3005: Navigating AI in the Workplace: Strategies from Augury

[00:00:01] [SPEAKER_01]: Is AI literacy the new reading and writing of the 21st century?

[00:00:07] [SPEAKER_01]: This is a question I want to explore today. It's a provocative question, but Artem Krupanov, VP of Strategy at a company called Augury,

[00:00:16] [SPEAKER_01]: is going to be sharing his insights on this seismic shift of how AI is reshaping the fundamental skills required in the workplace.

[00:00:25] [SPEAKER_01]: And with AI moving from specialized tool to a core skill integrated into daily tasks,

[00:00:32] [SPEAKER_01]: it almost prompts a re-evaluation of how we should all be preparing for careers in the future and how our children should be preparing for careers in the future.

[00:00:43] [SPEAKER_01]: And my guest, Artem, he advocates for a holistic approach, encouraging not just technical proficiency,

[00:00:51] [SPEAKER_01]: but a strategic understanding of AI's role in enhancing productivity and, of course, decision making.

[00:00:58] [SPEAKER_01]: So how are companies adapting to the shift? What does it mean for the future of the workforce?

[00:01:03] [SPEAKER_01]: Well these are some of the threads that we'll try and unravel today,

[00:01:07] [SPEAKER_01]: and also why embracing AI literacy is no longer optional, but it's essential. Artem is a cracking yet.

[00:01:15] [SPEAKER_01]: I want to take a time out to express my gratitude to everyone who supports my mission of delivering daily content to you in 165 countries.

[00:01:24] [SPEAKER_01]: I couldn't do it without you and I couldn't do it without my sponsors.

[00:01:27] [SPEAKER_01]: And today I want to give a quick shout out to Kiteworks,

[00:01:30] [SPEAKER_01]: who recently told me that defence contractors are facing immense pressure to comply with things like CMMC 2.0 security standards,

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[00:02:20] [SPEAKER_01]: Simply visit Kiteworks.com to get started.

[00:02:22] [SPEAKER_01]: That's Kiteworks.com to learn more about Kiteworks' secure content platform for CMMC compliance.

[00:02:30] [SPEAKER_01]: But with my thank yous out the way, it's now time to jump right into today's interview with a fantastic guest.

[00:02:37] [SPEAKER_01]: So buckle up and hold on tight as I beam your ears all the way to California where my guests are waiting to talk with me today.

[00:02:46] [SPEAKER_01]: So a massive warm welcome back to the show.

[00:02:49] [SPEAKER_01]: It's been a while since we last spoke though, so for anyone listening or any new listeners that missed our previous chat,

[00:02:55] [SPEAKER_01]: can you just remind everyone with a little about who you are and what you do?

[00:02:59] [SPEAKER_00]: Sure. And thanks so much for having me back. Really a privilege to be back on your show.

[00:03:03] [SPEAKER_00]: So my name is Artem Kropinov and today I'm a VP of strategy at a company called Augury.

[00:03:10] [SPEAKER_00]: My background is really in start-ups, entrepreneurship either as a founder or as an advisor or as an executive.

[00:03:18] [SPEAKER_00]: Building products, building companies, particularly in the space of AI and enterprise, AI and software.

[00:03:27] [SPEAKER_00]: And Augury is a company that is one of the leaders within the industrial AI space.

[00:03:33] [SPEAKER_00]: So AI for manufacturing, for heavy industry where we provide capabilities like detecting machine malfunctions way before they happen accurately

[00:03:42] [SPEAKER_00]: and letting maintenance teams know exactly what to do to fix those issues and those machines or providing kind of the perfect run,

[00:03:52] [SPEAKER_00]: perfect product or production processes and telling operators exactly what knobs to turn in order to be able to produce the best product most efficiently,

[00:04:02] [SPEAKER_00]: most sustainably every time. Those are the two categories, machine health and process health and kind of the wider category of production health that Augury leads.

[00:04:10] [SPEAKER_00]: And I've been with Augury for the last eight years.

[00:04:14] [SPEAKER_01]: Well, it's a pleasure to have you back on the podcast.

[00:04:16] [SPEAKER_01]: I think we like as he said, we spoke in 2023 and there was a lot of excitement around AI then.

