EP 363: Navigating the Changes of Generative AI in Work & Industry

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The very definition of jobs and how we work is changing before our very eyes and is actually changing quicker than maybe ever, right? Like when we look at past innovations such as the Internet, cloud, mobile, I think that generative AI is maybe redefining how we work faster than any of these previous tech innovations. And that's what we're going to be talking about today and a lot more on everyday AI. What's going on, y'?

All?

My name is Jordan Wilson and I am the host of Everyday AI and this is for you. This is your daily life live stream podcast and free daily newsletter helping everyday people like you and me learn and leverage generative AI to grow our companies and our careers. So if that sounds like you, first of all, thank you for tuning in. If you're on the podcast, make sure to check out your show notes for a link to our website, your everydayai. Com each and every day. Yes, we grab all of the most important insights and we recap today's podcast in our newsletter. So make sure you check that out. All right, I am extremely excited for today's conversation, but before we get started, we're going to do as we do every day and go over what's happening in the world of AI news. So first, Microsoft, according to reports, is set to revive the Three Mile island nuclear plant to power AI growth. So Microsoft has announced a groundbreaking deal to purchase 100% of the power generated by Pennsylvania's dormant Three Mile island nuclear plant for the next 20 years. This agreement aims to address the tech industry's escalating energy demands, particularly for artificial intelligence. The restart of the Three Mile island plant, which was closed in 2019 due to technical difficulties, is slated for 2028. According to Constellation Energy, the plant's owner, the Three Mile island site is historically significant as the location of the worst nuclear accident in US history, raising questions about safety in public perception surrounding nuclear energy. By committing to a long term energy purchase, Microsoft is positioning itself to meet the growing energy energy demands of AI while potentially influencing other tech companies to consider similar energy strategies. All right, our next piece of AI news. I like this one. This one's personal here. All right, a tech billionaire is making headlines this morning as he warned of AI's impact on jobs and workforce management. So according to Jim Kavanaugh, the CEO of Worldwide Technology, Corporate leaders need to start BSing their need to stop BSing their employees and be honest with them about the transformative effects of artificial intelligence on the workforce. So in a recent interview, Kavanaugh asserted that employers are too smart to believe that AI will not change their work environments or eliminate jobs, emphasizing the need for transparency from leaders. So he believes that trying to downplay the impact of AI on jobs is misleading, stating, if you think you're going to try to game this, that's just bs. All right, so he acknowledged that while AI will disrupt some jobs, it is also likely to enhance productivity and create new opportunities, emphasizing an optimistic outlook on AI's potential if only some you know, this same tech billionaire laid out his generative AI blueprint for success. Oh wait, he did that with us when he joined the Everyday AI show earlier this year. So make sure to check out the show notes if you want to catch that episode. All right, our last piece of AI news. OpenAI's $6.5 billion funding round is facing high demand and selective backing. So OpenAI, according to reports, is nearing the final stages of a significant $6.5 billion funding round which has attractive has attracted overwhelming interest from potential investors. So the funding round is oversubscribed, indicating that investors are eager to contribute more capital than OpenAI is willing. So reports suggest that the excess demand could reach billions of dollars, highlighting the high stakes involved in this financing effort. Prospective investors will learn today on Friday whether they have been selected to participate in this lucrative deal, adding an element of suspense in the proceedings. Speaking of OpenAI, its CEO Sam Altman acknowledged recently in an interview with T Mobile on the progress of its new Zero1 model. So in the interview, Altman alluded to the company's own internal roadmap of the five stages to AGI, or artificial general intelligence. He all but acknowledged OpenAI achieved level two, which is reasoners with its O1 model. And that level two achievements means that level three could be achieved very quickly and that level three is agents. All right, a lot more on the AI news in today's newsletter, so make sure you go check that out@your everydayai.com all right. But that's not what we're talking about today. We are talking about how AI is fundamentally changing jobs, changing the workforce. So I'm excited for today's show. So let's go ahead and bring on to the show. There we go. We have Kumar Parakala, the president of GHD Digital. Kumar, thank you so much for joining the Everyday AI Show.

