Digital Disruption

00;00;00;20 - 00;00;21;26

Geoff Nielson

Hey everyone! I'm super excited to be sitting down with I. Venture capitalist Jeremiah Yang. He's the general partner for AI Investments at Blitz Scale Ventures, set up by the founder of LinkedIn to bet on tomorrow's AI leaders. What's cool about Jeremiah is that he doesn't just follow the trends. He's the one deciding which I startups get the chance to change the world and which ones don't.

00;00;21;29 - 00;00;46;04

Geoff Nielson

I want to know what makes him tick. What does he look for when he's trying to find the billion dollar technology? Which cutting edge technology is getting his attention, and where he thinks all of this is taking us next. Let's find it. Hey, Jeremiah. Super happy to have you here on the program today. You're the general partner of AI Investments at Blitz Scaling Ventures.

00;00;46;06 - 00;00;57;21

Geoff Nielson

First and foremost, I guess I just wanted to ask you, you know, you're an AI startup investor. What does that mean? And what type of businesses and startups are you looking at in 2025?

00;00;57;24 - 00;01;25;11

Jeremiah Owyang

Well, Jeff, first of all, it is a delight to be here. It's a wonderful day here in Silicon Valley. I'm just immersed in the Silicon Valley ecosystem. And I got to tell you from from the macro view, it's all about AI. So the main freeway, 101 is around 80%. 75% of the billboards, are about AI. And there's typically 5 to 8 AI startup events per night.

00;01;25;13 - 00;01;54;24

Jeremiah Owyang

There's typically two to 3 to 4 hackathons each weekend in San Francisco and in Silicon Valley, each with 300 developers building. I've been in Silicon Valley since.com era, and I've never seen the level of energy here. So my job is easy, but hard at the same time as VC. It's easy because the startups are here in Silicon Valley, but the hard part is there's over 38,000 AI startups and projects, according to the database.

00;01;54;24 - 00;02;17;24

Jeremiah Owyang

There is an AI for that dotcom, of course, and it is just an amazing time to be here in the early part of this journey. And I've been in the generative AI, this part of the market full time here as at the VC firm for two years made eight investments. And we're looking for early stage startups like Pre-seed, seed and sometimes series A startups that are starting to show growth and traction.

00;02;17;27 - 00;02;24;26

Jeremiah Owyang

And there's a couple of things that we look for, but at a high level, that's what I'm seeing here, right in the heart of Silicon Valley.

00;02;24;29 - 00;02;50;04

Geoff Nielson

It's so amazing. And the volume is just, you know, as you said, like it's hard to even fathom that much excitement that many people, all, you know, with the same energy toward AI. You know, one of the questions I want to ask you before we go deeper into the nature of the startups themselves, is, you know, you talked about com and you know, having, you know, obviously there's a long history of kind of, you know, boom and bust and hype in the Valley.

00;02;50;07 - 00;03;04;09

Geoff Nielson

From your perspective, we hear so much about AI. Where do you see us as being in the hype cycle? Are we kind of, you know, over a hump, so to speak? Is it just going up from here? What does that look like from your perspective?

00;03;04;11 - 00;03;29;08

Jeremiah Owyang

It's it's challenging to tell, but I still think we're in market formation mode, which is towards the early part of the cycle. And so I've been through five tech cycles.com, web two, the sharing economy, Web3. And now I my background, by the way, I was an industry analyst at Forrester Research. We spun out, we started our own boutique industry analyst firm, which my job was to forecast what's going to happen in tech and business.

00;03;29;10 - 00;03;47;20

Jeremiah Owyang

And I've been a professional speaker and then an angel investor, which led me to a full time role at a venture capital firm. So tracking trends is really part of my DNA and what I do. So we're definitely in the early point of the market, you know, again, 38,000 startups. It's like the Cambrian explosion of all these startups.

00;03;47;22 - 00;04;08;15

Jeremiah Owyang

There will be a point in the market where we will have consolidation, there will be acquisition. Startups die, and we're seeing some of that happening now. We're seeing some acquisitions happening now. And so that's just starting to show. But we're we're still in phase one as market formation. This feels like a 10 to 15 year cycle. But it's really hard to forecast.

