Imagine having a satellite specifically designed to analyze your organization’s productivity landscape. That’s the power of KYP.ai and GenAI opportunity identification!
Join Sarah Burnett, Dr. Adam Bujak, and Wojciech Zytkowiak-Wenzel, PhD, and discover:
- How GenAI acts as your organizational productivity satellite, providing a comprehensive birds-eye view of your team’s efficiency.
- Actionable insights to identify and eliminate productivity roadblocks.
- Expert strategies to maximize your team’s potential and soar to new heights!
Transcript:
Sarah Burnett: Hello, ladies and gentlemen. Welcome to our webinar about generative AI. The focus is on from mass adoption to mass productivity. Important topics. I’m sure you agree with me. Today to discuss these topics are none other than our CEO and co founder Adam Bujak. Our Head of People and Culture, Wojciech Zytkowiak-Wenzel.
Welcome, gentlemen. So before I go into the agenda and explain how we’re going to proceed today, let me just say that the Q&A will be held at the end of the session and there is a panel for you to post questions. So please go ahead and as we go along, post your questions and we’ll do our best to answer them.
Now on to the agenda. We have divided the webinar today into three sections. The first is to talk about adoption by enterprises and what it means for productivity and many other aspects of it as well, particularly how it might affect the working week. The second section is about all these predictions of massive increases in productivity.
Will that necessarily happen? And we have some interesting subjects in this section. The Solo Paradox, FOMO and FOBO. Yes, you heard correctly, FOMO and FOBO. Please stay tuned and you’ll hear more about those as well. And finally, we’ll move into how to become productivity champions in this world where this figure matters more and more to every enterprise, every organization.
How can you make the most of this amazing technology to stay ahead and become a productivity champion? That ensures that you get the return on investment, the return on expectations as well. And then we go into the Q&A. First, though, I’ll share some data with you just so that you know what’s going on in the world.
As you can see, this one is, really indicative of what is going on. This was a report by Oliver Wyman that was based on a survey of more than 16 000 employees of different enterprises in 16 countries. And you can see here on the chart on average, employees are using generative AI.
at least once a week, and many of them are using it all day. So significant. We’re talking about 55% on average are already using generative AI. And we’ve seen this kind of ground up adoption. So often happens this way that individuals adopt a new technology before enterprises catch on.
Another really important thing that this chart shows us is the way that different countries are adopting it. And you can see that India is way ahead at 83%, but the countries on the bottom of the chart where they have the highest levels of adoption, generally are coming from, the big powerhouses of Asia and Latin America, with Europe and North America lagging behind.
The only country that sort of met that average figure in Europe is Spain. And this will have a significant impact on the economies of the world as well. So we are likely to see Those that are adopting technology early, really gaining momentum and getting ahead. And then we also looked at the industries adoption by industry.
And you’ll see there that tech at 75% adoption rate is leading the other industries, unsurprisingly financial services second. They always, that industry always adopts technology really early ahead of others. followed by manufacturing, media, retail, and so on. Basically, every industry is dabbling with the technology and some are further ahead than others.
And then what about the impact? This is again also from the Oliver Wyman report. 20 trillion is the expected boost to the global GDP by 2030. Just putting that into perspective, some of the Countries in the developed world in Western Europe have GDPs of sort of two to four, five trillion.
So just to show you how massive that figure is the implication for the world is really significant. And then the other figure, 300 billion hours of work saved globally with an average of two hours per week per person. And then the figure that we are particularly interested in, the productivity figure of 40 percent increase in developed countries by 2035.
Nobody can really ignore these predictions. We need to get on with it and learn about generative AI and also understand how it’s going to change things for us. Let’s get on to this and my next section is about productivity. Adam, what is it? Why do we care so much about productivity?
Adam Bujak: First of all, let’s start with the definition. Productivity is basically correlating the input that you’re investing in a given period of time to generate certain output. This definition must be clear and obvious. If you want to improve productivity, you of course have to measure it.
Measuring productivity forces you to understand how all elements of your business are working together across people, process and technology dimensions. This is what drives us at KYP to look at the most important metric in relation to the GenAI
Sarah Burnett: Thank you, Adam. And Wojciech, you with your people and culture hat on, I’m sure, this is right at the heart of your interest and research.