[00:04:22] [SPEAKER_01]: But equally, there was a lot of unease and concern and weariness about how businesses or what it would look like within a business and business data and machine learning algorithms, all that kind of stuff.

[00:04:35] [SPEAKER_01]: This year is completely different. Now that's turned to excitement.

[00:04:38] [SPEAKER_01]: And everyone's kind of overcome a lot of those hurdles and everyone's starting to move forward.

[00:04:43] [SPEAKER_01]: So I'm curious now, so much has changed in the last what eight to 10 months since we spoke.

[00:04:48] [SPEAKER_01]: Do you see AI literacy as a fundamental basic like reading and writing skills now?

[00:04:54] [SPEAKER_01]: Or why is this shifting perspective crucial for today's workforce?

[00:04:58] [SPEAKER_01]: Because there'll be a lot of kids out there that I don't know, they're studying almost for jobs that don't exist yet.

[00:05:03] [SPEAKER_01]: It's quite overwhelming, isn't it?

[00:05:05] [SPEAKER_00]: Yes, it's moving pretty fast, for sure.

[00:05:07] [SPEAKER_00]: We with Augrey particularly, we've been in the space of operational AI in the industrial space for the last, I would say, 11, 12 years.

[00:05:17] [SPEAKER_00]: And the AI has provided tremendous amount of capabilities.

[00:05:21] [SPEAKER_00]: But for a lot of the public, they have kind of been under the hood.

[00:05:25] [SPEAKER_00]: They provided insights, they provided tremendous amount of tools and at a large scale to be able to analyze tons of data and come up with the right answers.

[00:05:33] [SPEAKER_00]: But really, AI came to the forefront with large language models and things like chat GPT, really in the last two years and became more of a consumer or consumerized product.

[00:05:44] [SPEAKER_00]: And that I think a lot of their awareness comes from that.

[00:05:47] [SPEAKER_00]: Right?

[00:05:48] [SPEAKER_00]: It's not that AI didn't exist before, it's just now it's come to the consumer forefront, very apparent in terms of its capabilities and its value.

[00:05:56] [SPEAKER_00]: And if you ask me today whether AI literacy is important, absolutely.

[00:06:02] [SPEAKER_00]: But I think there's a nuance to that, meaning that AI literacy is not what it used to be in terms of understanding intricately how AI works to becoming a data scientist, a software engineer.

[00:06:14] [SPEAKER_00]: It's really the ability to learn and integrate AI tools into the daily workflow that is becoming important, right?

[00:06:24] [SPEAKER_00]: As an end user, not just as somebody who is developing AI skills.

[00:06:28] [SPEAKER_00]: So you don't have to be data scientist to be AI literate.

[00:06:31] [SPEAKER_00]: Actually, at the base of the way AI is developing, you will very soon not need to be a data scientist at all.

[00:06:38] [SPEAKER_00]: You will just need to be able to keep up with that, with the development and be able to learn.

[00:06:43] [SPEAKER_00]: And the more you use it, the more capable you become at using it.

[00:06:48] [SPEAKER_00]: So it is becoming a basic skill to have.

[00:06:52] [SPEAKER_00]: And even beyond that, I would say it would be almost impossible to perform a lot of tasks and a number of roles in the future without having AI deeply ingrained into your daily workflow.

[00:07:05] [SPEAKER_01]: And it is often referred to as a copilot, something that augments the workforce.

[00:07:09] [SPEAKER_01]: And it's so important to highlight that the magic happens when both AI work together with humans to achieve more than either could on their own.

[00:07:18] [SPEAKER_01]: It's so important to hammer home that point.

[00:07:21] [SPEAKER_01]: But how can workers develop that high level strategy and judgment skills rather than technical skills?

[00:07:27] [SPEAKER_01]: I think it's these human skills that are so important to ensure that they're ultimately empowered by AI rather than replaced by it.

[00:07:36] [SPEAKER_00]: Yeah, absolutely. I think there's also a bit of a misnomer, again, this young misconception saying that people will be replaced by AI.

[00:07:42] [SPEAKER_00]: Certain tasks will be done better by AI.

[00:07:46] [SPEAKER_00]: And I think as somebody who is performing any role, you can take two different worlds.