Good morning Jordan, and it's a pleasure to join your very top rated show. It's a great pleasure. Privilege.

All right, well hey, thank you for joining us. And you know, shout out to everyone joining us live. Tuning in to hear from Kumar. So Rolando, Tara, Daniel, Marie, Kurt, everyone else, if you do have a questions for Kamar, please make sure to get it in now. But before we dive in, Kamar, you obviously have a very, very impressive background in the industry, but maybe tell everyone a little bit first about GHD Digital, if you haven't heard of, of you guys.

Yeah. Jordan, GHG Digital is a digital transformation professional services business that I had the opportunity and honor of founding about six, seven years back. It was created as a part of the GHD Group, which is a global professional services company. And we've got about 12,000 people in ghd and we specialize in architecture, engineering, construction, industry related services. And yeah, so we are rated now GCD is rated number one in the industry for innovation and helping clients with digital transformation acceleration. And we are quite pleased with what we have achieved in the last five to six years.

Yeah, and maybe let's even set the stage there. Kumar. So even over the last five or six years, right. Artificial intelligence is nothing new.

Right.

It's been around for many decades, but how would you say that generative AI has even changed the work that you all do?

Yes, I think generative AI has taken us by storm. And we saw that happen in 2022 when we had the release of ChatGPT, which surprised everyone. You know, AI has been there since 1940s when, you know, two researchers, Michalak and Pitt, felt structures in the brain are similar to electrical structures. And for the next 60 years or more, attempts were made to implement electrical circuits. And then we moved to software. At the beginning of 2005 we started doing deep learning and big data and the computer power started increasing. And then in 2012 we had GPUs and they revolutionized the kind of computing processing needed. And as a result of that, today Nvidia is one of the most valuable companies of the world, as you very well know. So over the last, since 2020, 2012, over the last decade or so, from then onwards we have very large neural networks, vast amounts of data and huge computing power creating this situation where we have intelligence being generated by machines. And as a result of that, the whole conversation about AI has shifted. The power of AI has shifted and people are very excited about what is possible. So whatever we are seeing, it's all happened in the last four or five years, this acceleration. And this will continue to happen and it will Change the way we live and change the way we work.

So let's dive into just that. So even GHD digital, you all work in and around the AEC industry, architecture, engineering and construction, how would you say already? And you kind of referenced this kind of, this almost shift right in, in 2022 with large language models. But how has AI, specifically generative AI already started this, maybe redefinition of jobs in the AEC industries?

Yes. So our prediction is, and these are happening to various varying degrees, taking into consideration that the real impact of gen AI has started becoming visible only since last year, it's not been there forever. So we're talking about a late 22 November, December, but generally 2023 onwards. So we are, we are talking about less than 18 months here. And during the and 18 months things have had, a lot of things have happened, you know, in our own industry, AC industry, we are seeing generative AI tools and prototypes being used for time and cost savings, for innovation, for decision making, for sustainability outcomes and safety outcomes. So those experiments, if I can say, are happening. We have close to 2,000 startups that have just propped up over the last 18 months to focus on the industry. So you can see the amount of innovation that is already happening in a very, very short time. And I have no doubt that we will be in a situation where it will add significant value to the design, build and maintain elements of the industry as we go. So, so our industry, like any other industry, is set for, you know, huge impact of AI. The work has just begun and it's important that everyone who is in the society should be seriously interested about what is possible and how they can play a role.

I want to go straight into that. I love that you said everyone needs to be interested in AI and its impact. Right. Because I think maybe traditionally when we've talked about AI, you know, people are like, oh that's, that's for the data people, right? That's for the, you know, computer scientists, that's for them. You said everyone should be interested in this right now. Why?

