89. The AI-Enabled Leader

Intro: Duration: (04:58)

Opening music jingle & sound effects

Jeff Hunt:

Welcome to the Human Capital podcast. I'm Jeff Hunt. Today I'm devoting another episode to artificial intelligence, which is by far the most transformational technology of our time. My question for you today is, if you are a leader, have you started reshaping employee jobs to be more synergistic with AI? Not only boosting accuracy and productivity and creativity, but also with a goal of making your organization more human centric, not less human centric. My second question is, how well are you integrating AI into your workplace without compromising the core human values of collaboration and trust? and employee engagement.

Lastly, does your company's two to three year strategic plan include Agentic AI? Agentic AI is perhaps one of the most consequential shifts coming, which will pivot AI from being reactive to highly proactive, creating independent agents that will change the way we work and lead. To explore all of this, I'm honored to invite Mr. Bernard Marr to the mic today.

Bernard is widely recognized for his expertise in areas like big data, AI, the blockchain, the internet of things, and digital transformation. He's known for breaking down complex topics into understandable insights, helping to harness the power of data and emerging technologies to improve business performance.

Bernard hosts a very popular podcast called the future of business and technology. And is over 2 million followers on LinkedIn significantly benefit from his thought leadership. He's authored numerous bestselling books including Data Strategy, big Data in Practice, and the Intelligence Revolution where he explores the practical applications of AI and data analytics.

And by the way, we'll put links to those books in our show notes. Bernard is also a frequent contributor to major publications such as Forbes, where he writes about technology trends and their impact on various industries. Welcome, Bernard.

Bernard Marr:

Thank you very much for this very comprehensive introduction, Jeff. Yeah, I'm looking forward to this.

Jeff Hunt:

This will be a fun conversation. And I'm just realizing that you're usually the one asking the questions because you're on my side of the mic, but today I get to turn the tables.

Bernard Marr:

Yeah, which is nice. I like sitting on both sides.

Jeff Hunt:

Fantastic. Well, you're such a amazing resource. I'm really excited to kind of dive into some of these topics. And before I do I'd love to. Yeah, before we do, just take a couple minutes to give us a thumbnail of your career journey. How did you end up in this space, this technology realm?

Bernard Marr:

Yeah, I think somehow by accident, like so many of us, um, I started, uh, I started a a university degree in business and one in engineering, a dual degree in Germany.

And my professor had a relationship with Cambridge. So I then went to Cambridge University to finish off my degree. And that went very well. And they then offered me a job. So I became a research fellow at Cambridge. And then again, the department I worked for moved from Cambridge to another business school, Cranfield School of Management, where I worked for 10 years doing research on how companies use data to inform strategic decision makings, uh, decision making.

So in the beginning, things like KPIs, analytics, and this area then became big data, then touched on AI. And my business school was very practice orientated. So I was running Lots of industry networks and with lots of companies and run executive education programs. And then people came to me and said, can you help us do this in practice?

So I then started some consulting work on the side, started to write more mainstream books and thought, actually, what do I want to do? And then I decided to leave academia and work for myself. And now I. Split my time between writing books and Forbes articles, helping companies understand future trends in practice.

So I do keynotes, lots of executive sessions, board advisory work and then also some training aspects. So I work I, Run courses for the IMI. I have a number of online courses. So, and I, I love it. It's so exciting. And that's how it started in the data space data as the foundation for everything that we're experiencing today.

But then it touched on, as you said, in the introduction on blockchain on AI. AI is now the most fundamental technology, the most transformative technology we have available today. And and then I started writing for Forbes on all future trends and now I write on future trends and business trends.

Topic 1. Who or what inspired you the most along the way? (04:59)

Jeff Hunt:

And along that journey, was there any one person or, or people that inspired you?

Bernard Marr:

So many, I, I have the real privilege to speak to CEOs of some of the, the biggest tech companies on the planet. And I wouldn't single anyone out. And I love having those conversations as well as academics. People have, who have written amazing books on this amazing thought leaders in the AI space. If I look back at some of the interviews, the one that probably stands out was when I was interviewing a digital pop star called Polar.

So she was a. a digital only version and then I started my podcast as myself and then I actually used my AI avatar to do the interview with a digital pop star, which I blew my mind. And I love that.

Jeff Hunt:

Fascinating. We'll have to check that out. Like how long ago was that? And we'll go search on your podcast.

Bernard Marr:

Yeah. If you look for, if you search Polar P O L O R and, uh, A R and, and my name, you, I'm sure you will find it.