[00:07:50] [SPEAKER_00]: The world of, let's say, manufacturing, frontline, factory floor, which is very different from the world of white collar service business.

[00:07:59] [SPEAKER_00]: Somebody who is a lawyer or somebody who is, let's say, a speechwriter.

[00:08:03] [SPEAKER_00]: Right. Very different kind of environments.

[00:08:07] [SPEAKER_00]: And also the application of AI is different in those two scenarios.

[00:08:11] [SPEAKER_00]: For instance, the cost of summarizing an article or generating an image or writing a legal brief has dropped dramatically with these new AI capabilities in the last few years, maybe by a factor of 100 to 1000.

[00:08:27] [SPEAKER_00]: But consistently over the last 20 years, the cost of fixing a piece of equipment, turning a wrench, doing some kind of manual task has actually gone up in the last 20 years within the kind of the blue collar world.

[00:08:43] [SPEAKER_00]: So the impact of AI is larger or in terms of cost reduction on those white collar tasks, especially tasks where a lot of text and a lot of summarization is involved.

[00:08:55] [SPEAKER_00]: And also not for the full amount of the task and not the full complexity of a task, but a lot of the times for maybe the first mile and maybe the last mile of a specific task.

[00:09:07] [SPEAKER_00]: So we have to separate that. But as white collar work and tasks become more and more augmented by AI, you can just do more with it.

[00:09:15] [SPEAKER_00]: Right. You can become a lot more scalable in what you do.

[00:09:17] [SPEAKER_00]: And so you have to learn how to exercise judgment in order to be able to apply it correctly.

[00:09:24] [SPEAKER_00]: And so now a single person can become a lot more productive.

[00:09:27] [SPEAKER_00]: The same thing is actually happening within the blue collar space or within the factory space where the insights provided by AI now create a tremendous amount of efficiency and free up a tremendous amount of time for frontline workers.

[00:09:42] [SPEAKER_00]: Right. And the other thing that's happening is that where they were siloed in their decisions and in their collaboration, whether it was focused on specific tasks and the limited knowledge space.

[00:09:54] [SPEAKER_00]: Now those insights kind of democratized knowledge around the factory floor.

[00:09:58] [SPEAKER_00]: And you see people actually collaborating more and making decisions better together because the AI system is providing them with an answer that's most likely to be correct across a number of different functions.

[00:10:10] [SPEAKER_00]: And now those functions need to come together and say, okay, what do we do with this information?

[00:10:14] [SPEAKER_00]: How do we improve our operation? How do we work together and collaborate?

[00:10:18] [SPEAKER_00]: So that's actually very interesting that within our world, within the manufacturing space, the AI's answers and insights that a company like Augury provides actually start bringing people together and enabling them, empowering them to make decisions that are a lot higher order than they were able to do before.

[00:10:36] [SPEAKER_01]: So if we were to zoom in on one particular area, let's think of, I don't know, entry level roles.

[00:10:41] [SPEAKER_01]: How do you see AI transforming those entry level roles and what tasks are most likely to be automated?

[00:10:48] [SPEAKER_01]: And for any workers listening, what should they be doing to adapt and evolve with the technology rather than try and swim against the tide?

[00:10:54] [SPEAKER_00]: So interestingly, OpenAI recently just came out with a note on what they believe are the different stages of evolution of these AI systems towards what they call general intelligence, right?

[00:11:09] [SPEAKER_00]: The official general intelligence, AGI. And so it starts with a chatbot assistant, which is mainly the ability to have a conversation, understand the input for the user and provide a decent answer to some level of reasoning.

[00:11:23] [SPEAKER_00]: So we're at stage two, a level of reasoning which enables us to basically for AI to have some kind of thoughts in the background to be able to break down a logical argument and pass certain tests or summarize few amounts of information to come up with an answer.

[00:11:38] [SPEAKER_00]: So then to agency, which means now it's not just about knowledge, but also being able to execute certain tasks or hire other systems or even people to execute those tasks.

[00:11:51] [SPEAKER_00]: To then actually creating something that is innovative, so innovation or creating not just finding the right answer, but also creating something that's net new, completely new.