How is it going to affect the way that we work, the time that we spend at work? Yeah. So thank you, Sarah. It’s a very good question. And I’ve been thinking about it, especially for the last year, since the massive adoption of Gen AI. And I want us to pause for a second and look at this quote.
Wojciech Zytkowiak-Wenzel: It’s a beautiful quote, but it gets even more interesting if you put it in the context of our work. There is a big difference between Spending our time at work and actually using it. Spending means that I’m giving away my time always like for free. Not necessarily there is outputs.
That’s my input. Not necessarily. I see a lot of outputs now using my time means that I’m, doing it with purpose and there is some meaningful outputs, right? So this is the big promise because I believe that we’re on the verge of a big shift with Gen AI or AI in general, and that the shift in productivity is going to be not only incremental, it’s going to be massive.
It means that we’re going to fundamentally redefine the way we work, right? So it can be our game changer, and it will help us to move from being just busy, To actually doing things that matter, leveraging our potential. So just to sum it up, I believe that Gen AI’s promise is that we’ll flip the script of, how work is actually being done.
Sarah Burnett: And that is, in line with something that some of the industry figures are predicting. If we 40 percent increase in productivity Bill Gates, for example, has already quoted a similar kind of figure. He’s also talked about the change in working patterns and hours. He’s famously said that the three day week for humanity is okay.
And as somebody who works part time myself, I can vouch for that. But the big factor of course, is if you can earn enough of a living, a good living. That’s the big question that we’ll need to answer over the years that are to come. And as AI develops further that now brings us to the next section of the webinar, which is about the productivity paradox.
So lots has been said about how productive is going to be up. The 40 percent figure is massive. If it becomes true, it’d be incredible. But does mass adoption of generative AI necessarily mean mass increase in productivity as well? Wojtek, what do you think about
Wojciech Zytkowiak-Wenzel: Why? Because, I believe, and this is what I’m hearing a lot of conversation that there’s still a lot of people that think GenAI is just another management a hype that will pass to something else. And I think as human beings, we are prone to making these inadequate assessments, or, we over underestimate the impact of technology. And the question is why, here’s why, because in retrospect, if you look historically at the data, it took quite some time for many major tech advancements to scale. A good example is the light bulb. After 20 years from its inception, only 3 percent of businesses were using it. We’re using electricity in general, right now, something has definitely changed if you looked at the data of, ChatGPT adoption, because I’m sure this is not a surprise to you and everyone has been talking about it, that, it, reached a mass adoption in what, 10 months, I think. So did the growth pace and we can call exponential. So it’s really exploded. And I think that by now, we are, past the tipping point. And that means that this change, things will change and things will improve faster and faster.
Sarah Burnett: It was unprecedented, wasn’t it? The way that absolutely was adopted. But do you think what they’re predicting will necessarily happen? Will we get more productivity because of generative
Wojciech Zytkowiak-Wenzel: AI? Yeah. This really depends. So I would start by looking at some historical data and how it correlates with order, technological advancements, right?
So we had rapid internet connections, we had smartphones, we had cloud computing, but if you look at, productivity data from us economy. You have an example here. What we see is that there was no major big, massive shift in productivity. And even more importantly, even if there was a shift, it was delayed.
So it was not immediate. So the question is, why? Why are we witnessing this productivity paradox? Because on one hand, we have those, enormous disruptive technologies. On the other hand, we don’t really see an immediate impact on productivity. And the question is, why? And I think a part of the answer is because technology itself will not make that big shift happen, at least not immediately, because the question is also how do we embed that technology into our processes, work processes, and even more importantly, how our people in our organizations will interact and feel about that technology, right?
Looking at the people side of things. And this is the acronyms that Sarah has really mentioned earlier. So there’s at least two perspectives that we should look at. The first one is fumble and let’s look at the first. So this is something that we’re often witnessing at the very top of the organization.
So this is what our CEOs, what our, C-level colleagues, executives are facing, senior level managers who are taking decision about Gen AI adoption. And they are struggling at that. So they know, they feel that Gen AI and AI in general is their next big thing, right?