00;04;08;17 - 00;04;29;13

Jeremiah Owyang

Even our advisor of scaling, Reid Hoffman, he says he can only see two years out. And he's the first investor in OpenAI. And he's in the on the board of directors of Microsoft, and he's guiding us. Our firm is based upon the book called Bullet Scaling that he wrote with Chris. Yeah, my friend for 20 years. So I've read Hoffman can only see two years out.

00;04;29;20 - 00;04;34;27

Jeremiah Owyang

You know what? I'm definitely going to be able to see a lot less than that.

00;04;35;00 - 00;04;50;22

Geoff Nielson

So so let's talk about that scale for a minute. So if we think about two years out or, you know, even six months out, what are the big trends, or the big patterns that you're starting to see emerge that you think are really going to take off over the next handful of months?

00;04;50;24 - 00;05;14;13

Jeremiah Owyang

So let's start with today. Right now, the topic de jour is AI agents and AI agents complete actual tasks. Large language models are great at completing sentences. It's text, but I agents actually will go into your inbox. Manager emails can go and help edit. You know a video can create you know workflows can actually talk to customers. Do customer care, do marketing for you.

00;05;14;13 - 00;05;36;06

Jeremiah Owyang

It actually completes the tasks similar to entry level workers. Most of any entry level task that is on a digital device that will be automated within the next two years by AI agents. And that's pretty much a given in Silicon Valley. We all expect that to happen. In fact, many of the startups have 22 employees, and they're generating millions of dollars of revenue per employee.

00;05;36;08 - 00;06;03;25

Jeremiah Owyang

That's called the lean AI native startup. And they're using AI agents. So that's today at the front of the market. AI agents are helping people to get things done. Looking forward into the future. There's a number of trends to look at. One is that we're seeing AI agents in deep verticals. So we're going to see agents in health care agents and finance agents and real estate agents in even government agents in military.

00;06;03;28 - 00;06;30;28

Jeremiah Owyang

Another trend we're seeing is called work models world, like, you know, the planet. And just as we've seen large language models be able to predict what human sentences, how they will be completed, that's essentially what they do. A world model will predict what you're going to do physically, but humans are actually very predictable. Like we go to work, you go to the bathroom, you get coffee or maybe reverse that order.

00;06;31;00 - 00;06;52;15

Jeremiah Owyang

You're going to go to lunch at 12 and you get in your car five, you go home, you're going to go to this store versus that store. We know what radio station you're going to listen to. So a world model predicts what humans, animals, weather, cars, those patterns on what people do. So that's the a new emerging category called world models.

00;06;52;18 - 00;07;26;06

Jeremiah Owyang

Now after that is called humanoid robotics or the physical instantiation of AI into the physical world. We shift into self-driving cars and robots will be among us and humanoid robots. So that's coming as well. So those are just a couple of trends that we're tracking and then which I will be investing in. So it's my job to think about what's going to happen and make sure I understand the market, how the right connections, know the founders, make friends with them, show them how we can help them, as in and then invest in those startups.

00;07;26;06 - 00;07;28;22

Jeremiah Owyang

So that's kind of how I see the future rolling out.

00;07;28;24 - 00;07;54;10

Geoff Nielson

It's it's both of those examples are super, super interesting to me. And, you know, clearly big gnarly problems to solve. Are you starting to see with some of the startups that you're looking at and looking to invest in, or are some of those starting to be in that space, or is it still predominantly in kind of the AI agents and generative AI space that you're primarily focused?

00;07;54;13 - 00;08;17;23

Jeremiah Owyang

We've done a number of investments, and around half of them are AI agents, the other half are in, specific verticals, like I kind of mentioned, like how we think of the market. And so that's here now, and I'm exploring the world model space. And then the robotic space is next, to understand like how that's going to sort out what I do to stay on top of the market.