[00:12:01] [SPEAKER_00]: And then the last one is being able to really manage and organize a complex system and a whole organization like a group of executives, right?

[00:12:10] [SPEAKER_00]: So if you look at those different levels, entry level roles, somebody who's coming into the job space right now, likely the AI systems will evolve with them over the next five to 10 years and will become an integral part of how their career develops.

[00:12:27] [SPEAKER_00]: So as somebody, one way I can think about it is that if you come into an entry level job right now and you are going to in a few years, maybe you'll become a manager, maybe then a general manager and so forth.

[00:12:39] [SPEAKER_00]: And then go up that ladder of either individual contributor or management ladder.

[00:12:45] [SPEAKER_00]: The AI platforms will likely evolve with you and in a few years, you won't just be able to complete an entry level task better with AI as an assistant, but you will be able as a manager then to outsource a bunch of your tasks or even part of your planning to AI.

[00:13:02] [SPEAKER_00]: And then maybe later as you grow into a higher management role, you'll have an AI system that can actually provide your answers across the organization and even build strategy that will really empower you in how you do it.

[00:13:17] [SPEAKER_00]: So I think somebody entering an entry level position now don't just think about the static state of AI, which tool is better for me to summarize this or create a certain brief on that and so forth.

[00:13:28] [SPEAKER_00]: But think about how AI will be ingrained throughout the progression of your career as it develops and becomes smarter, more capable.

[00:13:36] [SPEAKER_00]: And you can actually use that to your advantage in order to be able to develop the skills that best uses that level of AI that's available to you at that same moment in your career looking five to 10 years forward.

[00:13:52] [SPEAKER_01]: And I also think there's somewhat of a responsibility for employers to not leave their employees behind, especially with the recalibration of the job market across just about every industry right now.

[00:14:04] [SPEAKER_01]: And I think there's an onus on them to help employees along the way here.

[00:14:09] [SPEAKER_01]: So the question for any business leader that might be listening here, what strategies should employers be adopting to better integrate that AI literacy we're talking about and integrating it into the workforce in an effective manner that is welcoming and not scary or overwhelming?

[00:14:27] [SPEAKER_00]: Yes. When you think about something that's so new and developing so rapidly, you cannot just take a top down approach or just a bottom up approach, right?

[00:14:36] [SPEAKER_00]: So the top down approach would be here are the five use cases where AI is great and you train your people on using those use cases and then you kind of know exactly to the highest level of detail what they should do and how they should learn it.

[00:14:48] [SPEAKER_00]: That just doesn't exist yet for a lot of these use cases.

[00:14:51] [SPEAKER_00]: The bottom up approach would be we'll just get everyone a subscription to one of these services and see what they come up with right now because that does justice to the variability of skills and capabilities and interest that your employees have.

[00:15:04] [SPEAKER_00]: And you will not have a way to even measure the success of integrating AI into the workspace.

[00:15:11] [SPEAKER_00]: So you have to have a combined approach and that combined approach is really for the way, let's say, take Augury as an example, we've implemented three levels.

[00:15:19] [SPEAKER_00]: First, first levels. Let's just make it available for everybody and make sure that people are aware of what's happening.

[00:15:25] [SPEAKER_00]: Then we're going to make sure that we have leaders who are early adopters of this technology actively utilize and create use cases and educate others on what they did specifically.

[00:15:39] [SPEAKER_00]: And then as a third stage, then we start institutionalizing these use cases because we're now building a body of knowledge about these use cases.

[00:15:46] [SPEAKER_00]: Specifically, we have leaders champions for these use cases with an organization.

[00:15:52] [SPEAKER_00]: And now we can actually have some level of structure on how we start educating the workforce and how to use it.

[00:15:58] [SPEAKER_00]: We are a tech company specifically in the AI space. So it's a little bit easier for us.

[00:16:03] [SPEAKER_00]: Most people are aware and most people are already using it.

[00:16:06] [SPEAKER_00]: If your company that's not in that same space, I think the same approach would apply.

[00:16:10] [SPEAKER_00]: You have to find first your people who are most interested in it and then empower them to formalize some of these use cases and spread them around the organization.