So they feel pressured to act. They feel pressured by competitors. They feel pressured by their shareholders, and also pressured intrinsically by their ambition to win. And it smarts everyone else in the market, right? So that often pushes them into taking gen AI or AI adoption decision based on intuition, on emotions, or on half truths, or simply, flying blind into it, right?
Because we have this fear of missing out on it, and hence the FOMO. On the other side of the spectrum, if we take a broader view we seem, at least to some extent albeit a little bit like suffering also from the fall bone. So fall bone is a bit, I think, less known phenomenon and it stands for fear of becoming obsolete, right?
So essentially what is happening here is we all understand that there is something big happening, right? And we have this fear of becoming obsolete, maybe in reverse. Replaceable, maybe irrelevant. Why is that happening? Because every single day we’re bombarded with news about Gen AI, what is changing, new vendors, emerging capabilities.
A good example, I think around two weeks ago, we had this news about Sora, right? Do you know the new text to video model, right? That has taken social media by storm, right? There’s AI gurus like everywhere. And that creates tension, anxiety, and feeling of overwhelm. And this is really like a serious problem that we have to attend to.
Sarah Burnett: And is there a way to overcome that? You know, you feel you might be left out of this
Wojciech Zytkowiak-Wenzel: Yeah. So we need to train our people. We need to reskill. We need to upskill. We need to help them. Because what we’ve seen at the Oliver Wyman report data is that
over 90 percent of our employees of our people in our organizations, are using or trying to experiment with Gen AI without having any form of training in it. So training is obviously right? But what comes before that is talking about the vision for Gen AI.
So what is that we’re trying to achieve? What can I can do for us in our organization? What can I do for you as an employee as a human being? How it can help you? Definitely training. But even before that, creating awareness is super important.
Sarah Burnett: Yes, and we all know it’s not perfect, is it?
There’s some things it does really well and some things it doesn’t do so well.
Wojciech Zytkowiak-Wenzel: Yeah, I
Sarah Burnett: Thank you, Wojtek. So this brings us really to the next section, but let me just quickly summarize what we have said. We are expecting an increase in productivity and it’s whether it’s quite as big as everyone is predicting because of the solo paradox and the challenges of FOMO and FOBO.
It might not quite be as high and there could be diminishing returns on investments in aI. So I’m just going to pose a question to Adam. Adam, you talk about productivity champions, and we know that the way that we approach technology and its adoption makes a big difference. Can you tell us about the concept of productivity champions?
Adam Bujak: The question that we are asking our customers at KYP is, what if you could replace your intuition with data and facts? Do you want to see the true picture on the trifecta of people, processes, and technology, just to illustrate that, starting with people, not only how do we improve their efficiency, but also how to maintain the work life balance, the right allocation of work, how to ensure that I’m driving enough waste elimination, standardization of the processes, and, very hot topic at the moment, process automation.
And then. Tech pass. This is what we brought to the market last year. We see that every second customer on all continents of KYP. has problems with technology, preventing people from being productive. You may have poor response time of applications and we’re not counting it in seconds.
The record holder waits 26 minutes for the application to respond. Believe it or not, right? It’s my hardware preventing me from executing faster because I do not have enough memory or I have a pretty poor CPU. So how to make sure that we are removing the friction from this CPU, relationship between input and output we were covering a bit earlier.
And when I look at what’s happening in the market, there is a tremendous mass productivity increase requirement that forces our customers to understand how all elements of their businesses are working together, right? And with the advent of GenAI, This challenge is massively amplified.
That’s why the value proposition of KYP is to enable data acquisition. Remember, there’s no way without data, right? And then AI opportunity identification with KYP. It’s just you’re covered by satellite that helps you to oversee the entire model of your organization. But more importantly, you can zoom in to figure out what to do in the individual unit of your organization, individual process, individual function to generate the impact.
So it’s not only about showing the opportunities, all the patterns. This was in the core of our value proposition in the last years, but also how to measure the impact. Ensure that, what we are inputting in the system generates the output that makes us more competitive, that allows our employees to focus on risk healing.
That allows us to, for instance, aim at three days working week, as we mentioned earlier slides.
Sarah Burnett: And what does it, mean for jobs?
