The 6 Technologies That Will Define the Future with AI Futurist Steve Brown

If you're not ready for the speed of change — you're already behind. Today on Digital Disruption, we’re joined by Steve Brown, a leading voice in the field of artificial intelligence and a former executive at Google DeepMind and Intel. Steve has delivered hundreds of engaging keynotes and AI innovation workshops across five continents. With over 25 years of experience in AI and emerging technologies, Steve helps organizations build winning strategies that drive innovation, boost productivity, and fuel growth. He has advised leading brands including Nike, JP Morgan, Samsung, Comcast, Audi, Bank of America, PepsiCo, and Disney. Steve is the co-founder of The Provenance Chain Network, a BCG Luminary, and an advisor to multiple AI startups. He has been featured on CNN, BBC, Bloomberg, Forbes, and The Wall Street Journal. His book, The Innovation Ultimatum, explores how six strategic technologies will reshape every business in the 2020s. He holds bachelor's and master's degrees in Micro-Electronic Systems Engineering from Manchester University and lives in Portland, Oregon. Steve sits down with Geoff Nielson to explore how AI, robotics, and automation are reshaping business, education, and the future of work. Steve reflects on the six emerging technologies he forecasted in The Innovation Ultimatum, where he got it right, and what surprised him — from the power of process orchestration and the quiet rise of blockchain, to the next potential “ChatGPT moment.” Steve also shares a preview of his upcoming book, The AI Ultimatum, and what business leaders need to know now to stay relevant and human in an AI-powered economy. In this episode: 0:00 Intro 0:42 Revisiting 2019's predictions 2:04 The Rise of process orchestration 3:11 Process orchestration 5:12 AI and sales enablement 6:33 Blockchain’s future 11:14 The mixed reality opportunity 13:49 What’s the next “ChatGPT moment”? 15:12 Robotics, Quantum & what's next 18:40 The real AI transformation opportunity 20:10 Top 3 areas where AI is impacting businesses 21:37 AI-enabled employee experiences 22:54 From lockdown to enablement 24:36 Getting started with AI transformation 28:01 Unexpected use cases 31:29 The education disruption is coming 36:20 Learn to get the most out of AI 37:48 How to become robot-proof 40:39 What gives life meaning 43:20 Creativity in the age of AI 45:42 The rise of one-person enterprise 49:19 Do we need AGI 50:50 Hype vs. reality 52:10 The AI Ultimatum 53:36 Speed of change Connect with Steve: Website: https://www.stevebrown.ai/about LinkedIn: https://www.linkedin.com/in/futuresteve/ Visit our website: https://www.infotech.com/Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:02Geoff Nielson?

  Hey everyone, this is Jeff Nielsen with Digital Disruption. Joining me today is Steve Brown, AI futurist, who's actually worked with Google DeepMind and Intel in the role of futurist. Steve, thanks for joining me here today.

• 0:14Speaker 01

  Yeah, pleasure to be here. Nice to meet you.

• 0:16Geoff Nielson?

  Likewise. So you literally wrote the book on emerging technologies a handful of years ago. The Innovation Ultimatum, it was called. And you covered, awesome, there it is. And you covered six emerging technologies at the time. I think it was 2019, which in hindsight is kind of a fun time to be making prognostications on technological change. And I'm curious, just kind of revisiting that now. Do you have kind of an updated viewpoint on those technologies? Which ones took off, exceeded your expectations, maybe have been slower to adopt? Where are they now?

• 0:58Speaker 01

  Yeah, I wrote the book in 2019. It dropped February 2020, right before we went into lockdown.

• 1:04Geoff Nielson?

  Oh my gosh.

• 1:04Speaker 01

  Really amazing timing for a book. Yeah, so the things that came out of that book. I mean, AI was the largest chapter in the book. I'm glad about that because it turned out, yeah, that was probably the most important thing to be talking about. Blockchain, you know, I wrote the book with a 10-year time horizon. So it was designed to be, what's going to happen in the 2020s? And we're halfway through. So yeah, I think blockchain is doing what I expected, which is it has some applications in supply chain. But beyond that, I mean, yes, crypto is going crazy, but it's just, is it creating business value? No, not yet, which is kind of what I called.

• 1:48Speaker 01

  The things that I thought would go a bit faster than they have, autonomous vehicles. Turns out that's a much naughtier problem than any of us expected. And robot taxis aren't among us quite yet. But it's looking like that will be on track. The thing that... That I leaned into, that I'm glad I did, and that has turned out to be the most prescient, was this notion of process orchestration. Thinking about the, looking at the major business processes inside a company, breaking them down into tasks and then figuring out which task is best done by a human, which is best done by an AI, which is best done by a robot, which is best done by an AI and a human working very closely together.

• 2:32Speaker 01

  I've had some version of a slide that shows that in my presentations for, I don't know, six or seven years now. And now that's, that's the core of what I think every IT person, every line of business person is having to think about. How do you re-engineer your business, given the capabilities of AI now and where it's going to be in the very near future?

• 2:50Geoff Nielson?

  So let's talk about that one for a minute, Steve, because, you know, I agree with you. I've heard a lot about process orchestration and it completely makes sense to me. I'm curious though, you know, from an adoption standpoint, are you seeing people doing it? Where, where are most organizations on the curve? Are, you know, 80% there or 20% there? And, you know, where do we go next?

• 3:11Speaker 01

  I think it's very early days still. You know, I, I work with clients in a wide range of industries and they're all panicked because they're behind.

• 3:18Geoff Nielson?

  Yeah.

• 3:18Speaker 01

  They all think they're behind and no one's really that behind. I think people are starting to have to confront all the, some of the fundamental stuff that they didn't quite have right in their organizations in the first place before they can move forward. So where's my data? Is it well organized? Is it clean? Most, for most companies, the answer is no, it's not. It's not quite ready yet. So most companies I work with are in that position, but they are starting to map out their business processes and starting to do experiments. So they're doing, you know, proof of concept, particularly in, I mean, the two main areas are sales and customer support. So partnering a human with an agent that helps them to seem smarter on the phone

• 4:02Speaker 01

  about your products or services you're trying to sell, helps them be better informed about the person they're about to call and what's been happening in their company in the last six months and guides them on maybe what are the right products and services to sell. And just automating away the stuff that salespeople hate, like filling in CRM forms and having to do those follow-up emails. Most of that is now automated by some of these platforms. So those are the areas that I think people are working on first because they're easiest to do, right? You just build a rag database and pull in your ticket information or you pull in your product information and off you go. Beyond that, it gets a little bit harder.