[00:16:21] [SPEAKER_00]: And what's really important is that continuous loop of showcasing of feedback, of improvement that you have to ingrain here just because the pace of this technology and the development of this technology doesn't happen at the creators, meaning like companies like OpenAI or Microsoft or others.

[00:16:39] [SPEAKER_00]: It's not that they're not the only ones who are contributing to the creation of this technology and the pace of its development.

[00:16:44] [SPEAKER_00]: It's actually the users that are doing that together with them, right?

[00:16:49] [SPEAKER_00]: It's very plausible that a company that came up with a completely new use case that will then be adopted by millions of people across the world.

[00:16:57] [SPEAKER_00]: And that might be the first since not the company that actually created the LLM or the chatbot that thought about that use case.

[00:17:03] [SPEAKER_00]: So it's very important to use it and use it in that way that creates iteration that spreads at both bottom up and top down at the same time.

[00:17:11] [SPEAKER_01]: And before you return to the podcast today, I was doing a little research on the kind of thing you've been talking about.

[00:17:16] [SPEAKER_01]: And I was reading that you mentioned that in five to 10 years from now, AI literacy will be assumed for any front runner applicant.

[00:17:23] [SPEAKER_01]: And it's hard to see how that won't be the case.

[00:17:26] [SPEAKER_01]: But I'm curious if you look into that virtual crystal ball, how do you see this impacting the entire hiring process and the skills that are going to be prioritized and employed?

[00:17:36] [SPEAKER_01]: I appreciate it. So it's a while off, but the speed and things are moving is probably sooner than many realize.

[00:17:42] [SPEAKER_00]: Yeah, absolutely. I think here in this case, we have some form of standardized testing during the interview process of hiring the applicants today for skills.

[00:17:51] [SPEAKER_00]: And I think that approach is going to transition more towards outcomes.

[00:17:59] [SPEAKER_00]: Show me what you can do with this technology.

[00:18:02] [SPEAKER_00]: And it's moving from, let's say high school into the job market university.

[00:18:08] [SPEAKER_00]: In high school, a lot of the times you get judged by how you think the thought process,

[00:18:14] [SPEAKER_00]: going through the steps or making the right logical arguments.

[00:18:18] [SPEAKER_00]: So the thought process is important or your capabilities, what goes in your head are important.

[00:18:24] [SPEAKER_00]: But once you get into the job market, well, it's not about how you think it's what can you do and what are the outcomes?

[00:18:31] [SPEAKER_00]: And so here I think it's a similar transition in terms of it's not so much about your skill set and experience as much as it is.

[00:18:39] [SPEAKER_00]: Can we test really quickly for what you can do utilizing these types of tools?

[00:18:46] [SPEAKER_00]: Right. How deeply is it ingrained into your workflow and the tasks that we would ask our employees to accomplish,

[00:18:52] [SPEAKER_00]: even if it's like a test task or maybe they come in and actually work with your team and do the actual work that you're expected to do on the job as a test case.

[00:19:01] [SPEAKER_00]: I think that would be a much better measure for whether on a performance level or productivity level,

[00:19:07] [SPEAKER_00]: that employee would be a good fit for your organization in addition to culture and other aspects that we take into account when we're hiring.

[00:19:15] [SPEAKER_00]: And it'll be I think it'll be easier to test. Right.

[00:19:17] [SPEAKER_00]: If we just test today for knowledge or skills, that employee can quickly utilize AI to answer the questions correctly.

[00:19:24] [SPEAKER_00]: But can they perform a task in real time while utilizing the AI?

[00:19:29] [SPEAKER_00]: I think that would be a better test.

[00:19:31] [SPEAKER_01]: 100% with you. And something I always try to do on this podcast as well is maybe try and bust a few myths, a few things you might hear that maybe frustrate you.

[00:19:40] [SPEAKER_01]: So what are some of the common misconceptions about AI literacy and its role in the workplace?

[00:19:46] [SPEAKER_01]: Anything you'd like to address there that we can finally lay to rest?

[00:19:49] [SPEAKER_00]: Yeah, I think the two main misconceptions, one is AI is here to replace us.

[00:19:53] [SPEAKER_00]: Right. As I mentioned, I think AI is just a tool like electricity or mathematics or anything else that's fundamental to how we will work in the future.