Adam Bujak: Jobs? Yeah, that’s an exciting question. How your job of the future will look like, right? And this obvious trend that automation is going to continue.
We started with the industrial revolution, right? For white collar workers, there was first uptake was with macros on Excel , right? And robotic process automation picked up. So many technologies came into the game. And this is something that will continue to shape our destiny when it comes to executing each individual job.
Augmentation is a new phenomenon, right? Previously there were desktop bots. But the question was always, okay, to which extent can this bot operate separately to move towards the automated side? Augmentation will be a big topic. And then there is manual effort. So expertise, knowledge driven execution, leadership tasks that cannot replace the humans at least not by now.
Our job at KYP is to identify these opportunities, continuously measuring the impact at scale. So this holistic approach makes a big difference and acts as a guidance, as a satellite that shows you in your command center what to execute on and whether you’re successful.
Sarah Burnett: Thank you. I guess there’s a individual dimension as well.
What does it mean for the individual? Wojtek, would you like to take that question?
Wojciech Zytkowiak-Wenzel: Absolutely. So if you don’t mind I’ll speak about, my own personal experience with the technology. I still vividly remember the first week of December 2022 when I started using the 10 version of, I don’t know, three something of ChatGPT and it, blew my mind.
And after almost like year and a half of using it, I can really feel what this augmentation really means. And for me, it’s not only about doing things faster. It’s also about, what happens with that manual time. Something that we call here in the chart manual time and what I discover is that I have more time now for more meaningful things like for more kind of problem solving for more creativity for, talking to people, because over the last, 12 months or so I have.
Myself become a prompt engineer, writing job descriptions, creating, content for presentations, even writing some of my emails with Microsoft Copilot. So can I do more? Yes, also that. But even more importantly, I can. Allocate my time where my skills I feel, that might be subjective, but I feel that my skills are better used right now and what it creates, because this is what is important.
What is the end game for me as a human being as an employee, right? It creates, satisfaction, job satisfaction, more fulfillment. And that for me. Means that my job, thanks to these technologies, has become better. And if my work is better, if my job is better, then ultimately I have a better life.
And, you can say that I’m biased because come from HR functions. So I’m biased, yes, but want that to happen for everyone. So this is, the vision, this is the great promise of Gen AI.
Sarah Burnett: I agree with you, Wojtek. It’s making my life and work life a lot easier as well.
And I’m not from HR. So we’ve talked about how it’s going to change jobs and work. And we’ve talked about the individuals. Adam, what about the enterprise? What does the future hold for the enterprise?
Adam Bujak: That’s a great question. When you look at productivity driven organization this is basically a question, what can I, how can I do more with less?
Or stay constant in my capacity and generate additional output. The word before Gen AI was focusing, as I said earlier, primarily on creating an automation impact. This is what we have been doing, helping to drive automation potential identification. We were focusing initially on robotic process automation, then on intelligent content recognition.
Now there is any pattern that you can look at with KYP. So whatever technology comes in, we are adding this patterns to the engine to make sure that this identification and quantification of the business case accelerates. The other side of the game is obviously what happens to.
For the manual effort, right? How do I drive efficiency? How do I ensure that my productivity commitments that I made or ambitions that I want to generate are relevant? With Gen AI, we see an absolute shift of excitement. Moving from the automation that continues to scale, right? So I think the maturity on the automation side is growing every day.
There’s no doubt about that. But GenAI potential identification became one of our daily bread activities. That allow us to say, Yes, we are the champion in the space acknowledged by Gartner and other analysts. But more importantly, we are helping this revolution to happen, right?
And we are still not neglecting the human factor. There will be no jobs lost in the near future due to jelly. On the contrary, you will have prompt engineers, people that deal with all the aspects of introducing this important technology component, but the focus on how to support the human, how to drive the human.
As individuals in the organization more efficient while maintaining the work life balance remains a clear priority. So I would not be worried about the FOMO. What I want to point you to is the other aspect. While you’re accelerating on the automation front and Gen AI at scale, people will become massively efficient.