Jeff Hunt:

That's such a great demonstration of how realistic A. I. can be in terms of representing someone, right?

Bernard Marr:

Yeah, exactly. And I, I did another interview recently with Boston Consulting Group, and they actually have an A.I. as part part of their podcast. So is, and she's called Jean. And again, we did a live demo. So I had the two people that created Jean, the podcast, podcast host, and then Jean coming in as well and joining the conversation, which was pretty cool.

Topic 2. Generative AI (06:47)

Jeff Hunt:

Wow. That is truly fascinating. Now, that was a couple of different guests on your show, when you reflect back on the last year, what's been the most interesting sort of topic or, or niche that you've explored on your show?

Bernard Marr:

The last year has been dominated by generative AI. This is by far the most. Important technology that I think humans have ever had access to it will transform so many aspects and this has been dominating most of my work is always interesting. How these. Things come in waves. Uh, two years ago, it was all about the metaverse.

Then this got crowded out by generative AI. And I always see my job as trying to cut through the hype and making things real. I don't think the, I don't like the word metaverse, but there, this is for me still a super important technology that we'll, And especially when you combine it with generative AI, it will have such a big impact.

So where you can use generative AI to create videos and music and, and, and, and so on.

Jeff Hunt:

Super interesting. And I think generative AI is a topic that many lay people just don't know very much about. So can you take just a minute to explain to the business leader that is is so consumed with running day to day operations and trying to manage his or her company and competitive threats and market driven changes.

And then all of a sudden this generative AI topic comes along and they don't really know anything about it. Can you take a second to just explain from a lay person standpoint, what this is and how this is going to impact us?

Bernard Marr:

Yeah, very simply, it is one type of AI is a, a large language model is based on machine learning technology, the AI that we've been using for a long time to do things like predict what we're going to buy next on Amazon.

Um, the only difference is that these are language models, so they've been, instead of. Being trained on, on data points. They've been trained on lots of language and we've basically taken pretty much all publicly available data, be it books have been published, articles written on, on the internet. Comments, anything that has been available, and we loaded this into these machines and they are now able to use this information to create content based on it.

So they are one of the first examples of AI is that I would call creative that can create content in the beginning. They could only create words. So, and they are basically probabilistic models. So they're saying, what. Is the next word that would make sense. So if you write a prompt, a human language prompt, like, please write me an article on AI, it will do this.

And the more context you give it, the better it will be at that. And then it literally says, this will be a good next word. This would be a good next word. So sometimes when we have conversations with these systems, because they now have evolved, it's not just a text conversation. We can have voice conversations with them.

And they. Appear hugely intelligent. But we sometimes have to take a step back and say, actually, they do not understand anything about the context. They don't understand what they're saying. They just use prediction to produce the next word. And very similar in that they, they are now multimodal. So it's not just text and voice.

They can now create images and increasingly. Powerful videos, so, and this works very similar. It just generates pixels and say, this pixel would make sense based on all the millions of data points I have.

Jeff Hunt:

That's such a great description. And it's a reminder. that these technologies are not human, even though sometimes they feel human. I mean, even to the point where you just mentioned that you interviewed an AI on your podcast. And so that I imagine was fairly realistic in terms of that overall. conversation, right?

Bernard Marr:

Hugely. Yes. And, and she was asking very intelligent questions and responding really well. So yeah, it would be, and it's a great demonstration that even though these systems are not truly intelligent, they can perform very intelligent functions and can be hugely useful for us in our jobs and potentially even threatening many jobs because maybe AIs will do a much better job than us two in the future.

Topic 3. Becoming human-centric (11:46)

Jeff Hunt:

Yes, exactly. And before we hit the record button, Bernard, you and I were chatting a little bit about the human centric approach that we take on this podcast and how we're often talking about culture. And I think if we could speak to business leaders for a minute, I'd like to help them understand better how to balance the AI driven efficiencies that are available to us that are truly transformative to an organization with how to maintain a human centric approach to leadership in business. And I'm wondering if you have thoughts about that.

Bernard Marr:

Yes, it's I think one of the most fundamentally important questions, uh, I, my belief is that we have to approach this in a human centric way, because if we simply try to replace people by these systems, they will in the end produce very dull results.

Unexciting content. At the moment, people get very excited if you think about, okay, AI can now draft your social media posts, and they can write articles for you, and so on. But the true value in these systems is not by replacing humans, but working alongside humans. And it's all about all of us. augmenting our capabilities.