[00:20:05] [SPEAKER_00]: We're starting to work today and it will create a tremendous amount of productivity.

[00:20:12] [SPEAKER_00]: But you have to you have to use it right.

[00:20:14] [SPEAKER_00]: And then you will know specifically what parts of what you are doing or somebody else in your role is doing that it is going to augment or displace or replace.

[00:20:24] [SPEAKER_00]: But your role will evolve and everybody else's role will evolve right now with as long as you use it.

[00:20:30] [SPEAKER_00]: The second one is that AI literacy equals some kind of engineering or science degree.

[00:20:37] [SPEAKER_00]: And I think as the interface has become more and more natural and human like with these AI systems, as they become much more sophisticated,

[00:20:48] [SPEAKER_00]: can actually create a rapport between the user and the AI system, then it becomes like a core worker.

[00:20:55] [SPEAKER_00]: Right. So it's less of a tool, but really more of a persona that is in your life and your work life.

[00:21:00] [SPEAKER_00]: And that's enabling you to do a lot more.

[00:21:03] [SPEAKER_00]: And the basic skills required to interact with AI are not a degree of math or computers, software engineering.

[00:21:10] [SPEAKER_00]: They're just human basic human skills of interaction, reasoning, conversation.

[00:21:15] [SPEAKER_00]: So I think those are the two biggest myths I've encountered.

[00:21:19] [SPEAKER_01]: And I had a tech conference in the US recently had a number of interviews lined up and one particular let's just say a US bank had to cancel

[00:21:27] [SPEAKER_01]: because their management pulled the idea at the last possible minute because they didn't want their brand to be associated with AI in any way, shape or form,

[00:21:36] [SPEAKER_01]: which I felt was a little bit strange at the time.

[00:21:39] [SPEAKER_01]: But I'm curious for businesses that are hesitant to embrace AI, what are the stakes if they get it wrong?

[00:21:45] [SPEAKER_01]: And what immediate steps can they take to start integrating AI literacy into their operations?

[00:21:50] [SPEAKER_01]: Because in some industries there is that unease still isn't there?

[00:21:54] [SPEAKER_00]: I think there's a healthy level of unease around anything new, but especially AI when we talk about an established brand and the certain way they interact with their customers

[00:22:05] [SPEAKER_00]: and certain level of service and then replacing that with a technology that will not necessarily meet customer expectations or in some cases might hallucinate

[00:22:14] [SPEAKER_00]: and provide a completely embarrassing wrong answer.

[00:22:17] [SPEAKER_00]: So that's completely understandable.

[00:22:18] [SPEAKER_00]: In our world, in the world of the industry manufacturing, building reliable and responsible AI that provides a highly reliable, highly accurate result is paramount.

[00:22:31] [SPEAKER_00]: We can't emphasize that more.

[00:22:34] [SPEAKER_00]: So we build reliability and responsibility into the AI systems and how customers interact with from day one.

[00:22:42] [SPEAKER_00]: So that's super important.

[00:22:43] [SPEAKER_00]: So making sure that's in place and making sure that you have measures in place in order to have put a check on AI and the value it provides or any of those tools.

[00:22:55] [SPEAKER_00]: You have a person in many cases making sure that the answer that you give to customers is not just automatically generated, but there's some level of review, for instance, and so forth.

[00:23:05] [SPEAKER_00]: So those types of measures absolutely have to be in place for any business.

[00:23:10] [SPEAKER_00]: You have to make sure because that's your responsibility to customers, to stakeholders.

[00:23:16] [SPEAKER_00]: But that's not the same as AI leaders, right?

[00:23:20] [SPEAKER_00]: Making sure that the people within your organization utilize these technologies is also part of your responsibility to your employees and also to your customers, to your stakeholders outside the organization.

[00:23:32] [SPEAKER_00]: Because otherwise you will not be able to move at the pace that the technology is moving at and the world is moving up.

[00:23:39] [SPEAKER_00]: So you absolutely have to do both.

[00:23:41] [SPEAKER_00]: Be responsible about how you utilize the AI and also invest as much as you can in AI literacy for your workforce.

[00:23:50] [SPEAKER_00]: And then from there, you can start innovating, right?