00;08;17;25 - 00;08;43;10

Jeremiah Owyang

So I, I attend on average three AI events in Silicon Valley at SF per week. So that's like 150 events per per year. And that's just I love it. And it's I've always been doing that here in Silicon Valley. So I'm just hyperconnected. And when I go to an event I know about a third of the people in the room just because I show up so much, and then another third of the room I can get introductions to, and a third, I don't know, you know, people fly in, right?

00;08;43;10 - 00;09;06;04

Jeremiah Owyang

So usually I have enough network where I can get all the signals and meet people or get to people I want to talk to and and listen and learn and and do things. I host Lama Lounge, one of the longest running Silicon Valley events, and we hosted several times per year here in Silicon Valley. And typically it's 300 AI founders, CEOs that show up and around 75 VCs.

00;09;06;04 - 00;09;26;04

Jeremiah Owyang

My network, my friends, my peers, sometimes competitors, by the way, and then around 50 fortune 500 executives and AI leaders. So I'm just hyper connected to all of these things. And for sure, I'm seeing this rise of robotics emerging with the AI space, that it's all starting to converge at a high level. And I love to hear your thoughts.

00;09;26;04 - 00;09;39;28

Jeremiah Owyang

Is AI is permeating every industry and every technology trend. It's like it's everywhere. It's it's just kind of like air where we just breathing it. It's connected to every single technology movement.

00;09;40;01 - 00;09;53;06

Geoff Nielson

So Lonna Lounge, you mentioned that it's, you know, hundreds of AI founders, it's VCs. What does it actually look like? You know, on the floor and in practice, is it tech demos? Is it pitches the conversations? What what actually transpires at an event like that?

00;09;53;08 - 00;10;13;05

Jeremiah Owyang

Well, I love to invite you in. Next time you're in town, please be my guest. So it's hosted at one of the top tech companies, one of the hyperscalers. So it's been hosted at Amazon Web Services, SAP, Capgemini, Stanford Campus, zoom campus. The mayor of San Jose has shown up the founder of zoom, a billionaire, Eric Yuan, and showed up.

00;10;13;07 - 00;10;31;00

Jeremiah Owyang

Press and media. It's been covered. The Atlantic, The New Yorker, TechCrunch. So it has really grown to a massive thing. And you can see the group photos. We take one giant photo. So what everybody usually says is that the energy level is so high. People are so excited to be there. We decline hundreds of people. There's usually a line down the street to get in.

00;10;31;00 - 00;10;50;21

Jeremiah Owyang

There's videos showing that happening, and what happens is out of the 300 to 400 people that attend, many of the founders are applying to demo, and there's ten demo slots that are offered to these startups that I choose. And by the way, three of the ten slots are always reserved for female founders. And we want to make sure often we're at that parity.

00;10;50;23 - 00;11;08;27

Jeremiah Owyang

And it's really important we have that diversity, and we try to ensure that we see all the different things. So there's demos on the floor and then we all come together for the kickoff and I do something very unique. So there's usually 100 to 200 AI events in Silicon Valley per month. That's it's insane. Right. So how do you stand out?

00;11;08;27 - 00;11;30;08

Jeremiah Owyang

Well, we've got a great brand. We've got a great logo at the Who's who shows up. But what I do to make it unique is I have a giant conch shell. Yes. And I am a former jazz trombone player. And so I play it and everybody knows it and they scream it. So it has its own audio signature kicking off that event and the energy just goes up, boom, boom, boom, all these notches.

00;11;30;11 - 00;11;47;26

Jeremiah Owyang

We have a keynote speaker, and then we have the ten startups who come in pitch for only 30s. It's kind of like that Eminem song, like you have one shot and they got one shot to pitch in front of 75 PCs and 300, CEOs. And this is their shot. And so this is like a big moment for them.

00;11;47;28 - 00;11;52;16

Jeremiah Owyang

And many of them get funding customers, partners, employees from that event.

00;11;52;19 - 00;12;21;04

Geoff Nielson

Wow. No, it's it's, it's amazing. It's like it's, you know, sounds like kind of like Shark Tank on on speed or something. So it's, really cool to be able to see that, that level of excitement and that level of investment. So I want to come back, Jeremiah, to one of the questions I asked earlier that we started to get into, which is, you know, for you and for some of these VC investors, what are you looking for these days in, you know, in an AI or in a tech startup?