And so if you use them to brainstorm and make your ideas better and see, so I use it quite often for my articles. When I write an article, I give it to an AI to say, have I missed anything? And, and that is, that's, really good because sometimes I think actually I could always say anything not clear enough.

And so I work with those tools to help me, but I wouldn't ever have this tool right for me because it takes away my competitive edge and also anything I really add as a human. So for me, it. It will, my hope is that will enhance us as human and what gives us superpowers, but there's a fine line that we shouldn't cross where we then become over dependent on it.

And what is interesting is I've recently written a few articles about some research that found that these models that we currently use are based on all humanly generated content. Now there's so much content that is generated by AI that there's a real risk that we train future large language models with AI generated content.

And that could in theory lead to a collapse of, of those models because they are. Like entering this weird cycle, whether then re using some of the content that they have produced. So we will always need human content creators. And, and, uh, and I think this is really important that for leaders and organizations figure out how these jobs will, uh, how, how these AIs will make our jobs better, how they ensure that we get the best out of machines.

And humans, where we leverage the best of people have and the best of machines and bring them together to create true value.

Topic 4. Using AI to improve our abilities and reduce bias (15:28)

Jeff Hunt:

Is what you just described analogous in some ways to a bias that could exist within these AI models becoming a potential echo chamber of itself. So in other words, if there is bias that enters in and then that's self propagating, it could become more biased or is that not an issue?

Bernard Marr:

Yeah. Bias is a tricky question when it comes to data because there's unbiased data doesn't exist. We humans need bias in our own decision making that we are somewhere in Africa and we see a lion, then our focus is all about how do we run away from this lion? Bias has worked in our favors for a long time.

We have so much information at our fingertips. We need to figure out what information we use to help us make better decisions. When we then use the entire internet as a basis, there is lots of content that is biased. That is, there's propaganda out there, there's misinformation out there. There are gender biases, racial biases.

And so you don't want. To have models that then further emphasize and carry on those biases and So if you ask an AI that was trained on all the data that we have, give me if we ask that, give me an image of a doctor, because in the past there was more male doctors than female doctors. There's a bias in all of this, and it might produce more pictures or only pictures of male doctors.

And if you ask for a nurse, it will give you female. We don't want this. So we can now have. We can adjust those systems. We can now fine tune those models to say, actually, when someone asks for a picture of a doctor, make it balanced. Give us a bit of both. Give us male and female, different races, and so on.

And, but we have to be careful doing this as well because we can take it too far. And Google has experienced this recently when they tweaked their Gemini AI. And suddenly when you ask it, Hey, give me a picture of, of a Pope, it would then create a black female Pope. Or you are, which would be great to have at some point in the future, but we haven't had this or historically wrong things like it would create a picture of Vikings that are, again, you have some black Vikings, some Chinese looking Vikings and so on.

And, and again, that is historically wrong. So we need to, I think companies are still working through this, how we address biases in those systems, but I think we need to be aware that. There will always be biases in data, but there are now ways to counteract that.

Jeff Hunt:

You mentioned earlier the importance of using AI in an augmented fashion to the work that we're doing.

So your example of the articles that you've written, that you've written, that you have AI check. And the path of least resistance is to just accept the content that it's producing, which is going to produce lower quality and also less personal content. That's reflective of our own thoughts and our own creative juices that are flowing when we produce content.

Thanks. And I have a two part question for you, which is really focused around agentic AI. The first is, describe what agentic AI is, or agent AI, and what that's going to look like in the future. And then the second part of the question is, how can we prevent This type of future where agentic AI is not involving the human in the way that you just described is so important.

Bernard Marr:

Yes. So, agentic AI is the, the. Cutting edge of AI at the moment where instead of just giving us an answer and give us output, like I want an, an article, I want a social media post from you, you ask the AI to also put to act on your behalf. So it will. Almost become your personal assistant. So you could ask the AI to not only create a social media post, but also put this up on LinkedIn and X.

And that would be an example of an agentic AI that then does something for you. It then fulfills a number of tasks that you, you ask it to do. And you can see how this is hugely Impactful when we think about improving productivity in our organizations, where you can think actually, instead of just asking it to create a, and a tweet that I want to put on eggs, it can also put it up for me.

And I can also maybe turn it into a longer version for LinkedIn. And so it will perform a workflow for you. And in the future, you can take it further and say, Hey, find out about a holiday that I would like. So companies like Expedia currently use generative AI on their website. So you can talk to it, say, I really like a holiday.