• 4:41Geoff Nielson?

  Well, and then sales can be a particularly sexy place to start because there's this belief that, well, if we start with sales, like cha-ching, the money's going to follow here, it's going to drive revenue. But you talked more about efficiency when we talk about sales. Are organizations, are you finding actually able to use this technology to improve sales, increase revenues, or is it more of an internal efficiency play at this point?

• 5:09Speaker 01

  I haven't seen any numbers that show me that you're actually increasing revenue per person. But I suspect that that is what is happening.

• 5:22Geoff Nielson?

  Right.

• 5:22Speaker 01

  Because you're just increasing the efficiency of that person, they probably can make more calls per day. If the AI is helping them, so a lot of these AIs just listening to a call and then they surface information on the screen for the salesperson to say, hey, there's an objection here, why don't you pivot your strategy and try selling these? I have to imagine that that is going to give some sort of uplift on the sales process, but I haven't seen numbers yet.

• 5:48Geoff Nielson?

  Right, right. So yeah, I guess if you if you kind of untangle that, it can it can juice the individual, you know, pieces of the sales equation and you would you would hope that that would, you know, lead to better sales on the other side.

• 6:00Speaker 01

  Yeah, if you can make more call, more calls in a day, just kick my light there. If you make more calls in a day and you're able to close those calls more effectively, you should be closing more business.

• 6:12Geoff Nielson?

  Yeah, yeah. You mentioned you mentioned blockchain as an area that, you know, it sounds like it's just kind of quietly doing its thing in the background now. It's got its applications, but it's something that, you know, maybe doesn't make the same news cycles as it used to, you know, exempting all the conversation happening now about, you know, the price of crypto. Have we reached, you know, peak blockchain? Is it no longer, you know, an emerging technology? Or do you see more kind of adoption and innovation around the corner there?

• 6:44Speaker 01

  You know, there's still there's still potential in the supply chain, a lot of potential. One of the biggest things that people, whether you're a brand manager, a regulator, a consumer, you want to know where things came from and how they were made. That's I'm co-founder of a startup, so small plug for the providence chain network. Trying to figure out how to move from a system of claims where I'm selling you something and I claim that it has these features and this provenance. You know, it was a T-shirt that's not sewn by tiny fingers in a Vietnamese factory. It is palm oil that didn't come from a dodgy place. It is leather from hides that were not from cattle where land was cleared in the rainforest. Right?

• 7:30Speaker 01

  You want to be able to move from a system of claims to a system of evidence. And I think blockchain is really good at helping to do that by locking in this evidence. So you can be more confident when you're buying products where they came from. I think that's the biggest and most powerful application. The other one is. Distributed systems, being able to create value in a distributed way. And you're seeing that start to happen with AI, with people being able to run distributed models, basically renting someone else's computer to run models and do training runs. That's an interesting collision between AI and blockchain I'm watching.

• 8:07Geoff Nielson?

  Yeah, yeah, it's really interesting to me, the supply chain piece, Stephen, the claims piece, and it's, you know, it's so, I don't know, for me, it's just intellectually interesting that like literally any object are consumable in this modern world, you know, I can point at this microphone and it's like, where did any individual piece of this come from? Like, I have no idea, right? Like, I don't know what it's made from, I don't know how it was sourced or what that supply chain looks like. And, you know, the idea that you can have this, you know, this record with evidence of where it came from is, you know, kind of transformative, but I don't know, is this really on top of minds for a lot of organizations or a lot of consumers? Like, how do you, how do you cross that hurdle?

• 8:50Geoff Nielson?

  And what does adoption look like to start putting something like this in practice?

• 8:53Speaker 01

  It depends on the organization. If you are the US Space Force.

• 8:57Geoff Nielson?

  Yeah.

• 8:57Speaker 01

  And you're putting a hundred million dollar spy satellite into space.

• 9:01Geoff Nielson?

  Right.

• 9:01Speaker 01

  You need to know that not a single component came from China.

• 9:05Geoff Nielson?

  Yeah.

• 9:06Speaker 01

  And you have a room full of people running that information down, use a product like the Provenance Chain Network, and suddenly, you know, you can do that automatically. So if you're a brand manager, and you've had maybe a few incidents that have not reflected well in your brand, and they're in the press, you're going to be more interested. Or you're just a good brand manager.

• 9:27Geoff Nielson?

  Right.

• 9:28Speaker 01

  Who worries that you, you're going to be the next person in the press. So those are the sorts of companies that are leaning into this stuff earlier. I think consumers are a little bit further behind. There are plenty of conscious consumers, but there are not enough of them yet, and they're not demanding this stuff enough yet, that it's happening, it's being deployed more broadly. I think what may happen is you'll see, you know, the next generation of food safety.

• 9:52Geoff Nielson?

  Yeah.

• 9:53Speaker 01

  Requirements, and they may cause at least the food industry to move in that direction. So they know, you know, when there's some contamination in lettuce, as there seems to be on a, on a regular basis, they don't have to take every remaining lettuce off the shelf everywhere in the country. They can trace exactly where it came from and not have to throw all that lettuce away.

• 10:14Geoff Nielson?

  Right, so I mean, whether it's lettuce or spy satellites and I don't think I've ever put those two in the same sentence before. You know, it sounds like regulatory bodies may be kind of a key ingredient in this. Do you buy that? Or is this still gonna, you know, kind of proliferate without it being a compliance requirement?

• 10:33Speaker 01

  Compliance is part of the thing, but I think it's if you care about your brand, you're going to want to have eyes on your supply chain. I mean, a lot of brands have supply chains that are quite deep. They can go back three, four, five, six steps. And you can tell your immediate suppliers to behave.

• 10:50Geoff Nielson?

  Yeah.

• 10:50Speaker 01

  But, you know, economic pressures mean that people are always looking to save a buck here and there. And so two or three steps down the supply chain, you need some incentive mechanism built into your supply chain so that you can incentivize or penalize people if they don't comply with what you're requiring.

• 11:06Geoff Nielson?

  Right, right. So I mean, it sounds like overall, you're still pretty bullish on this whole use case for blockchain.

• 11:12Speaker 01

  Yeah, very much so.

• 11:14Geoff Nielson?