00;12;21;05 - 00;12;31;09

Geoff Nielson

You know, obviously, blitz scaling is kind of the name of the game, but what are some of the indicators that, you know, there's there's the right DNA here, whether it's the right people or the right idea.

00;12;31;11 - 00;12;51;08

Jeremiah Owyang

Great. So it depends on the stage of the startup. So an earlier start up, we're going to look more carefully at the founder, his or her background. What is their pedigree. Do they can they learn quickly? Do they have a track record of doing new things? What's their attitude and why are they really doing this? Like really getting down to core motivation.

00;12;51;08 - 00;13;12;20

Jeremiah Owyang

So that's really important in the pre-seed and seed towards series A or B, the company scaling. Sometimes the CEO is even replaced by a professional executive. Right. So at that phase we're looking at the scaling attributes. All throughout our thesis because of the Blitz scaling book, which used to be a Stanford class where there's two major business strategies.

00;13;12;22 - 00;13;29;10

Jeremiah Owyang

And first, I want to just share that a technical moat in AI last only a few months before it used to last years, no longer. In one tweet from Sam Altman, your company could get wiped out.

00;13;29;12 - 00;13;29;25

Geoff Nielson

Wow.

00;13;29;27 - 00;13;54;10

Jeremiah Owyang

Literally. It could be overnight, right? They'll announce a new feature, the one you've been working on for two years. You're ruined. So a technical moat is very thin inches feet. It's not a very wide moat and certainly not deep. Very few people have a real technical moat. If you do, it's not going to last long. So what we look for are a few other business strategies.

00;13;54;10 - 00;14;18;18

Jeremiah Owyang

For example, do you have deep industry experience in a specific vertical? Do you have all the contacts in the construction space and you know that space because OpenAI is going horizontal, anthropic is going horizontal. Google, Microsoft, Amazon, they all go wide. So if you have deep expertise in one vertical, secondly, do you have proprietary data that nobody else has.

00;14;18;22 - 00;14;42;25

Jeremiah Owyang

And that should be a legal contract with clients. Or you've acquired IP and you've trained your models or agents on that specific thing that nobody else has. The key classic business strategies to blitz scaling. There's two major things, and this is based off the interviews that they did at Stanford with the leaders in the market. It's viral effects and network effects.

00;14;42;27 - 00;15;04;19

Jeremiah Owyang

So a viral effect is when the product spreads on its own with. And we can look at this data flow or no marketing low or no sales low or no advertising. So if you strip away that data, by the way, I'm not saying don't do those things. I'm just saying let's pull the data away. Does the product actually spread organically, whether it's word of mouth?

00;15;04;22 - 00;15;26;08

Jeremiah Owyang

More importantly, product led growth where the product is designed to spread DocuSign box, LinkedIn, Airbnb, Uber, they all do that. And three the third thing we look for is is there a distribution strategy? Like for example, does Salesforce promote your SaaS startup in their network? Do you have a lot of GitHub stars? And therefore everybody sees and it spreads.

00;15;26;14 - 00;15;50;07

Jeremiah Owyang

So that's that's the key strategies, viral effects. Does the product spread on top? The second one we look for and we have a scorecard. We score companies on this if they have 80 points or higher and total. If so we bring it to Reed Hoffman for a review. The second one is network effects. Network effects are when the value increases as every new user and customer joins.

00;15;50;09 - 00;16;16;23

Jeremiah Owyang

So Airbnb, Uber, Facebook, social networks, marketplaces, exchanges, app exchanges, B2B cloud infrastructure, they all have network effects. The more people that participate, the value increases for everybody else. So viral effects are key because the product spreads to the whole market at low cost. But then you got to keep the customers. So network effects means the value increases, therefore increasing the loyalty and reduces your switching.