I want to go skiing, or I want to go somewhere warm. And I like the sea, and I don't like, Swimming boards and whatever it might, you might be might like or not like. And then it can suggest holidays for you. But a agentic AI then takes it a step further and could potentially then book it for you. And it can not only book the holiday, it can book your transport, it can book excursions and so on.

Jeff Hunt:

So trust becomes a critical component at that stage. Right.

Bernard Marr:

Yeah, hugely important. Trust is, I believe, one of the most important components whenever we talk about AI because it is so hugely transformative and there's a lot of mistrust.

There's lots of misunderstanding out there, but also mistrust. People are scared. They're worried about their jobs. They're worried about the impact of the AI. They're one area where I think AI is impacting trust, this, this whole area of generating content and also generating fake content is so now so easy to use a generative AI tool like Elon Musk's Grok to create videos and images of things that have never happened of even of politicians.

So if I wanted a fake. video of, of Donald Trump or Kamala Harris doing whatever I wanted them to do, we can now create these. And this is hugely dangerous. So we need to, we need to regain some of the trust around AI, I think.

Jeff Hunt:

And is some of that going to happen through governmental regulation internationally?

Bernard Marr:

That's one part of it. I, we are seeing this now that in the European Union, for example, they have just created an AI act that I think it's a very positive step in the right direction. It's pretty much risk based because you need to balance. You don't want to stifle innovation, but at the same time, you don't want to let these AIs do anything.

But so this is one element of it. Regulation will never stop. Really nefarious companies, people do really bad things. So we, we can now use ais and weapons, we can use AI in cyber attacks. And when it comes to those ais, regulation is not good enough. We also need detection and security against those.

Topic 5. Augmenting the way we work with AI (23:00)

Jeff Hunt:

And Bernard going back to the agentic AI for a second. is do you see, I'll just paint a picture and you tell me if this is something that might be accurate or we could see in the future. A CFO at a company might have an agent that's an AI agent working for him or her. That, and that agent is now capable of analyzing all sorts of integrated data within the organization and not only creating new reports and analysis that they haven't seen before and that allow the company to make better strategic decisions.

But also creating goals and almost ending up as a person that's on his team. Is that something that we might see?

Bernard Marr:

Yes, I think so. I think Slightly more nuance. I think I completely agree that we will have someone working alongside a senior decision maker and maybe multiple AIs, maybe multiple AIs combined in one that can help us with so many things. It can help us understand company data. For me, this is one of the best use cases because there are lots of executives that, um, Don't necessarily have the data analytics skills themselves.

They rely on an analytics team to pull the data together. Now I can do this all myself, even with no analytics capabilities. I can simply speak to an AI and say, Hey, what, what, you know, what our customers, where things that are, what, what haven't we spotted what our trends for the next year. And so whatever it might be, so we can now, we democratize the use of data.

And make sure that anyone now has access to this information. So we democratize it. The. When it comes to goals, I think you don't want an agentic AI to create goals for you, for your department or your company, but you might have an AI that suggests some goals, but I think when it comes to strategic decision making, this should always be The realm of CEOs and senior leaders in organizations, because I, I think so far humans have this competitive edge over AI that don't understand the full picture.

They don't understand the context. They don't understand some of the more nuanced things that a CEO might know. And I think we need to use the information that the AI can give us and then channel this through our own thinking and our own experience into goals that, that the organization should then pursue.

Jeff Hunt:

Which really comes right back to that whole concept of augmenting the way we work, not just relying on the outputs of the AI. So exactly. And so I want to pivot and talk about the more human aspects in business and how AI integrates, what are your thoughts on how leaders can integrate AI into their processes and really ensure that employees remain Um, engaged and valued and they have the human connection with each other.

Bernard Marr:

I think for me the most important thing is to have an open dialogue and have those conversations. And this is a bit like what we've been learning in change management for the last hundred years really. That don't. Put stuff onto people, don't impose things, but engage everyone throughout the organization and say, how would you like to use AI?

Are you already doing it? What I find in my own research is that there's a lot of what I call shadow AI use going on where lots of employees are using it to improve their productivity. They use these tools, but they are not the tools that have been authorized by their company to use, which then poses some real risks.

So it's really important that we have those conversations and let people give them tools, but let them decide the best ways to use these tools to help them become more productive. So I think open conversation builds trust. and giving people tools and giving them the education. This is something else that lots of organizations have not been great at in the past.

They say, okay, we now have these amazing tools, go off and use them. So we need to have a conversation about, okay, Do you need any skills? How do you write good prompts? How what can these tools do? What can't they do? Where are the limits? This is really important. So we need to offer people training and then we need to put some guardrails in place as well.