I was back to the examples that Vojtech shared, being a CEO of a fast growing company, I receive roughly between 60 and 120 emails a day with copilot. I’m able to answer all of them. Obviously 60 percent is people that want to sell me something, right? So that’s an easy one, but I have to rapidly respond to what is happening.
And my efficiency went up dramatically. And the question is, what do you do as an organization with this capacity that is being freed up, right? And this opens potential for upskilling. It opens potential for more, for generating more. It opens potential for shortening the working week.
It depends on the organizational priorities. But the future is absolutely exciting from my perspective. And we are incredibly proud and humbled to support large players that you can look up on our website with identification of the patterns. And continuous measurement of the impact of what’s happening in your organization. Because the change has to be accompanied by the data.
Sarah Burnett: And Adam, there must be a way of measuring what we’ve achieved, the outcomes. Absolutely.
Adam Bujak: And you know this example Sarah we have we are working among other categories also with VPO players, right? They have tremendous productivity commitments.
Now, this is a pharma player that started with us in Q3 2022. What we see here on this overview is the entire 2023. So last year and the impact of data driven improvement focus is 29%. So almost 30 percent of capacity freed up. Not only have they exceeded. Their productivity commitment, but more importantly, there’s enormous upskilling happening, right?
You need to catch up on the new technology. So instead of suffering from the FOBO that Vojtech was describing earlier you’re investing in new capabilities that create competitiveness and can cover other new engagements that you’re winning to deliver the outcomes. And this applies for any function, for any sector.
for any area that you may dream of, assuming that you have the data, that you interpret it correctly, and then you execute accordingly. That’s the name of the game nowadays.
Sarah Burnett: I like the fact that the augmentation has grown over the months. That’s really interesting as well. The level of augmentation. Thank you very much. That really brings us to the end of the talks. We do have a paper that is freely available on our website. The address is there on the screen, and you can download it by just registering and being able to download it.
Then it talks about it focuses on, the way that kyp. ai is helping deliver better returns on adoption of Microsoft Copilot. It’s very interesting and I encourage you to download the paper. So now we go to the Q&A section of the webinar. Please, if you haven’t already posted your questions, do post them.
I have a question that I’d like to get everyone started on, and that is about AI myths. So much is being published and perhaps not always, people who are, particularly experienced in AI. Could there be Problem with myths and really mumbo jumbo almost being generated and scaring people off.
Wojciech Zytkowiak-Wenzel: If I may, because I think we already discovered, discussed that and covered that. So I don’t want to repeat what I already said, but I think, yes we’re facing this enormous noise. And the advice and my answer would be okay. Show me the data. And this is what we’re ultimately trying to do with our customers.
So show me the data where I can apply this technology. And also when I apply it, it’s not just a promise that things will change measure what is changing and show it to the people and show how the things are changing. So this is, by the way, not a, one of exercise. It’s a continuous improvement process, right?
Just with the new amazing technology. So that would be my answer. Based your action on data.
Sarah Burnett: Very good point. Thank you. Another question. It’s about KYP. The question is how does KYP help other enterprises using productivity 360 product? Adam, would you like to take that one?
Adam Bujak: Absolutely. There is a wide spectrum of our value proposition. that ranges from Gen AI opportunity identification RPE candidates, measurements of work life balance of the people side assessing process compliance or technology. The most important aspect here is the objective that you should have in mind when it comes to AI.
There’s lots of aspects that we see starting creation of the COEs definition of the data like data officers nowadays. gain tremendous traction and their role becomes even more important, right? It started a while ago with the move to the cloud, where we were facing the promise of, okay, once you move your applications to the cloud, the insights will be there, right?
It didn’t happen. That’s why technologies like KYP are appearing on the horizon to close that gap, help you to automatically gather, acquire the data, generate insights. And then execute accordingly when measuring it. So for us, the priority is to support the mission of productivity increase. And as we see wherever you go it’s an ongoing battle of every corporation, every individual, we have to remain competitive, generate more with less.
And most importantly, take advantage of the technologies that are in the market looking at the adoption, right? There is another question on the adoption that I see here. This is one of the aspects that are absolutely relevant. For the latest technologies like Microsoft 365 co pilot or Google’s Gemini.
