torrent’s test of creativity. It has a lot of creativity benefits. A lot of research shows that. But you still need people like the person you mentioned, the employee mentioned, to choose the right idea, the right questions.

Frank Cottle [00:17:07]: To choose the right ideas question becomes elemental. How do I assess that? How do I look at you and say, hey, gleb, I see this on your resume, but how do I assess your interacting, your capacity to interact with artificial intelligence, which makes you more valuable to me, perhaps, than another person that I’m interviewing for the same job.

Dr. Gleb Tsipursky [00:17:33 ]: So same thing that if somebody claims they have skills in python, right. You can just assign someone a test using artificial intelligence to have certain algorithms. So let’s say create a product and evaluate it from an internal perspective, from an external perspective. Create a business and marketing plan and a pitch deck for this program. We’ll give you 15 minutes. Now, if you’re doing it by yourself and you don’t know how to use artificial intelligence, you have absolutely no chance.

Frank Cottle [00:18:08 ]: You’re stuck. Agreed. So, so testing as part of the interview process, which isn’t that, wasn’t that common? We used to look at people’s portfolios. Look at, take marketing as an example. We might look at their portfolio of work, but we weren’t doing live tests.

Dr. Gleb Tsipursky [00:18:29 ]: Yeah.

Frank Cottle [00:18:30]: So that is a major change overall.

Dr. Gleb Tsipursky [00:18:35 ]: There are no certifications that are really quality and accepted right now. I think in the future there will be more certifications as programs in using artificial intelligence skills come up. You can get badges, certifications, but right now, from the clients, what I’m saying is just testing because certifications that are out there right now are not really very well validated.

Frank Cottle [00:19:00 ]: You’re going to have to train the trainers on that one pretty well to make sure that the people in the HR side of things, on the hiring side of things, are as smart as the combination of the candidate and their AI put together. That’s going to be quite challenging for a lot of companies, I think.

Dr. Gleb Tsipursky [00:19:24 ]: So I’m telling you, when I help with hires.

Frank Cottle [00:19:27 ]: Right.

Dr. Gleb Tsipursky [00:19:28 ]: So that is an example of a test we’ve done. Gift all 15 minutes to create a new product from the company for the company, evaluate internally, externally, create a business marketing plan, the pitch check, that’s kind of a test. And we see whether the person is able to do it or not using generative AI. And some people are not and some people are. And then we can compare how well they did using generative AI to have these outputs. So it’s not something that you can see. You can see how people are doing in the testing process. So this is not something that’s, I think, that hard to train on and it’s not that adversarial.

Frank Cottle [00:20:11 ]: Yeah, no, all these evolutions are fun, but we’re, we’re talking right now in the context of text workers, marketers, basic white collar creatives. In many respects, when we talk about the future of work, we also have to talk about blue collar manufacturing jobs. I mean, if you were to look at the jobs reports, manufacturing jobs are elemental to the success of the economy. So how do you see these shifts impacting not just white collar jobs, but also blue collar jobs, farm jobs, etcetera? There’s a lot of different things that are being used. But will we see the same adaptation rate? Maybe it’ll be higher. What do you see on adaptation?

Dr. Gleb Tsipursky [00:21:11 ]: So for white collar workers, the ones who will succeed like we talked about, will be the ones who learn how to use generative AI effectively. And I have a book about that chat DPT for thought leaders and content creators. For those people who do want to learn how to use genetic AI and effectively in terms of blue collar workers, it’s going to be a little challenging for them because we do see robotics being advanced, and so they will be increasingly outsourced. For example, I would want to be a trucker in the United States right now to, let’s say, starting careers in trucker, because we’re clearly seeing the replacement of trucker jobs, which is a million people by tools using generative AI that are able to drive themselves, or at least in a convoy with one human driver and several automatic trucks. So that’s kind of one example. And we’re seeing, let’s say, cashiers being replaced by generative AI tools in a lot of restaurants. So that’s another area we’re seeing. A, and so those blue collar jobs, and those are just two examples, robots are becoming increasingly effective because generic of AI using video training. So we’re having more and more high quality video with generic AI that is enabling the training of robots on human jobs. And it’s not nearly as close as outsourcing of people’s jobs for copywriting or idea evaluation and creation. I think it’s more something like two, three years out more. Most close, of course, for cashiers and truck drivers, less close or more complex jobs that are harder to train.