So organizations need some sort of guidelines saying, these are the rules. You can use these systems, but you can't use any public systems, for example. We can now buy APIs. We can have sandbox versions of these tools that can be safely used inside the organization. But when we use public information, there's a real risk that we share confidential information that things that and the ethical risks, lots of risks.

So it's really important to have those guardrails in place as well.

Topic 6. Leadership and learning augmented by AI (29:00)

Jeff Hunt:

And when you think about a leadership team or an executive team that is less experienced and you want to get really pragmatic for them what are the ways that they can evaluate the right technologies and determine what , is acceptable to implement in their organizations without compromising their intellectual property?

Bernard Marr:

And I think this is where partnerships come in. I think if you have an executive team that isn't really, Too much into tech and understands those. I actually believe that one of the jobs of a leader today is to become digitally savvy and, and especially understand the capabilities around AI and where the future is going.

This is where I see my job come in. My job is to help executives and leaders around the world understand those trends. And I think that if you don't have those, those skills inside the organization. Bring someone in that has. So I fulfill the role of non executive director in a number of organizations where sit on the board and I can bring in this voice.

Others bring in advisors or they partner with consulting companies that have that. have the expertise. And then I think once you have this understanding, then we need to look at this strategically because you don't want to implement AI because of some sort of fear of missing out far more. You don't want to implement it to really help you strategically drive the performance of your organization.

And. So when I work with organizations and I've worked with large organizations like Shell helping them to design that their AI strategy and what you do is you start with a business strategy and say, okay, what are the challenges we have and where are the real opportunities to use AI to help us make real progress in terms of making people's job easier, delivering a better service to our customers and then you really start from there.

And instead of experimenting with lots of different things, lots of proof of concepts, that's fine. But we have to also start from the top level strategic on the biggest priorities and figure out where AI can be really helpful. And actually doing a bit of both. So the leadership team should figure out what are your goals.

What are your strategic challenges? How can AI and how can technology as a whole help you address these? And then you also want to give people some freedom to say, okay, everyone can go off and do a bit of their own AI and figure out how they can make their everyday job better.

Jeff Hunt:

So it, it sounds like just to summarize a little bit about what you said, at least what I'm reflecting on is for the less educated executive team, the pathway would look like.

First of all, surround yourself with the best advisors you possibly can so that you can learn about this topic and how it's going to impact your business. Then secondly, make policy decisions internally so that you're crystal clear on what it is you want to implement, why you want to implement it, and how it's going to be used.

And then thirdly, go to your entire organization and create. Really an opportunity for dialogue both directions about the way people use the technology, what they've experimented with, how they feel like they can become more efficient and accurate and improve quality within their own roles. And then be sure to manage and measure and hold people accountable so that they're not stepping out of that sandbox, if you will, compromising the intellectual property of the company.

Is that a reflective summary?

Bernard Marr:

Yeah. Very, very good summary. And I think I would probably add in stuff just on the surrounding you with the best people also make it your mission to learn yourself about these. I think, I don't think anyone can be a successful leader in the, in the future if you haven't got.

a really good understanding of the digital trends that will shape our world in the future. So pick up a few books, read, listen to podcasts like this one. Look up on YouTube. I have thousands of videos on my channel about pretty much all topics that we've just covered. So there's so much information out there.

There are free courses, there are online courses people can Put this into your diary.

Jeff Hunt:

You can, for listeners that are out there, you could pretty much get a PhD in AI just by listening to Bernard's podcast. So if you have some time, you're on the road, put on some of his podcasts and I think you'll be blown away about what you can learn.

I'd like to talk just a little bit about how AI may play a role in actually improving leadership or leadership development. What do you see happening in that space? Is that in our future?

Bernard Marr:

I think it's happening right now. That I believe if, if I had to pick two areas where I believe generative AI in particular will make the biggest impact, it will be healthcare and education.

And obviously, Leadership development is a subset of education and what what we will see is this complete transformation of education over how many years from now till the future, where we have a system today where you go to a class and you learn something, or you go to an executive development seminar and you listen to someone in the future, this will be completely customized.

Based on what you really want to know, what you already know. And instead of having someone like me stand in front of a room. You have an AI that might look like me, might look completely different. Everyone can have their own version of it. That is a far better teacher than I could be. And it will teach you exactly what you need to know.

And that for me is super exciting. So I see a complete transformation where AIs can help you understand what gaps you might have in your executive skills. bag and how you can improve those and then, and then it will deliver education programs that are completely customized to you.