  Yeah, oh, it's interesting. I want to, you know, I was thinking about just your list of technologies and one of the ones we haven't really talked about yet is, you know, VR and AR and just kind of this notion more broadly about spatial computing. And, you know, as recently as like a year ago, it seemed like this was kind of on the tip of everybody's tongues. And I don't know if it was, you know, Mark Zuckerberg, you know, not having anything new to show, or, you know, Apple having their, you know, their rollout. But it feels like it's fallen off a little bit. Is this just that point in the cycle? Is it going to come roaring back? You know, what's next in this space?

• 11:53Speaker 01

  Yeah, I think with VR particularly, you know, the use cases are relatively limited.

• 11:57Geoff Nielson?

  Yeah.

• 11:58Speaker 01

  Because when you put on a VR helmet, you're cutting yourself off from the physical world. So in an enterprise situation, you need your workers to go to see what they're doing. So that's why augmented reality, mixed reality was always going to be more interesting than virtual reality. Virtual reality is fine for simulations and training, for games, for, you know, it has so many applications. But it's not until you have high quality, low cost, lightweight, long battery life, mixed reality, particularly mixed reality that is paired with an AI assistant that's just spatially aware, then it gets to be the kind of use cases that everybody will want. But the technology is just taking a little longer to develop.

• 12:39Geoff Nielson?

  So you still see it as, you know, if I say, if we talk about the 2020s, you know, the next five years, you're still predicting, you know, pretty interesting advances in that space. Once AI can kind of unlock that, is that, is that fair?

• 12:52Speaker 01

  Yeah, I mean, you look at what Microsoft is doing with the dynamic 365 platform and comparing that with HoloLens 2.

• 12:58Geoff Nielson?

  Yeah.

• 12:59Speaker 01

  You know, putting on a pair of magic glasses that then shows you how to fix something or how to, you know, build something in the moment, just cuts down training times, makes it easier for somebody to get up and do something. And ultimately, I know, I'd love something like that to help me build IKEA furniture or, or fix my washing machine, right? YouTube videos only go so far.

• 13:20Geoff Nielson?

  Yeah.

• 13:21Speaker 01

  To be able to just put on a pair of glasses and have an AI converse with me and talk me through what I need to do is a very powerful use case.

• 13:30Geoff Nielson?

  Yeah, and I'm, you know, there's, there's so many, just in this constellation of kind of technologies. And, you know, I use the word constellation deliberately because they all, as you said, they interact with each other, right?

• 13:40Speaker 01

  Yeah.

• 13:41Geoff Nielson?

  You know, this is maybe an unfair question in its specificity, but, you know, obviously, a couple of years ago, we had that watershed moment with ChatGPT. Do you have any predictions, Steve, for like, where are we going to see the next one? And is there another, you know, emerging technology watershed moment coming within the next two or three years?

• 14:00Speaker 01

  Yeah, don't worry, I get asked that question all the time. What, what's the next ChatGPT moment?

• 14:04Geoff Nielson?

  Yeah.

• 14:04Speaker 01

  I think there's a few that we can imagine. I mean, the first time there's an assistant that you can give quite a complex task to, and it goes away and does it for you.

• 14:15Geoff Nielson?

  Right.

• 14:15Speaker 01

  Which I think is coming next year. And that, that's a pretty big one. The first time you see a robot walking down the street, I think it's going to be a big moment.

• 14:26Geoff Nielson?

  Yeah.

• 14:27Speaker 01

  And then, you know, within a year, like, ah, whatever. You know, it's just getting, getting groceries for Lynn down the street, you know. So I think it's going to be, there are going to be moments like that, which surprise us all. And then they're just going to become normal.

• 14:40Geoff Nielson?

  Yeah. So robotics, I mean, the the robots walking down the street, and I think I saw like actually in LA or something there. It seems like that like that is starting already. And I'm curious because robotics is not, you know, in a in innovation ultimatum. Robotics was not one of the big technologies. And so I'm curious, you know, halfway through, you know, the 2020s or the 10 year time horizon. Are there any technologies that you're starting to look at now that didn't make the cut five years ago?

• 15:12Speaker 01

  Yeah, robotics is in there as autonomous machines. But yeah, I don't, I didn't see the speed of development of the humanoid robots. I've been very impressed with companies like Figure, Sanctuary up in Vancouver, BC. Agility Robotics down in Oregon doing good work and Boston Dynamics are pretty good. So I think we're going to see big leaps forward there. And it's the combination of these robots and, you know, advances in motors and batteries. But combining that with developments in large language models and vision systems that's really provided these breakthroughs. What do I see coming next?

• 15:55Speaker 01

  I deliberately didn't write about quantum as one of the six technologies because I was writing about a broad application in the 2020s. I think quantum is still a 2030s technology, but that's the one I'm starting to watch closely. Are there, is there an intersection between quantum and the future of AI?

• 16:16Speaker 01

  We cannot scale up AI in the way that we're scaling it now indefinitely. You know, it's just, you're going to hit a wall. We're starting to get there in terms of the amount of power it consumes, the water these things take. You know, it's not environmentally sustainable. So we're going to need something different. And, you know, there could be some analog AI stuff, quantum AI, those are the ones I'm watching closely.

• 16:41Geoff Nielson?

  So with that, with that application of quantum, you know, it's, you know, I talk to people about quantum, I hear about it. But most of the conversations are still fairly academic in that space, it seems around quantum. Are you starting to see any more kind of applied use cases of quantum, even, you know, kind of conceptually that are emerging?

• 17:01Speaker 01

  I mean, again, this is why I didn't write about it in my book because it's out there still.

• 17:06Geoff Nielson?

  Right.

• 17:06Speaker 01

  Though it's interesting in sort of molecular chemistry research, looking at the interactions of complex organic molecules, making, doing bleeding edge scientific research, it's a great tool in some specific areas.

• 17:23Geoff Nielson?

  Yeah.

• 17:24Speaker 01

  But are you going to have quantum in your next smartphone? No. So I think there's some interesting areas where you might be able to do AI in a different way.

• 17:38Geoff Nielson?

  Right.

• 17:38Speaker 01

  The brute force, matrix multiplication, transformer model, transformer based model approach that we're using for large language models today uses enormous amounts of compute. Are there other ways to do it? And there are some interesting companies out there who are looking at different approaches and they're using quantum techniques at their foundation. Are they using quantum computers? No, but they're using quantum properties.

• 18:08Geoff Nielson?

  So that, you know, you mentioned compute and, you know, certainly I don't think it's controversial to say there's a bit of an AI kind of arms race going on right now, especially with kind of the big tech organizations, you know, using as much compute as possible to, you know, get this next big thing. And, you know, we were talking earlier, Steve, about the fact that like, everybody's behind an adoption right now. And so, so I'm curious, like, in your mind, how big is the next big thing? Or, you know, do we still have our work cut out for us with the existing technology?