Frank Cottle [00:23:16 ]: Well, you know, I would agree with that. There are. Well, just as an example, Intuit last week announced that they laid off 10% of their employees. And they announced it because they were satisfied that their strategic initiatives with AI would allow for them to run more effectively. They had come up with a way to integrate AI within their processes to speed things up so that they no longer needed that number of employees to do the same amount of work. We as a company did the same thing last year. We looked at our processes and we looked at our staff and we looked at our production, and we said, we’re gonna have a hiring freeze for a year, and we’re gonna do nothing but look at every process and add every application of improvement, including artificial intelligence, that we can. And we grew almost 40%. We didn’t add a single employee, and we’re handling substantially more clients than we were last year. We didn’t let anybody go either. I’ll mention we kept everybody there because we knew that we could gain productivity without shrinking the teams. But that issue of into it, let’s assume that those people were laid off, and they were laid off because their job was made AI redundant in some way. Their skill set may not allow them to get another job that isn’t AI redundant in some way. So all of the people that we may be looking at displacing or slowing a hiring pace down with as a result of this other option. I know Sam Altman just was running an experiment the other day with a governmental group or a non governmental organization of some sort on uniform income for people, basically going to the position that people needed an income. And how would they play with that because of artificial intelligence. Are we going to go to a different subsidy perspective, do you think, where government or all of us are paying a burden as a result of the advances we’re capable of making, because we aren’t capable of making those advances without necessarily hurting someone. What do you think about the social side of all of this? Because it’s definitely two thirds of what you hear about AI is. Is it safe? Is it going to hurt jobs? You hear a lot of that. I won’t call it fear mongering, because we see it actually happening. What are the social sides that you see of this?

Dr. Gleb Tsipursky [00:26:24 ]: So the social sides will depend on how quickly AI is moving. I think the quicker it’s moving, the more destructive it is. The more impact it will have socially. So from the perspective of less social impact, you might want to go for slower technology change. That’s not necessarily the best thing in terms of having a positive economic impact. The reason to have slower technology is because of some of the existential risks around generative AI, where if we have, let’s say, generative AI gets out and becomes a computer virus, it’s able to evolve and destroy a lot of the world’s Internet. I mean, we just saw what happened with crowds, strikes. Right. Just a stupid, bad update that caused so much trouble. So generally it was a lot of disruption if it gets out in a way that programs do harm the world. So that’s kind of one, I think.

Frank Cottle [00:27:26 ]: I saw that movie where AI took over the world.