00;16;16;25 - 00;16;27;01

Jeremiah Owyang

So that's what we look for. Awesome founder deep vertical knowledge proprietary data, viral effects. Network effects. Review by Reid Hoffman.

00;16;27;04 - 00;16;50;23

Geoff Nielson

I love, I love that model, Jeremiah. And it's so clear and so rational to me. The one piece I wanted to ask you about. So viral effects, product led growth, all of that like completely computes in my mind and makes sense. Network effects to me. Seems like it could be a double edged sword, right? If it's saying like, oh, in the future, if everybody joins this, it's going to be amazing.

00;16;50;23 - 00;17;01;17

Geoff Nielson

But right now it's not. How do you mitigate that risk? Is it only joining at a certain phase in the growth, or, how do you, how do you engage with that?

00;17;01;19 - 00;17;19;03

Jeremiah Owyang

Yeah, it's a great point. So at Pre-seed, it's, it's it's difficult those sorry. It's more difficult to determine. Do they have viral effects and network effects and precede the early stages of the company. But right around seed the starting to get traction. The product's built. They're starting to get product market fit. They kind of know who their ideal customer profile is.

00;17;19;05 - 00;17;41;04

Jeremiah Owyang

So we can see their business strategies by then. So it's pretty obvious. So some of the companies, they already have a a data network effect or the AI's learning, that is a network effect where they have multiple customer cohorts that are collaborating in a platform. That's a network effect. We can see that in the product already, often in seed and often in the pre-seed the roadmap.

00;17;41;07 - 00;17;54;21

Jeremiah Owyang

I don't tell them too much what we're looking for, but they should be smart enough to just like perplexity. It like network effects. I can see it in the roadmap if it's coming. So those are just some of the kind of things that we look for, even though it may not be fully built out.

00;17;54;24 - 00;18;24;19

Geoff Nielson

Got it, got it. Now that makes complete sense to me. You start one of the things I wanted to ask you about and you already started answering, is just how you see the shape of the AI marketplace in the AI industry. Kind of unfolding. And, and you mentioned that for a lot of the big players like, you know, OpenAI, or some of their peers that they're kind of horizontal and fairly shallow and you're looking for more deep, vertical plays in, in specific industries.

00;18;24;21 - 00;18;41;20

Geoff Nielson

It is that I mean, first of all, is that is that a fair summation of your, you know, prediction of the shape? And is there any more nuance either in industry or geo or any sort of, demographics that help you predict and understand what this could all look like a few years from now?

00;18;41;23 - 00;19;04;20

Jeremiah Owyang

Yes. So we have done some horizontal bets, but they're not in the spaces, the giant foundation models or the giant tech scalers like Google, Amazon, Apple are playing in yet. So which is fine because they are, but likely to acquire these startups. So we definitely done some emerging horizontal plays and then also these vertical plays. But it's too late for me to get into OpenAI or anthropic, right?

00;19;04;20 - 00;19;33;04

Jeremiah Owyang

Those companies are worth billions and trillions now. So in general, I see that now this is important to note that many startups, that are around the world, they are often very successful in their specific region. And you asked me about geography. I'm in the Middle East very often. I've been in Asia quite a bit, and they are great at tackling their market, which could be a culture or language or region or a country or specific area.

00;19;33;07 - 00;19;53;28

Jeremiah Owyang

And one of the requirements of many, maybe most VCs in Silicon Valley is that the startup needs to go global. And so that's often a big challenge for regional based startups. But the founders often fly to silicon Valley to meet the the ecosystem and to raise money and to show their plans on how they plan to go global.

00;19;54;01 - 00;20;11;27

Jeremiah Owyang

So that's an important thing. Now, with that said, we've invested two times in India, one time in Canada in the fund that I'm managing, and we'll continue to invest globally. But a mass majority of the startups are in Brazil. But the mass majority of the startups tend to be headquartered in Silicon Valley. There's just the acceleration, the movement.

00;20;11;27 - 00;20;31;03

Jeremiah Owyang

It's just happening so fast. At my own event Lama Lounge, I pull the audience to see where are you from? The mass majority are from U.S. and then live in Silicon Valley. But the second largest group, which is a 2,025%, are Europeans. But they're coming here because they can innovate faster. European regulations have been a stranglehold for many of them.