Yeah, I think, you know, we are going through one of the pivotal moments in the way in which the society operates and that is directly as a result of the intelligence that is going to be available to us, that is already available to us. You know, you can now talk to LLM models like Chat, GPT and others and they will answer you a lot better than any individual. And some computer scientists claim that these models are now smarter than a very well experienced legal professional or an accounting professional. So the quest for intelligence commoditization has already begun. Then what happens? What is the role? I mean, human beings were considered to be the most intelligent species. What happens if the machines then take over that intelligence? What is the role of the humans in that concept? Human machine collaboration is the new space. So we should be interested from multiple perspectives. One impact on the society, impact on the industries that we work, impact on the people that have those that are employed on those industries. And also shifting. You know, it's not only redefinition of jobs, is also shifting of the wealth and power. I very strongly feel that as the AI acceleration happens, technology companies will have a huge amount of shift in the power dynamics and they will become the most wealthy companies. Some of them will be wealthier than the nations. You know, for example, some of the tech companies have a greater revenue than the GDP of Canada. So tech companies will become very powerful. And how do you kind of regulate tech companies? Deep fakes, bias and toxicity will take over our Internet. So how do you deal with that? Because that will have a harmful. That's the third impact. And that's the reason why we should be very, very, very careful, very serious about this. And last but not least, AI race is going to be the new arms race. So we will have the Russian AI or the Chinese AI or the American AI or the Indian AI. And because this is intelligence. And that will again have a huge impact on the world order, on geopolitical dynamics. So AI, whether we like it or is going to impact all of us. And that is the trajectory that we are on right now. And therefore we should be very interested in whatever is happening around us in this space.

I love that answer. Kumar is just bringing the, the spicy takes already and we're only a couple minutes in. I love it. So, you know, one thing that you even said there, right, you, you talked about and acknowledged some of these, you know, huge downfalls of, of generative AI, right? Like deep fakes and biases and toxicity. I think that's important to call out. And I think sometimes we think, right, we think, oh, these are things that just impact us in, in our personal lives, right? On social media. But I'd say maybe not, right? Because also if large language models are essentially reflections of public information on the Internet, that gets scraped, right? So what dangers maybe do the future of generative AI also present for companies, right? Because I think sometimes we only focus on the premise or the promise. But you know, you are the president of one of the companies that's a global leader in digital transformation in a $200 billion industry. So what are some of the things that you maybe worry about or challenges when it comes to generative AI in the workplace?

Yes, Jonathan, so you said something very important, very profound, and that is the way we engage with the AI systems will create our future. Okay, so what that means is you said, okay, they're taking a huge amount of data, and for example, ChatGPT3 had 500 billion words, that it use 175 billion parameters. So they take huge amount of data in the process. But if that data, which is again generated by humans has got biases and toxicity and something undesirable, the AI models will bring out that. And if something is good is put into, put into the system, they'll bring that out. So it's very important to be conscious users of all AI models. And because that data is being used, the data is being recirculated, that data will be again used for future purposes. So from futuristic perspective, again, having that guardrails, having the data quarantined, having that data reviewed is absolutely critical for responsible AI.

So let's get into that piece. The data, that's everything now, right? Even our company has personally, we've worked with, you know, small companies doing, you know, $20 million in revenue, and we've worked with companies that are doing 20 billion. And every single company, it seems, has a different stance on their data and, and how they're going to maybe integrate it or not integrate it with large language models. So maybe, you know, you kind of said, kumar, hey, this is an AI arms race. And you kind of mentioned the different companies, but I assume that is also within different industries as well. So maybe whether you want to talk about it personally through GHD Scope or if you want to talk about the bigger picture, is that also going to be the same for different industries and who wins and who loses in this new competitive business landscape?

Yes, Jordan, I think data strategy is the most important aspect of any successful AI application. And for example, in our own industry, I'll just give you an example. We had a client in, in the agriculture sector who faced regulatory compliance challenges due to their plant expansions and evolving regulations, and they were risking significant fines. And this is also a challenge for many in financial services sector as well. When they don't comply, they get huge fines. One of the clients, one of the companies that I know, they almost got $150 million in fines. So what we did, what my team did, utilizing AI and machine learning, is to develop a system that mapped operational limits to regulatory requirements and then we use the Internet of Things devices to connect to different daily operating limits to equipment, ensuring, collecting a lot of data, processing that data and then ensuring compliance. This impact was substantial because, and that's what is needed, our client was able to get a real time insights into improving their regulatory reporting and being able to undertake predictive maintenance, reducing errors and of course making fast decision making. But last but not least, they were also able to save about $3 million per year. So that's a great example and also very related to the topic of this conversation, industrial processes. We have examples which we are aware of where AI is being used in industrial processes for predictive maintenance, demand forecasting, waste reduction, quality improvement, and also supply chain management. These are all direct applications. And again, the whole generative AI paradigm is only 18 months old. We're already seeing active use. And this example that I've given to you is a good example where we are ourselves experimenting with generative AI.