• 18:40Speaker 01

  That's a very good question. I mean, there's so much opportunity with adopting AI across the enterprise, but doing it right and doing it at the right speed.

• 18:53Geoff Nielson?

  Yeah.

• 18:53Speaker 01

  And figuring out the right use cases to go after is the challenge. Right? And, and what's the foundation you have to put in place? Yes, there are existing technologies that will still be able to get some things out of.

• 19:07Speaker 01

  I'm not, you know, there's still value in whatever the next rev of the SaaS software is you use, you know, there's even new features. But I think the transformation stuff, transforming the workforce, elevating the performance of your workers, and notice I say performance and not productivity. You know, it's productivity is a big one, but elevating the creativity of your workforce, the intuition of your workforce, the decision-making abilities of your workforce. Figuring out how to do that with AI, that is where the real opportunity lies. So maybe, you know, completely differentiate versus your competitors. So I think that's where, at least the enterprises I'm working with, that's where they're focusing most of their energy.

• 19:50Speaker 01

  There's some sustaining work and yes, we need to keep doing the stuff we used to do. But figuring out where to lean in.

• 19:57Geoff Nielson?

  Yeah.

• 19:58Speaker 01

  And where to focus, um, where am I going to run my experiments? What are my pilots going to be? Where are the areas of most opportunity? And that's something I help a lot of clients with.

• 20:09Geoff Nielson?

  Yeah. And, and you know, on that, who, who do you see and what do you see as being the biggest indicators, I guess, of, you know, an organization that's going to be a disruptor versus one that's going to be disrupted?

• 20:26Speaker 01

  I mean, there's three main areas that people are using AI in their businesses. First one is customer experience, second is employee experience, third is operational excellence, right? How do you elevate your offering, whether it's a product, a service, do the user interface to an existing product? How do you elevate your offering to improve customer satisfaction, improve utility and differentiate the marketplace? That's a fairly obvious path. The one that I think people are not spending enough time focusing on is how do I elevate my workforce? So that's the process orchestration stuff we talked about. And you're trying to boost performance, but there's another reason to do that, too.

• 21:08Speaker 01

  We are moving into a period of time when we're going to have not enough people in the labor force. And that is a demographic certainty. The only way you fill that gap is with automation or immigration.

• 21:22Geoff Nielson?

  Yeah.

• 21:23Speaker 01

  And immigration's probably not on the table for at least the next four years.

• 21:26Geoff Nielson?

  Yeah.

• 21:27Speaker 01

  Or not, not in the ways it was perhaps in the past. So automation is going to be a significant part of making sure that we can fill the jobs that people have. So.

• 21:39Speaker 01

  When you are competing for that scarce labor, think about, you know, when you're thinking about what's your next job going to be? Do you want to work for a company that has invested in AI tools, services, assistants, so that when you go into work every day, the things that you don't enjoy doing are all offloaded to an AI? And the things that you do enjoy doing, that you get satisfaction from, you have support to elevate your performance. So you're going to go work for that company? Are you going to go work for the company that's not invested in creating that amazing AI-supported employee experience? So just for access to the best talent, I think companies need to think about that very carefully.

• 22:20Geoff Nielson?

  Right, and, and, I, I, you know, just reflecting on that, there, there's what's in the hands of the organization versus what's in the hands of the employee as well, who's trying to use AI. So for, for you, Steve, is like a, a, a total lockdown of AI in your mind, like off the table for organizations? And, you know, in some cases, I guess, where there's, you know, regulatory reasons to do that, is that creating just an environment where these organizations are making themselves, you know, kind of, you know, prey to be leapfrogged by, you know, someone who's going to take that chance?

• 22:54Speaker 01

  Absolutely, and there are good reasons why people don't want an employee just randomly using ChatGPT. Because when you do that, you know, everything you type in is going to the training data set for the next round of models. And it's not good if you cut and paste confidential information and send it to the AI to train on it. So, yeah, there are good reasons to do that lockdown, and that was a, that was a fair initial response. But that was a fair response two years ago. It is not a fair response now. There are plenty of options to be able to give, to expose employees safely to these types of tools without compromising confidentiality.

• 23:36Speaker 01

  You know, there are, there are ways to interact with, with Google, with OpenAI even on an enterprise plan so that you, you can keep your data safe. And to use RAG and other techniques so that you can. The average knowledge worker spends thirty two days of the year just looking for the information they need to do their jobs. So taking all of the corporate information and safely surfacing it, making it available through a vector database to your employees is going to save a lot of time and help them be more effective. That's an easy thing to do. And companies should all be looking at that.

• 24:12Geoff Nielson?

  Yeah. And, you know, speaking of easy things to do, I mean, there's, there's, you know, clearly a spectrum here from, you know, the low hanging fruit and some of the like, oh, this is easy to adopt right now to, you know, I have to imagine that this, this conversation around like, you know, process orchestration. I mean, this is transformative, but I don't think we'd use the word easy for that one if I had to guess, right? Like that's, that's like fundamentally re-architecting, you know, the organization. And so, you know, I'm curious, I know you've been doing some AI workshops with various enterprises. What does that look like? How do you recommend they get started? And what kind of journey do you take them on?

• 24:53Speaker 01

  Yeah, so I get hired by lots of companies to help them figure out what's their AI transformation journey. And it usually starts with me going in and talking to their board or management suite. Give them a briefing on AI, help them understand what are the opportunities that lay ahead? What are the challenges they should know? How do they avoid the pitfalls? Then they bring me back, usually to torch the lex level down. I give them the same kind of spiel. And then they bring me in to do the hard work, which is an AI innovation workshop. I come on site for a couple of days and I use the future casting process to help them ideate future use cases for the organization. So they bring people into a room, we get about forty, fifty people together, working small teams and ideate potential use cases for the future.

• 25:36Speaker 01

  And then we map them out in time and figure out which are the ones that are priority. And what are the? By looking at all of these potential use cases, what are the things that we need to do to get there? Do you have the talent that you need? Do you have the data that you need? Do you need to acquire that data? Is that through a partnership? Is it through M and A?

• 26:00Speaker 01

  Is it something that you have, but you have to clean up? What's the IP that you need to generate? What are the infrastructure requirements? Is it a make versus buy conversation? So I walk them through all of that so that they can start on that journey. And even though you are making like you're building a five year roadmap or a three year roadmap, you know what you're going to do when you go into the office on Monday. How do you start on that journey? So that's probably the most popular workshop I run right now.