Dr. Gleb Tsipursky [00:27:30]: Yeah, we’re not talking about AI taking over the world like Terminator talking about a virus. So generative AI is a virus that learns, evolves, adapt. It can be the most powerful virus in the world, because most the viruses currently out there didn’t change. They don’t adapt. Generative AI, by definition, can adopt and evolve. So that’s a real danger. Now, from the perspective of jobs, what I think people really need to do is learn how to work with generative AI because it’s not necessarily the case that there will be less jobs. So I think Sam Altman, if the technology goes sufficiently quickly to make people unnecessary, that might be something that happens if you know, his wildest dreams of like five years. Right. If that happens, there might be a case for universal basic income. But in many cases, if the technology is moving somewhat slower than that and we have some more constraints, then people will have plenty of time to learn how to use generative AI in their work. So gaining skills. So you talked about, let’s say, into it, laying people off. Yeah. And I have a number of clients laid people off because they were unable to learn skills around generative AI quickly enough or they weren’t necessary. For example, one client in the accounting department where they just didn’t need that many workers, they laid off a couple of their, several staff members because there was enough work for them to do. But certainly the world needs a lot of accountants, and there will still be accountants if they gain skills in using generative AI to accounting. So I think that’s where people really need to think about and focus on using generative AI skills, and that’s what companies need to focus on. The nice thing, by holding on to all of your employees while integrating generative AI into your company. And I encourage the companies, I work with to do that if possible. It wasn’t so possible in that other case because you couldn’t really change an account to do some other stuff in the company, whereas many people who are like marketing, you could change their world to something else. So that is something that I think need to be thinking about. They need to be thinking about using generative AI and learning the skills. Leaders be thinking about how they will integrate generative AI into their company. And again, that will enable much more distributed work, which will enable you to hire talent from around the country and around the world, but at least around the country, and will enable you to coordinate people much more effectively. So thinking about genetic AI as a tool for evolution and disruption, that’s where people really need to be thinking about from themselves as employees and leaders in terms of their companies.

Frank Cottle [00:30:39 ]: Okay, I’m going to take a position, if you will. Everything we’re talking about is mostly white collar, first world countries, people that have the resources to take advantage versus people that don’t have the resources to keep up. Do you think that generative AI will bring the global population’s capabilities more closely together or create even more disparity between economic groups than we have today? Is this going to become a world where the shareholders of the company is able to take the fastest advantage of AI, are going to increase their wealth dramatically over the individuals that may get displaced by AI and create a broader gap? Or do you think that. Aih, and we’ve kind of gotten hung up on AI here, but it’s a good topic. Do you think the AI will actually bring that gap narrower? And if so, how?

Dr. Gleb Tsipursky [00:31:53 ]: I think it’s definitely the case. The shareholders of companies that are most happy about using generative AI will gain a lot of. So no question that’s the case. And so we don’t yet know which companies those are. Nvidia, obviously. Number of companies, number of tech on Microsoft, Google. I assume that they will. So that’s kind of one thing. Now, you asked about the world, and I think one of the things that really helps the developed world against developing countries is capacity to have a lot of knowledge. Generative AI is going to equalize that, and people in developing countries will have a lot more knowledge, lot more information than we did not have before. No question about it. Another thing that will be equalized is the quality of education. So right now, rich kids are able to have personal tutors and poor kids are not. They have to go to public schools, which, you know, are not the best in the future. Currently already and more and more in the future. Generative AI will provide a personalized tutorial for every student so that will equalize social disparities, so that children will be much more capable of learning and getting up in the world, around the world, and also right now in the United States and other countries, which are developed countries, but where more kids are going to public schools. So I think those dynamics will also be playing out. And of course, another benefit is that people will be able to coordinate much more effectively using genome AI. Those dynamics that I think are pretty clear. Those things will be certainly happening. Other dynamics are more complex, but those are the ones I think I want to focus on that I think will unquestionably happen because they’re already happening. Right.

Frank Cottle [00:33:51 ]: Well, that ends on a positive note then, because I happen to agree with you, by the way, that the use of these tools, which don’t understand borders, they don’t, aren’t limited by language or place, should be able to be used more freely by everyone. And that will hopefully rising tide floats all ships approach to way we see the world’s economy in general going on. So, Gleb, I really want to thank you. It’s a joy always chatting with you, and I look forward to the next time we have the opportunity. And I wish you the best of luck on your most recent book. You just keep cranking out those bestsellers. It’s amazing. So good luck with that and we’ll look forward to next time.

Dr. Gleb Tsipursky [00:34:43]: Thank you. I appreciate it. I’m glad you like the doctor. Chad JPT for thought leaders and content creators. You can check it out on Amazon, anyone who wants. And thank you for having me on the show, Frank, it’s been a pleasure.

Frank Cottle [00:34:55]: Take care. Bye