And I want to go right to that. Right. So yes, generative AI is only, you know, 18 months old, right. For the most part. But it feels like in terms of development and updates, we've seen 18 years worth. Right. Because every day there's a new model, there's new best practices. Right. And it's extremely hard to keep up with. And then you also, Kumar just talked about risk. Right. So, but I personally think there's still this huge gray area and some ambiguity around large language models and data. Right. I've talked kind of off the record with multiple Fortune 100 companies and, and they have very different viewpoints on, you know, giving their data to large language models. So, you know, how should companies be approaching this? Should they be more cautious and have a slow and steady or should they know. Kind of like what you said, it is an arms race. You have to get in. You have to be one of the first. Right. In your industry if you want to get ahead. How should companies be approaching that?

Yes, it's a great question. And you know, different countries have got different legislative and, you know, regulatory frameworks and sharing data in one country could be relatively easier compared to sharing data in another country, like for example, United States. So what the leaders of these companies need to be very aware of is that, well, if it's highly confidential information, they should quarantine the data and keep it within the walls of their organization. But if it is like industry specific data, they should quite openly share. Because ultimately the competitiveness of any industry, including our own industry, which is architecture, engineering, construction industry, will depend upon the collaboration of the industry players if they don't collaborate, the technology companies, the startup companies, the others who are actually actively experimenting, they will beat the well established players. That's the whole paradigm of Christian Clayton Christensen's Innovation Dilemma Theory previously so that's already happening. That will continue to happen. I have no doubt in my mind that those who are nimble and agile will go far ahead compared to those who are slow and study and want to follow the bureaucratic ways of moving forward.

A great question here from Tara. So she's asking, what is your elevator pitch to those who are skeptical skeptical or resistant to AI adoption? And how do you address the concerns of naysayers who believe AI may pose more risk than benefits? Are you still running in circles trying to figure out how to actually grow your business with AI? Maybe your company has been tinkering with large language models for a year or more, but can't really get traction to find ROI on Genai. Hey, this is Jordan Wilson, host of this very podcast. Companies like Adobe, Microsoft and Nvidia have partnered with us because they trust our expertise in educating the masses around generative AI to get ahead and some of the most innovative companies in the country hire us to help with their AI strategy and to train hundreds of their employees on how to use Gen AI. So whether you're looking for ChatGPT training for thousands or just need help building your front end AI strategy, you can partner with us too. Just like some of the biggest companies in the world do. Go to your everyday AI.com partner to get in contact with our team. Or you can just click on the partner section of our website. We'll help you stop running in those AI circles and help get your team ahead and build a straight path to ROI on genius.

Yeah, I mean I'd like to be a little bit provocative here and I would say to those ignorance is bliss. Do you want to be in that blissful state or you want to come out of it? Just look around what is happening and open your eyes. Just look at what capabilities Chat GPT just download it. It just probably cost you 10 or $15 a month and start playing with it and then start asking chat GPT 4.0 some questions and see the power of what it is. So you can't do anything. For those who want to close their eyes and don't want to participate. But those who want to really who are willing to experiment, I think they should experiment with these various models and they will understand the transformative power of these models and they'll very soon start Adopting them in their own ways of working, and that will lead to shifts. So my message is, yeah, I'll motivate people to look around and start experimenting and playing. Don't be in the state of ignorance is bliss.