[00:23:53] [SPEAKER_00]: That will provide you a tremendous advantage if you can innovate around these capabilities in the future.

[00:23:59] [SPEAKER_00]: But you start with enabling your workforce to utilize these tools safely.

[00:24:05] [SPEAKER_01]: I think another thing that we're looking forward to doing is finally removing silos from the workplace.

[00:24:11] [SPEAKER_01]: How can cross-functional collaboration better enhance the integration of AI across the workplace?

[00:24:18] [SPEAKER_01]: And I'm curious, are there any examples of what you've seen out there where it's been particularly successful?

[00:24:23] [SPEAKER_01]: Because I think there's a lot of people or a lot of businesses put the tech in, but they struggle with the culture change within an organization.

[00:24:30] [SPEAKER_01]: Have you seen anyone that's got it right?

[00:24:31] [SPEAKER_00]: Well, I think I mentioned earlier a lot of our customers have it right.

[00:24:35] [SPEAKER_00]: And based on the ability to start trusting the AI insight, once you realize for let's say a specific use case, let's take machine health, for example, predicting machine malfunction.

[00:24:46] [SPEAKER_00]: So once you realize that AI can do that 100 times faster and in order of magnitude more accurately than a person.

[00:24:55] [SPEAKER_00]: So you understand what are the limitations of AI, but also where is it?

[00:24:59] [SPEAKER_00]: What are the limitations of humans?

[00:25:00] [SPEAKER_00]: And where AI goes well beyond human capacity.

[00:25:05] [SPEAKER_00]: Once you trust the results that it provides, you start changing your workflow and the way you work based on that foundation.

[00:25:12] [SPEAKER_00]: So I mentioned we have insights that tell you what's wrong with the machine, how to fix it or your multiple machines, multiple factories and so forth.

[00:25:20] [SPEAKER_00]: Now you have to bring together different experts from different previously siloed departments to talk to each other and collaborate on what should we do at the strategic level?

[00:25:32] [SPEAKER_00]: How should we change our maintenance practices?

[00:25:34] [SPEAKER_00]: How should we change reliability?

[00:25:36] [SPEAKER_00]: What should we do with our operations based on this new found knowledge?

[00:25:41] [SPEAKER_00]: And then that newfound knowledge becomes the new baseline of how you operate.

[00:25:45] [SPEAKER_00]: So it becomes almost irresponsible to run a factory without machine health in place or process health in place without AI telling you what is the status of your equipment or your processes.

[00:25:58] [SPEAKER_00]: So that is what enables a different type of collaboration.

[00:26:01] [SPEAKER_00]: First of all, how do we change the way we work?

[00:26:03] [SPEAKER_00]: But also how do we address specific issues that are strategic that we could not address before because we didn't just simply didn't have the insight to do that.

[00:26:11] [SPEAKER_00]: And I think you will see that not only in manufacturing, you will see that across the board in multiple companies.

[00:26:17] [SPEAKER_00]: When AI starts providing like a baseline of insights that are beyond human capacity across different functions within the organization, you'll see a different level of collaboration and also innovation between the departments between the different functions.

[00:26:32] [SPEAKER_01]: So many big takeaways from our conversation today.

[00:26:34] [SPEAKER_01]: I cannot thank you enough for spending even more time with me.

[00:26:38] [SPEAKER_01]: You've already been on before.

[00:26:39] [SPEAKER_01]: I'm going to see if there's something we can do for you now because some of the biggest names in business VC funding and tech have either been guests or maybe even listened to this podcast.

[00:26:48] [SPEAKER_01]: So is that a person you'd love to have a private breakfast and lunch with?

[00:26:52] [SPEAKER_01]: Who would it be and why he or she might just be listening to this?

[00:26:55] [SPEAKER_01]: But let's see what we can manifest together.

[00:26:58] [SPEAKER_01]: Who would it be?

[00:26:59] [SPEAKER_00]: That's interesting.

[00:27:01] [SPEAKER_00]: There's so many.

[00:27:03] [SPEAKER_00]: There's so many people, but I'm a big fan of first of all your podcast, but also of Lex Friedman's podcast.

[00:27:11] [SPEAKER_00]: Share quite a lot of things in common with him.