00;20;31;06 - 00;20;59;12

Geoff Nielson

That's interesting. I wouldn't, if you if you asked me to guess where the second largest group is from, I don't know that I would have guessed that, but that's, that's really interesting to me, you know, one of the one of the kind of adages about AI and I, you know, big tech players you hear these days is that we're in AI arms race and it's going to be winner take all and everybody is dumping money into it, and that the winners are going to be kind of the people seem to think it's going to be one of the incumbent big players in the space.

00;20;59;14 - 00;21;16;17

Geoff Nielson

Do you buy that? Like do you see the the big tech players as having a stranglehold on it? Do you see new players emerging and what are the implications, you know, as it pertains to some of these startups. So they just need to get acquired? Or is there room to kind of grow on their own?

00;21;16;20 - 00;21;36;26

Jeremiah Owyang

Great question. So I published a diagram called the AI Tech stack. I also did one called the AI Agent Ecosystem. It's a framework. You can find those. Just do a perplexity on those, and you'll find the graphics and how I've literally drawn out the market in boxes to show the segmentations of the different products and the different companies, and how they segment.

00;21;37;03 - 00;22;01;21

Jeremiah Owyang

I again, my background is I'm a professional industry analyst and forecaster turned VC. So it's a natural skill to me, and it depends on which part of the market where we will see a winner that takes most. Now we're often asked, I mean, this is a complex question, so whoever gets the AGI first is going to have a dominant position, but it will probably be multiple companies that achieve that.

00;22;01;24 - 00;22;18;16

Jeremiah Owyang

And in the A in the era of AI agents, where you will use your agent app to get most things done, you don't have to visit websites in the future. You don't have to visit apps. The agent will do those things for you, and they will also go to podcast and listen to it, and then and report back to you the way that you want to consume that information.

00;22;18;16 - 00;22;39;15

Jeremiah Owyang

Like you don't have to leave that experience. We're going to see a big shift in how we consume media. Now, with that said, I don't think we'll have one app that's your AI app. My thesis is, and it remains to be seen, is you will have the equivalent to the current amount of email accounts that you have now.

00;22;39;22 - 00;22;42;03

Jeremiah Owyang

So, Jeff, how many email accounts are you managing?

00;22;42;06 - 00;22;49;18

Geoff Nielson

Oh, that's it's a good question. Too many. Let's, I don't know much more than 2 or 3, let's put it that way.

00;22;49;21 - 00;23;13;22

Jeremiah Owyang

Okay. Cool. So let's say three. So you'll still have three very powerful AI platforms and therefore companies in your life. And there's a lot of reasons why is because Apple versus Microsoft versus opening AI versus cloud versus Amazon. Apple. They're going to fight tooth and nail to make sure that they still have a piece of your attention, or they have a piece of your data, and they're going to give you great options.

00;23;13;22 - 00;23;34;20

Jeremiah Owyang

And competition is wonderful. And that's what I think that's going to continue to happen. So I think I have 3 to 5 email accounts that I'm actively, managing. So that's how many dominant, what we call the meta agents, by the way, that will be in our lives. So I don't think it's one winner that takes or so.

00;23;34;22 - 00;23;59;18

Geoff Nielson

And I like that model. It resonates with me and it's in line with what I've seen. You know, both in kind of the consumer in the enterprise space. And for a lot of what we've talked about, it's been the consumer space. And, you know, we talked about vertical in terms of the enterprise space with your bets in the AI, the AI startups, you're looking at, is it predominantly consumer, is it predominantly enterprise, or is it, you know, kind of a blend?

00;23;59;20 - 00;24;24;27

Jeremiah Owyang

It's a blend. So I have an enterprise background. I was at Hitachi and data centers and and obviously industry analyst is very enterprise focused. So we've bet on a number of enterprise, players. In fact, 95% of VC funding I believe goes to B2B, not B2C. B2C is the chances of success are minuscule. It's very hard market. So most investment goes to B2B, right?