I love, I love that. That's such a great answer. Right. Just cut it off. I tell people it's like, y' all look at Follow the money, right? The six largest companies in the U.S. yeah. Have all gone all in on AI, both with their investments, their time, their resources, their humans. Right? You got to follow the money. So one, one question. Another question I have for you, Kamar, is kind of just the, the capabilities of these AI systems. Right. So we talked about, you know, in the last 18 months, how quickly they're changing. Right. So how do you, as the head of a very large company, you know, keep track of this? And there's all this, this talk, oh, you know, this new O1 reasoning model from OpenAI and, you know, AGI, artificial general intelligence. Right. As the president of a very large company, how do you both, you know, keep your eye on those developments and, you know, take advantage of them, yet do the right thing around, you know, the future of work and ethical AI, Right. Like, how do you balance those things?

Yeah, that's a great question, Jordan. And no one can get their hands around what, what is happening as far as the evolution of knowledge is concerned. The, the evolution of AI and technological developments are far greater than we can really keep up with. So what I do is I collaborate. I read a lot, but I collaborate. I'm a member of a leadership team in Silicon Valley where a lot of this innovation is happening. And I try to focus on areas that will directly impact my industry, my people, and society in general. And then I motivate my, my clients to think about some of those changes, and we get into a mode of active experimentation and, and again, on the other side, I engage, I'm engaging, like many other leaders, with regulators, lawmakers to explore how do we put guardrails to be able to manage something like this, which is again growing at an explosive pace. So the engagement of all leaders need to be multi dimensional, including if you're a CEO or chairman of the board, you have very important role to play in the use of AI. And also definition of the path for future use of AI. You cannot simply delegate this to technology people and say, hey, I'll look at it when the time is right. Because for me, AI transformation is business transformation, and that's the only way to remain competitive in the business. There's no escape from it.

One more quick question from our audience here before we start to wrap. Kumar. So Monica asking what specifics are you seeing on how AI is impacting your industries?

Yes, there are many examples that we are beginning to see. They're all in experimentation stage. But I'll give you one use case that we have successfully achieved. As you know, GHD supports the infrastructure industry, roads, dams, ports. We support the building of those industries and building of those assets. So road authorities, if we take the road, roads, you know, everybody's familiar with roads. Road authorities typically manage large number of standards and guidelines which are relied upon not just by their own technical staff, but also industry and local government authorities. And these standards and guidelines are different for every state and they vary in a very, very big way. With the advent of generative AI large language models, a client of ours asked the question, can LLMs enable the automation of identifying documents across that can cross reference and assist with prioritizing key updates? We worked with our clients in an experimental co creation mode and the results of a trial on various road design and operation documents. We were able to achieve almost 95% accuracy in cross referencing and identification of relevant documents which are again very, very complex. So we have now started implementing a generative AI enabled tool called AI Library and again complex data AI has been able to help. Generative AI tools have been able to help us, you know, increase speed and you know, reduce many months of effort to a few minutes. So we are experimenting. So that's a great example. We know that generative AI is being used for design purposes. We know that generative AI is being used for environmental and sustainability outcomes. So there are other applications too that my team is working on. Again as I mentioned, they're all in, in stages of experimentation as we speak.

All right, Kumar, we've, we've talked about a lot today. We've covered a lot of ground and, and some great insights, you know, from how jobs are changing rapidly in the post generative AI world, the transformation of jobs in the AEC industries, how AI ignorance is bliss. I love that one. But maybe what is your one most important takeaway here as we wrap up the show? You know, about how AI is transformed, transforming traditional workflows and processes and you know your best piece of advice for a roadmap for success.

Yes. So I'd like to say the quest for machine enabled intelligence is now on and that is doubling every 12 months the intelligence that is possible. So my one liner is empower innovation through AI because that will then allow you as individuals and as companies to not only survive but thrive in this rapidly changing, digitally accelerated world.

I love it. Survive and thrive. That is what we're all about. And that is a great takeaway from today's show. Kamar. So thank you. Thank you so much for joining the Everyday AI show. We really appreciate your time.

Thank you, Jordan.

And hey, as a quick reminder. Yeah, we covered a lot there. So many great insights from a industry leader in Kamar. So if you haven't already, please make sure to go to your everydayai.com Sign up for the free daily newsletter where we will be recapping everything that happened on today's show and everything else in the world of AI so you can keep up with. So thank you for joining us and we hope to you see see you back for more Everyday AI. Thanks y'.

All.

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