• 26:27Geoff Nielson?

  Right. And you mentioned, you mentioned there make versus buy. And I have, I have a suspicion, I know what you're going to say, but you know, what, what percentage of the time are you recommend recommending make versus buy? And you know, what are the, what are the cases you see, if any, for make?

• 26:43Speaker 01

  It depends what kind of problems you're trying to solve. You know, if you are wanting to use a generative AI to accelerate your sales team, yeah, I'm probably going to recommend that you, you buy that in because building your own large language model from scratch, not something I recommend for people.

• 27:02Geoff Nielson?

  Yeah.

• 27:03Speaker 01

  Right? That costs a lot of money and you're not going to be competitive with what you can rent in essentially. If you are building a model in an oil company to help you figure out optimal gas uplift. So you're, you're forcing gas into the ground to get oil to come out. You know, that's something you're going to do yourself because it's going to give you competitive advantage. And that's a model that you are going to be able to, to create in-house. So it really depends on what is it you're trying to solve? What's the problem you're trying to solve with AI? And what's available out there? And what is something gives you a sustained advantage versus it's just something that you need as a base capability for the enterprise?

• 27:44Geoff Nielson?

  So, you know, on that note, do you have any war stories? Maybe you can share about, you know, really good, you know, AI use cases or ways you've seen organizations take advantage of this technology? That's, you know, kind of caught your attention. It's like, wow, I never thought of that.

• 28:01Speaker 01

  Um. It's amazing where it shows up, you know, like one of my clients is a uranium mining company up in Canada. Um. When you're mining uranium, you have a spinning head. And the rate of spin and the pressure of the water coming out, you vary it over time to get the uranium ore to come out. I'm not an expert on uranium mining, as you can tell. But the speed of spin and the pressure changes, you optimize that process with AI. And you increase the yield by, get ready, one percent. And you think, well, is that worth having? Turns out, yeah, because that's worth tens of millions of dollars a year.

• 28:44Geoff Nielson?

  Huh. Interesting.

• 28:46Speaker 01

  So it's looking for that. What are the areas where you can get biggest return? Even if it's a one percent bump by using AI, it's worth doing in some cases.

• 28:55Geoff Nielson?

  Yeah. Yeah, no, it's funny and it's just the one percent, I guess, got my attention because it's just taken in isolation. It's like such a who cares number. But right, you apply it to any big enough, you know, big enough sample and suddenly you start to you start to have a real impact.

• 29:14Speaker 01

  Yes, if you're operating at scale.

• 29:16Geoff Nielson?

  Yeah.

• 29:16Speaker 01

  And you can go after 10 or 15 one percents. That's going to be transformative to your business results.

• 29:22Geoff Nielson?

  Yeah. Yeah. Um. Are you working with many organizations, Steve, on that kind of, um, you know, the process orchestration? Or do you find that's like fair, that's reserved for the most advanced organizations right now?

• 29:37Speaker 01

  I'm not. So my role as a futurist is to go in, help them understand the possibilities.

• 29:42Geoff Nielson?

  Got it.

• 29:42Speaker 01

  Build that roadmap and then I step out of the way. So I then hand off to other organizations that are going to help them actually get into execution. But they're partners, I mean, companies like Salonis, who's a client of mine, actually, um, great to work with, by the way. They are a company that helps you do that mapping, that map out your business processes, which is the first step to then figuring out which of these tasks am I actually going to automate.

• 30:06Geoff Nielson?

  Right. And and you know, just thinking about the organizations I assume you're working with are you know, not not super different from the organizations I'm working with, which is to say, it's probably not the startups that, you know, were founded in 2024. And it's probably not, you know, for the most part, the Amazons of the world. It's, you know, that that kind of, you know, middle of the economy, you know, bread and butter organizations. And I'm curious, you know, from your perspective, like, how big is the risk right now for these organizations? That they're either going to, you know, get displaced by, you know, founded in 2024 organizations, or that, you know, their business model or something that they're doing is going to get

• 30:49Geoff Nielson?

  absorbed by, you know, the magnificent seven?

• 30:54Speaker 01

  That's a great question. I mean, most of my clients are, you know, medium sized enterprises or big enterprises. So my clients recently have included Bank of America. I work with Disney, Nike, JP Morgan, lots, lots of big companies. But you're right. The question writ large is, what's the risk of disruption from upstarts? When you have a powerful technology, if you, if someone else is able to harness it better than you, because you have the innovator's dilemma, or you have organizational torpor, you just not know if it's moving fast enough, what's the risk? I think the biggest risk is going to be in education. You know, I talked to people

• 31:36Speaker 01

  in higher ed, and they're either la, la, la, la, la, are not, you know, not, not listening.

• 31:44Speaker 01

  You know, the more you've got, you've got teachers who are more worried about their kids cheating using chat GPT than they are thinking about, well, how do I prepare my kids to thrive in a world of, you know, mass automation? What's, how do I give them a differentiated advantage to survive in that world? And how do I use AI and embrace it to amplify my ability to teach them? You know, that's what people need to think. And the risk is, to your point, you know, okay, I'm Harvard University, I'm XYZ University.

• 32:21Speaker 01

  What happens when Microsoft Academy or Google University comes along and offers a really great accreditation and the turning point is when businesses in corporate America say, you know what, a degree or whatever the rating is from Microsoft Academy is worth more or equal to something from a Brixton Moore University. Suddenly then they have a real problem. It's hard to charge two or $300,000 for education if I can get the same one from Microsoft for two or $3,000.

• 32:54Geoff Nielson?

  I love that you went there and, you know, I do a lot of work with higher ed and it's,

• 33:01Geoff Nielson?

  it really feels like they're kind of at that pivotal moment right now. They're facing this, you know, enrollment cliff due to demographics, due to, as you said, immigration. The model itself is changing. Like, I don't know, it seems to me like we're in this weird kind of liminal space where everyone agrees that the old model isn't really suited to the present, but we haven't found anything yet that's clearly, you know, the answer. So I don't know if you are, and, you know, to me Harvard is probably in a better spot than a lot of the, you know, next tier or two rungs down from Harvard.

• 33:38Speaker 01

  Imagine a global brand.

• 33:39Geoff Nielson?