What we see is that it’s not enough to acquire the first 50 licenses and say, okay, let me see what happens, right? This is what we call lavish experimenters do. It’s about identifying, first of all, who in my organization looking at the end to end execution is using enough, for instance, of the MS office to apply MS 365 copilot, right?
If you’re just spending 3 percent on Outlook and Excel, it’s probably not for you. But the good news for Microsoft is we sometimes have customers that approach us from the finance department latest case in Singapore, where the customer said, we are an SAP shop. We measure that we show that actually.
SAP constitutes only 7 percent of time spent across the entire finance department covering 55 countries. So it’s not a small organization. It’s just 7 percent of time. The rest happens in other applications and more than 70 percent is spent in Excel Outlook teams. It may sound familiar to some of you, right?
So there we try to elevate the potential and say, okay. If you have such ratio. This is where you look at, and then you have to identify very clearly the objective. If I want to operationalize aspects like how do I faster answer my emails? That’s my specific case, right? How do I take better advantage from summarization of the calls?
It works incredibly well, whether you’re on MS 365 Copilot or Google’s Gemini. But the most important aspect is to see the entirety. Is it going to change my destiny and which of my employees are going to benefit from it? And that’s why we will be launching Microsoft Copilot impact score.
We start with Microsoft. We then publish the version for Google where you will be able to see what is my potential? Do I know my potential before I take a decision to spend millions on enabling my employees? So we prefer focused executors that drive it with the ambition to change the destiny of their organizations and more importantly, to generate more impact.
Very interesting. Thank you. There’s also. the ability to achieve the return on expectations as well, those expectations are very high, aren’t they? And KYP can help with that. So there’s actually a question about that.
Yes. And, this is something that is the most difficult aspect to define, right?
With every project that we are starting the rollouts usually define, okay. First of all, what is the business case, but more importantly what is the soft impact that you’re going to generate, right? Will you sleep better because you have data, you have the insights that allow you to take a decision between A and B, right?
That’s by the way, one of the most quoted values. But what does it mean for the employees? What does it mean for the relationship leader versus employee? Can I look at the data and take an education decision on the performance evaluation on the potential how to remove this mundane activities?
But not dying the death of, automating every little deviation in the process and screaming around because the RPA bot again failed to execute yet another exception. It’s about educated way of taking decisions where to deploy technology. And how to support the outcome and the people in the journey of excellence that we are propagating and supporting around the globe.
Sarah Burnett: Thank you, Adam. Wojciech, anything to add?
Wojciech Zytkowiak-Wenzel: No, I think I agree, with everything that Adam said. And my one sentence summary would be that, intuition is good because we’re and always be human beings, but data is better.
Sarah Burnett: Sure. And I guess there’s this other dimension to it, which is with KYP, we talked about FOBO and educating people and training them and the lack of, currently, the lack of education.
With KYP, you can actually identify where more training is needed as well. Isn’t that true? By the way that, work is conducted. So it can help with that aspect. Absolutely.
Adam Bujak: And, this is speed to value is one of the critical factors, right? We see that with the past in Corona, there’s lots of changes that are happening.
Some companies have not yet decided how do they drive for instance, the hybrid office. Should I spend three days in the office and two at home, vice versa? How to drive that? So this is one aspect. Now with the new employees, new journeys, joiners, and we feel it at KYP as well, that are not necessarily where the office is, right?
So you have remote workforce per se. This becomes even more important. We’re able to show you how the compliance of execution looks like, how the work is getting done, and more importantly, help accelerate the journey. There are dedicated platforms, by the way, where we are also assessing the potential for.
So when you are adding. Enormous amount of new employees. There is dedicated technologies that help you to train them, especially the white collar work for space. We had to predict the impact. See whether you’re doing the right things. And then measure the productivity, as I said earlier, right?
Because ultimately, the outcome matters.
Sarah Burnett: Thank you. I think that’s all we have time for. Thank you very much, Adam and Wojtek for joining me today. And thank you to all the delegates for joining us as well. And don’t forget to download the paper that I mentioned earlier. And I hope you’ll join us again for another one of our webinars very soon.
See you soon. Goodbye.
Adam Bujak: Goodbye.
Wojciech Zytkowiak-Wenzel: Thank you, Sarah. Take care.