[00:27:13] [SPEAKER_00]: But I'm just a fan of the variety of different guests that are there and the depth of conversations.

[00:27:18] [SPEAKER_00]: I thought really the balance between going widely across the different fields and then diving deep into AI, which is one of my favorite topics as well.

[00:27:26] [SPEAKER_00]: So I think there's a lot there for me to learn from a conversation with somebody like that.

[00:27:33] [SPEAKER_01]: What a great choice.

[00:27:35] [SPEAKER_01]: I'll throw it into the universe, into the ether.

[00:27:38] [SPEAKER_01]: Let's see what we can make happen there.

[00:27:40] [SPEAKER_01]: But for anyone listening just want to find out more information about all agree with the work that you're doing follow you, etc.

[00:27:46] [SPEAKER_01]: Where's the best starting point for everything?

[00:27:48] [SPEAKER_00]: Check us out.

[00:27:49] [SPEAKER_00]: I'll agree.com.

[00:27:50] [SPEAKER_00]: I think that's a great place to start.

[00:27:52] [SPEAKER_00]: And if you're an industrial manufacturing space or anywhere where there are large machines and big heavy processes, that's, I believe, where we can be really helpful.

[00:28:04] [SPEAKER_01]: Well, as I said a few moments ago, pure gold for me.

[00:28:07] [SPEAKER_01]: I love how you at a time where so many people are thinking AI literacy is the different rate is how you believe that AI literacy is becoming a fundamental skill, just like basic reading and instead of replacing role, you see AI replacing certain tasks, especially amongst those entry level roles.

[00:28:27] [SPEAKER_01]: It's such an important message to send out there and workers, they should just focus on honing that a higher level strategy and judgment skills, cross functional collaboration.

[00:28:38] [SPEAKER_01]: But using AI as a tool is pure magic.

[00:28:40] [SPEAKER_01]: But thank you so much for shining a light on this and making these important points.

[00:28:45] [SPEAKER_01]: Thanks for joining me today.

[00:28:46] [SPEAKER_00]: Thank you so much for having me.

[00:28:48] [SPEAKER_01]: As we conclude our discussion with Artem, I think it's clear that AI literacy is more than just a skill.

[00:28:55] [SPEAKER_01]: It's an imperative adaptation for thriving in this modern workforce and it's always a pleasure to get on the podcast.

[00:29:03] [SPEAKER_01]: So many rich insights.

[00:29:04] [SPEAKER_01]: And I think his perspective on integrating AI seamlessly into our work and enhancing our strategic capabilities offers a roadmap not just for employers but for employees too.

[00:29:17] [SPEAKER_01]: And the challenge seems to be in balancing the rapid integration of AI with nurturing the human skills that complement this technology.

[00:29:26] [SPEAKER_01]: And it's all about the two of those things together, human skills complementing technology and completing tasks quicker and more efficiently and better than either ever could do on their own.

[00:29:38] [SPEAKER_01]: So the question is how is your organization fostering AI literacy?

[00:29:42] [SPEAKER_01]: How are you ensuring you're not leaving anybody behind?

[00:29:45] [SPEAKER_01]: Are you finding new ways to leverage AI in enhancing job performance?

[00:29:50] [SPEAKER_01]: How are you bringing people along?

[00:29:51] [SPEAKER_01]: How are you training your existing staff?

[00:29:54] [SPEAKER_01]: Please share your stories, insights and thoughts with me.

[00:29:57] [SPEAKER_01]: This is a conversation that's impacting everyone so I'd love to hear your thoughts on this.

[00:30:02] [SPEAKER_01]: So Artem thank you for your deep dive into AI literacy and its impact on the evolving workplace landscape.

[00:30:08] [SPEAKER_01]: And for you listening, yeah I mean you, email me now.

[00:30:11] [SPEAKER_01]: You can find me on the tech blog right at outlook.com, Twitter, LinkedIn, Instagram at Neil C Hughes.

[00:30:17] [SPEAKER_01]: But enough talk of AI for one day. I'll be back again tomorrow with another guest and another topic.

[00:30:22] [SPEAKER_01]: But thank you for listening today and until next time, don't be a stranger.