  Yeah, yeah, because they've got the brand. But, you know, is this, how do you avoid watching from the sidelines? I mean, do these organizations have an opportunity to disrupt themselves, to partner with the Microsoft academies of the world? You know, where do we go from here? You know, to make sure that we're not just kind of, you know, in the dustbin of history?

• 34:01Speaker 01

  Yeah, yeah. So I think there is a huge partnership opportunity because the benefit of going to university is not just information transfer from, you know, faculty brains to my brain, right? It is, that's a big part of it. I'm learning some of the knowledge and skills that I need to thrive in the workplace in the future. But it's also about learning to be a well-adjusted human to interact with other people. There's a huge networking component, right? I still am in touch with people I was at university with and sometimes we help each other out.

• 34:35Geoff Nielson?

  Yeah.

• 34:36Speaker 01

  Right, certainly if you went, if you went to Harvard, it's amazing network there. That's a big part of why you go to Harvard. It's not just a brand and the cachet. So I, I think the opportunity is how do you have this blended model? And it comes back again to process orchestration. Right? What, what are the things that I can deliver best with an AI? An AI tutor that adapts to my style, that is very good at teaching me anything I want to learn? And pair that with the human connection of a tutor, um, being on a, on campus with people who are like me and we're learning, we're talking about the ideas that we are, um, we're being exposed to. Uh, and building that network for the future. How do you combine those two?

• 35:20Speaker 01

  So maybe I can do a degree in a year, uh, instead of three and get the same high quality education, the same networking and pop out the other side and, and at a fraction of the cost.

• 35:30Geoff Nielson?

  Right. And you've got, you, you've got the gears turning for me right now, Steve, because, you know, I see a few things coming together. And, and one of them is, you know, I, I'm a, I've got a business background, but I, I'm a self-proclaimed apologist for like a liberal arts education. Um, and I, you know, I've, I've always believed that one of the main benefits to, to schooling is like, it teaches you how to think, if that makes sense, right? Like, it's not necessarily about the answers you learn there. It's about asking the right questions. And the gears you got turning in my brain are like, to me, in the age of AI, that's actually more important than ever. Right? Like that, the answers, like, you know, it happened when we had calculators, like you don't need to remember how to do long division.

• 36:14Geoff Nielson?

  Um, and, and something similar may be happening in AI. So.

• 36:20Geoff Nielson?

  I don't know, where does that kind of take us? And does that become a skill that's that's more needed in the workforce? Is that something you're seeing?

• 36:27Speaker 01

  Yeah, yeah, I mean, there was an article, I think it was in the Atlantic, about a year, a year and a half ago, which the headline was the most in learning to talk to an AI could be the most important skill of the 21st century. They are going to be the tools that we use to help us do all the things that we do in our personal lives, our private life, work lives, learning, constantly growing. AI is going to be a partner for doing that. And the same way we all had to learn, if you're old enough, WordPerfect and Lotus 123. If you're younger than that, then you know, Word and Excel or the Google Suite. You had to learn how to get the most out of those tools. We have to learn to get the most out of our AIs.

• 37:12Speaker 01

  And that is going to happen through a process of trial and error and being taught. And yeah, I think we're going to need to teach kids how to get the most out of their AIs. But at the same time, people always ask me, the number one question I get, probably number two is the one you asked me about. What's the next chat GPT moment? The number one question is some version of what do I need to do to become robot proof? Or what do my kids need to do? What do my grandchildren need to do? What should they do in school to make sure that they're robot proof in the future? That they're going to be relevant in the workplace? And I tell them the same answer every time. Double down on your humanity.

• 37:55Speaker 01

  The things that make you uniquely human, your empathy, your communication skills, your intuition, your creativity, AIs can do some creative things, but humans are better for a while. So figure out what are the things that make you uniquely human? Lean into those because the future is still human. It's just supported by amazing AI.

• 38:19Geoff Nielson?

  So thinking about like, I love the optimism that comes with that. And I was gonna ask you on balance, like, what is your excitement versus fear? You know, looking out at the next 10 years and, you know, maybe more than anything, you know, what it means for, you know, children and grandchildren and, you know, the future of somewhere between humans and the human workforce, I guess.

• 38:44Speaker 01

  Yeah, I mean, we're getting into huge question space now.

• 38:49Geoff Nielson?

  Guilty.

• 38:50Speaker 01

  You know, if you ask the question, you know, should I be excited or afraid of AI? The answer is yes, you know, it's both. We need to be cautious about it. It is a very powerful technology. It is an amplifier. So it amplifies good behavior and bad behavior. So we could live in a world of, you know, huge misinformation and disinformation created and pumped out from AI factories at scale. At the same time, there's a good chance that somebody listening to this podcast will have their life saved by an AI. A drug that was developed or co-developed by an AI is going to save someone's life. If not you, then your kids.

• 39:34Speaker 01

  So, you know, it's good and bad. My biggest worry, you know, I'm a future boy, right? So when I play things out, I don't know how long it will take, but AI is probably going to get good enough that it can do most jobs. Most economic activity will be done by machines freeing us up to do something else. And I'm not sure that we all know what to do with ourselves. And let's say we can fix the economic side of things and make sure that people have what they need to live. You know, if we live in a world of abundance fueled by AI, because the cost of labor is, cost of goods mostly is about labor. So if you crash the cost of labor, then the cost of goods comes down.

• 40:18Speaker 01

  You live in a world of abundance, everybody can afford what they need. So you figure out some sort of economic distribution model, then what? What are we going to do with ourselves? And so I I think we all have to start asking and answering questions to prepare ourselves for whenever that comes. And, you know, maybe it's a generation from now, maybe it's two generations from now, maybe it's never, maybe it's 15 years, I don't know. But when it comes, we have to know, who are we? What's important to us and what makes us happy? And it's never too late, never too early to start thinking about the answers to those questions now. We all found out during

• 40:59Speaker 01

  Covid, when, you know, the universe sent us back to our bedrooms to think about what we'd done for a few months.

• 41:06Geoff Nielson?

  Yeah.

• 41:06Speaker 01

  Yeah, people turned to alcohol and drugs and they were miserable. When that happens and you're told you don't need to work for the rest of your life, what are you gonna do?

• 41:16Geoff Nielson?

  Yeah.

• 41:18Speaker 01

  That's my biggest worry, is we won't make that transition elegantly.

• 41:21Geoff Nielson?