Jeff Hunt:

That's very exciting and really can accelerate learning for people because they can learn in a way that works for them. Right.

Bernard Marr:

Exactly. And then I mentioned the metaverse. I prefer to use the word immersive internet or a more realistic 3d. Digital environment, and if you combine this with generative AI, so you can not only learn, watch someone teach you, but you can then do it.

You can experience it. You can travel back in time. You can put yourself, if you wanted to learn about public speaking, you can put yourself in front of an audience and see what it feels like. If you want to, if you are a, a medic, a surgeon, you can then use those to perform a digital operation. You can try out operations on a digital twin of the patient that you're going to operate on in the future.

So you can fine tune your skills and then do the operation once you're sure you know how to do it and where to cut and how to get to the bone or the organ that you need to need to sort out.

Topic 7. Lightning round questions (36:49)

Jeff Hunt:

Remarkable. Remarkable. Well, and listeners, for those of you that are interested in learning a little bit more about AI and learning and development, I did a recent interview of Juliet Denny on the podcast and she owns a company that is right in the center of this L and D space relative to AI.

So there's some good learning about Edgar Dale's cone of experience on that podcast. But as we wrap up Bernard, are you ready to answer some lightning round questions?

Bernard Marr:

I would try my best.

Jeff Hunt:

The first one is, what are you most grateful for?

Bernard Marr:

I am most grateful for my family, my parents, my wife, and my children. That's the, the core of everything I have.

Jeff Hunt:

That's such a great sort of proclamation AI space that nothing will ever replace those valuable human relationships, right?

Bernard Marr:

Exactly.

Jeff Hunt:

Exactly. What's the most difficult leadership lesson you've learned over your career?

Bernard Marr:

For me, the most important lesson is to have humility and curiosity. If as a leader you have those two, you will succeed. And humility means that you don't know everything and you need to listen to others and learn and carry on learning. And curiosity is to just do it. See, and explore how the world is constantly changing and, and having this curiosity will help you learn, but it also help you understand how your customers are changing, how technology is changing.

And that makes a good leader. I think.

Jeff Hunt:

What's your top book recommendation?

Bernard Marr:

I really like, bill Gates book on climate change and the things we can do. I, if I go, if I look beyond technology, there are lots of technology books. I have written 23 books. They are good starting points. If you want to learn about generative ai, about future skills you need about future trends in business and technology.

Lots of stuff I've written, but I think, for me, one of the biggest challenges in the world is our planet, is climate change. And I love how Bill Gates breaks this down into really actionable points, actionable points saying these are the biggest challenges we have from concrete to energy generation to transportation and some real clever ideas of how we can fix it.

So that was a book that really, I read that was had a big impact on me.

Jeff Hunt:

What's the best piece of advice you've ever received?

Bernard Marr:

I think always keep learning. I think it comes back to humility and curiosity. I think that is something that my parents have instilled in me and lots of people I worked with and worked for in the past have instilled in me.

And I think that is, that is something I'd like to carry on.

Jeff Hunt:

You've given us so much great information today, Bernard. And I'm wondering if you can take a minute just to summarize what the most important takeaways are. For our listeners.

Bernard Marr:

Okay. So I believe that artificial intelligence is the most powerful technology that humans have ever had access to.

I believe it will completely transform every single business and every single job. If you don't see your business and your role as an role that is AI enabled, then You will basically be overtaken by people that and organizations that are AI enabled, but what we need to do is we need to have many more conversations.

We need to take this all very seriously. We need to approach this strategically, have those conversations, invest in education in our organizations, and. Focus on augmentation rather than replacing people and replacing functions. So you can bring the best out of people and AI, because when it comes to people and AI, I truly believe that one plus one equals much more than two.

Jeff Hunt:

All right. Well, Bernard, thank you so much for an incredible conversation. Listeners, please go avail yourself to Bernard's thought leadership on his, the future of business and technology podcast, all of the articles he's written on Forbes, all of the many books he's also written. Bernard Marr, thank you for joining me on the show today.

Bernard Marr:

Thank you so much. That was really enjoyable.

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Outro(41:37)

Closing music jingle/sound effects

Jeff Hunt:

Thanks for listening to the show this week. We release new episodes every other Tuesday. Let me know what you thought of this episode by emailing humancapitalgoalspan.com. Human capital is produced by GoalSpan. Subscribe, wherever you get your podcasts. And please share this podcast with your colleagues, team, or friends. Thanks for being human kind.