  Well, and that's, there's, there's, there's something implicit there too, Steve, which is, to what degree we answer that question ourselves versus someone answers that for us, right? And, and in some ways, maybe that was the scariest part of, of the pandemic is that there was no one there to answer that for us, right? Because we didn't know. And it feels to me like we're just at this kind of historical inflection point where there's just more unknown unknowns than ever, you know, and, and the, the number of people who can tell us what's next seems to be dwindling, you know, you, you and I, you know, try our best, but it's just, I don't know, I feel like we're still in, in kind of watch and see mode as we kind of grapple with these bigger questions. So,

• 42:05Geoff Nielson?

  I, I don't know, should, should we be waiting for somebody to tell us what's next? Or should we be empowering people to, to come up with those answers by themselves?

• 42:13Speaker 01

  I think we all own this, right? Our society is constantly changing. We're about to see more change in our society in the next 20 years than perhaps the last hundred, perhaps the last 200. You know, that's a big deal and we all need to help each other through it. And yeah, I think businesses will pop up that help people figure out what's your life 2.0, right? There'll be people to help with that. But I'm encouraged by the fact that yes, some people turned to alcohol and drugs and didn't do so well and came out of COVID depressed. And I feel very bad for them. But there are also people who figured out a love of making

• 42:54Speaker 01

  bread and, you know, getting out in nature more and discovered arts and crafts that they've carried on to this day. And so I think that that little glimpse, that two or three months where we were all in lockdown was a test. And some didn't do so well in it and some did. So we need to help people who who didn't do so well in that, as this becomes something we face on a grand scale, help them make that transition.

• 43:20Geoff Nielson?

  Yeah. And and with that transition, do you see AI as a risk to people finding meaning? And what I mean by that is, you know, there's this kind of talking point going around now that like, you know, AI was meant to do all the administrative stuff so that people could do all the creative stuff. And low and behold, suddenly AI is writing songs and it's creating paintings and, you know, it's people who are left, you know, doing the dishes which AI can't do. Does that have merit? Or do you see that as just kind of, I don't know, an easy talking point that that won't bear itself out in the long term?

• 43:57Speaker 01

  I mean, it's a fair critique of AI today. But at the same time,

• 44:03Speaker 01

  people who who don't have the ability to draw amazing images, but they have an idea in their head that they can't realize, and they've been impotent up to this point, or people who want to write a song and they had, they know what they want, but they they can't sing, they don't play an instrument. Now they have access to that. AI is going to help them realize their dreams. So I think in some ways, it is unleashing people's creativity. They're just using these tools to create the output rather than picking up a guitar or, you know, and some people will argue with you don't have calluses on your fingers, you're not a musician, you're not creating music. Well, there's some truth in that, but not everybody wants to take that part. And I suspect that we will have.

• 44:49Speaker 01

  People will want artisanal things, things that were made by humans.

• 44:55Geoff Nielson?

  Yeah.

• 44:55Speaker 01

  It doesn't mean there won't be a marketplace for things that were made by machines guided by humans. So I think you'll see both.

• 45:03Geoff Nielson?

  Right.

• 45:03Speaker 01

  There's a place for all of it, I think.

• 45:04Geoff Nielson?

  Yeah, it just becomes kind of a two-speed, you know, economy or a two-tier, you know, there's the, are you willing to pay the premium for, you know, the, the bread made by human hands? Or, you know, whatever, whatever, you know, use case you want to use. One of the, um, one of the other potentials I see here is, you know, when we look at what AI is able to unleash for people, there, there's the creative side that we discussed, but there's also, there's also the productivity side. And there's also the ability, you know, in my mind of if people want to start their own enterprise, their own company, the ability to do that now seems like it's an order of magnitude easier than it was 10 years ago.

• 45:47Geoff Nielson?

  And it seems like to your point, Steve, it's, it's only getting easier. It's, I mean, is, is this the direction we're going in? And, you know, is that something that, you know, enterprises of, you know, 50 or a hundred thousand people should be worried about if suddenly, you know, any individual can, can run their own organization and, and, you know, play in their space?

• 46:12Speaker 01

  I mean, it's empowering of, of change. Jensen Huang, I mean, he's running the most valuable enterprise on the planet right now. And he famously was asked a couple of months ago, you know, what's your plan for the future of Nvidia? And he said, well, we've got about 32,000 employees now. We're planning to head to, you know, maybe 50,000 human employees, supported by a hundred million agents.

• 46:37Geoff Nielson?

  Wow.

• 46:38Speaker 01

  And that tells you what the workforce of the future is going to be. It's going to be humans, digital employees and robots working side by side. You know, and people have thrown around the idea of, you know, when are we going to see the first unicorn, first billion-dollar enterprise with one employee? Um, you know, it's possible. I think it's more likely you'll see a group of a few, you know, basically a C-suite supported by agents. Um, but yeah, it's, it's going to unleash an enormous amount of opportunity and creativity. And that's a good thing. But yeah, if you're a big enterprise that's kind of stuck in the past. The average life of a company is what, forty years? So maybe it's your time, which means you need to start thinking now about how are you going

• 47:21Speaker 01

  to scale your operations using digital employees?

• 47:25Geoff Nielson?

  Right.

• 47:26Speaker 01

  Employees who work for electrons, not dollars and cents.

• 47:30Geoff Nielson?

  Right. And, and, you know, just on, just on the point there that you mentioned about, you know, oh, maybe it's a C suite and then, you know, down from there it's AI. Is, is it? I was going to use the word risk. I don't want to use the word risk. Do you see us moving toward a world where there's AI C suite? Where we get to an AI CEO? Or is that too fanciful?

• 47:55Speaker 01

  I don't think it's too fanciful. It's not going to happen right away. It starts off where, as these digital agents start to come on the scene and OpenAI is rumored to launch their operator agent in January of 2025. So that's when we'll start to see this happen. You know, we're going to move, we'll move quickly into a world of a hundred billion software agents, which means that every one of us will be a manager. We will all manage, you know, really smart interns that we can have. They, they act like remote employees. But the question is, when do we then start to be managed by an AI?

• 48:37Speaker 01

  In some circumstances, an AI may be more capable as a manager. Will they move to CEO level? You know, once we get to AGI or ASI, maybe all better off. And yes, we will have an AI that is going to do a better job than, than a human. But will we accept that is the real question?

• 48:58Geoff Nielson?

  And I'm, I'm glad you brought up AGI because, you know, that's, that, that's another question I'm sure you get fairly regularly is, you know, is AGI something we're going to see in the next five years? And for a lot of the conversation we've had today, Steve, like, do we need AGI to get to these places? Or is it, you know, just one, you know, potential, you know, one potential innovation?

• 49:21Speaker 01

  Yeah, I don't know if you need AGI to get to these places. What you need is a highly accurate AI. The accuracy of AI is not there with hallucinations. There are some techniques you can do to improve that. The reasoning capabilities you see in models like O1, O1 Pro particularly,

• 49:38Speaker 01

  using RAG so that you're operating off, you know, a source of ground truth, help a lot. But reasoning and RAG stuff only get you so far. It needs to be more accurate than it is today. So it's reliable. Once you get to that level, I mean, these AIs are already operating at sort of PhD level. You know, a digital PhD employee that I can hire for 50 cents an hour because I'm just paying for electrons. Yeah, that's interesting. I don't think it needs to be AGI to do that. When does AGI happen, sort of implicit in your question? The smart people I speak to in the industry, the range I get is from next year to never. And it's somewhere in between.

• 50:23Geoff Nielson?

  Nice and, nice, nice and precise.

• 50:25Speaker 01

  Yeah. But the, the smart people that, you know, I'm, I'm hearing 2028, 2029. Ray Kurzweil, bless him, has, has been saying 2029 for 40 years.

• 50:35Geoff Nielson?

  Yeah.

• 50:36Speaker 01

  It would be kind of nice if he was right.

• 50:39Geoff Nielson?

  Yeah, interesting, interesting. What are, what are you seeing people get wrong about conventional wisdom around AI right now?

• 50:50Speaker 01

  I think the adage that Bill Gates uses is right, which is people always have, they always overestimate the impact of a technology in the short term and underestimate it in the long term. I think that's the most likely with AI. There's a lot of furor about AI right now. Everyone's excited about it. And, you know, you had me on this podcast because everybody's excited about AI and rightly so. But we're probably going to see some sort of a dip coming as people's expectations fall, you know, fall short of what's delivered. But in the long term, I think we're going to see a wholesale transformation of our society because of AI. But that's probably the best answer. Are there specific things that?

• 51:33Speaker 01

  I think there's just so much hype and excitement over AI and it's well placed. But it's just going to take a little longer than people think in the short term for it to have true impact in the enterprise. But then, once it starts to find its way in, I think you're going to see dramatic change.

• 51:48Geoff Nielson?

  Right. So, you know, thinking about that dramatic change, Steve, you know, you mentioned before we started recording that you're actually working on a new book right now, kind of revisiting, you know, what the future looks like from an emerging tech landscape. Can you maybe give us a sneak peek about, you know, what's in there, what you're excited about and what we should be thinking about, you know, over the next five or 10 years?

• 52:11Speaker 01

  Sure. So the first book I wrote was called The Innovation Ultimatum. And the premise of that was to to arm business leaders with the right questions they need to ask so that they understood the technology to level where they could work with vendors and figure out how to use this basket of six technologies to innovate in their organizations. And the imperative to do that, hence the Ultimatum. The second book is going to be creatively titled The AI Ultimatum. And it is really leaning in on that one technology and trying to do roughly the same thing. So help business leaders, equip them with the right questions to ask, some frameworks to help them think through how and when might I use AI and what

• 52:52Speaker 01

  kind of areas might it help me move my business forward. And then empower them to participate and and build a roadmap for an AI transformation for themselves personally and also for their organization. So that's hopefully coming out next year.

• 53:11Geoff Nielson?

  Amazing. Looking forward to to reading it and and diving into that. Steve, what technology or implication of a new technology is most keeping you up at night these days?

• 53:23Speaker 01

  Oh, I mean, other than AI potentially challenging our role in the world and giving us a lack of purpose.

• 53:32Geoff Nielson?

  Oh, that one.

• 53:34Speaker 01

  That's a long term worry. And I think we will rise to it if we start planning for it now. But that's a long term worry. One of my most keeps me up at night.

• 53:48Speaker 01

  I just, I worry that we're not ready for the speed of change that's coming. It's going to come at us so quickly. And I think we've already seen over the last two years just how quickly the AI roadmap is moving forward in terms of its capabilities. It should prepare us somewhat for the speed that things are going to run.

• 54:08Speaker 01

  But I just, once this starts to bite and it starts to be deployed broadly in enterprises and that has implications for the workforce, I'm not sure that as a society we're ready to handle that speed of change. That's my biggest worry. But if we can start talking about it now, then I think we have a good chance.

• 54:31Geoff Nielson?

  Right. So how we make sure that it like, it doesn't just happen to us, which is like the risk right now that we're just...

• 54:37Speaker 01

  Right. Yeah. Yeah. I did a TED Talk in 2012 or something. I think I still had a bit of hair then. And the title of my talk was "Why Machines Must Make Us Better Humans." I think we need to have that mindset of rather than figuring out how to use machines to automate away talent, how do we use it to amplify and elevate human talent? And I think that just, that makes more economic sense in the long term. But it also is going to, it's going to enable us to be all much happier in what we do. It's not all just about a bottom line and making short-term profits.

• 55:20Speaker 01

  So that's, I hope that people will figure that out.

• 55:24Geoff Nielson?

  Yeah. Yeah. It's a, it's a lot to unpack and yeah, it's, it's going to be really interesting to see where the next few years go.

• 55:33Speaker 01

  Yeah. I mean, buckle up. 2025 is going to be exciting year.

• 55:37Geoff Nielson?

  Yeah.

• 55:37Speaker 01

  And I think 2026 beyond that.

• 55:39Geoff Nielson?

  Absolutely.

• 55:41Geoff Nielson?

  Steve, do you want to do a, just grab a soundbite of doing a quick plug for your website?

• 55:45Speaker 01

  Sure. So easiest way to find me is at my website stevebrown.ai. I do a range of different keynotes for public audiences, for C-suite and everything in between. I do AI innovation workshops to help people figure out use cases of the future for AI. And coming soon will be an online training course on all things AI, designed for business leaders and anybody who's interested to learn about AI on how you can use it to actually build your AI transformation journey. So stay tuned, coming soon.

• 56:15Geoff Nielson?

  That's great, yeah. Anyone we can get ahead of the curve and not just slapped in the face by this thing is a, is a win in my books.

• 56:22Speaker 01

  Yeah, make the, make the future happen because of you, not to have the future happen to you.

• 56:27Geoff Nielson?

  There you go. Steve, thanks so much for joining today. I really appreciate it and really, really insightful conversation.

• 56:34Speaker 01

  Yeah, we enjoyed talking with you. Thanks for the great questions.

• 56:37Geoff Nielson?

  Amazing. Thank you.