00;24;24;27 - 00;24;44;00

Jeremiah Owyang

So we've invested in one company which is very popular and growing fast is called crew AI, open source AI agents for the enterprise. And I want to just share this concept of the lean AI startup. Have you heard this or having guests talk about this? It's a concept that's been growing in the last few months in Silicon Valley.

00;24;44;02 - 00;25;05;27

Jeremiah Owyang

So a leaning AI startup has the AI first mentality where you if you have a business problem or a personal problem, you first see if there's an off the shelf AI that exists or an agent. And if you can, you grab it, you download it, or you use it, and if it doesn't exist, then you build it. And there's many no code tools that can help you do that.

00;25;05;29 - 00;25;29;12

Jeremiah Owyang

And if you can't do 1 or 2, then you hire somebody. So right now Silicon Valley is obsessed with this lean AI native leaderboard. It's actually it's a notion page and Alice out around 40 startups and the requirements to be on this leaderboard is the company has to be less than five years old. It has less than 50 fewer, fewer than 50 employees.

00;25;29;14 - 00;26;01;08

Jeremiah Owyang

And it's generating $5 million or more. Now this is the shocking stat. The average SAS company generates around 200,000 USD. That's revenue per employee per year, 200 K. Just hold that number. You my 200 K average employee revenue. You know, the big tech companies the big SAS companies are in that the lean I need of startups coming out of SF like 66% 70% are from S.F., they're generating 2 to $3 million.

00;26;01;12 - 00;26;28;20

Jeremiah Owyang

Wow. Wow. We've never ever seen that. So we invested in crew AI, which is doing hockey stick and adoption. There's they're they're following this these practices, these methodologies. There's four shocking stats with crew. Crew is in 60% of the fortune 500 enterprise agents. Number two the company's only it was birth around two years ago, less than two years ago.

00;26;28;22 - 00;26;52;13

Jeremiah Owyang

There's 30 employees, but 300 AI agents that are doing the work. So that's the future of companies 10 to 1 AI agents per employee. Like today, in this year, you know, that number will increase agents per employee over a year and revenue should go up. So that's what a modern company is looking like out of Silicon Valley. 2 to $3 million revenue per employee.

00;26;52;18 - 00;26;58;01

Jeremiah Owyang

You've never seen that before. That's ten x revenue compared to traditional one.

00;26;58;01 - 00;27;19;09

Geoff Nielson

It's especially cool to hear that crew is actually doing that. And it's not just, you know, they're promising that they'll do that one day. And the reason, Jeremiah, why why that's so exciting to me is, you know, I've had this hypothesis for a while now around, AI agencies. You know, I think a lot of people out there probably heard about this for the first time from Marc Benioff, you know, getting up at, you know, Dreamforce and basically Agent Force.

00;27;19;09 - 00;27;19;14

Jeremiah Owyang

Yeah.

00;27;19;15 - 00;27;50;15

Geoff Nielson

Yeah yeah yeah. Agent force just you know, agents agents agents and you know, a version of like the Ballmer developers, developers, developers, and it's easy enough for me to imagine a world where the big B2B and enterprise players like Salesforce just have a total stranglehold on the agents that organizations use. And it sounds like you're saying that doesn't have to be the case, and it doesn't look like it's going to be the case and that, you know, smaller organizations have have a shot at this.

00;27;50;16 - 00;27;54;13

Geoff Nielson

Is that fair? Am I representing that properly?

00;27;54;16 - 00;28;18;13

Jeremiah Owyang

Absolutely. So the big enterprise companies like Salesforce, Adobe and Amazon, they're big, but they're also very slow. So the startups are maneuvering much faster and getting faster adoption. Plus, open source offers something that these lock in SaaS companies can't offer. And many CIOs are really tired of being locked in. So open source is a faster way and they can control the data, they can download it, use it on prem.

00;28;18;16 - 00;28;43;18

Jeremiah Owyang

So there's a numerous reasons why the startups are playing here. Now, Salesforce doesn't have a lock in at the same a week before, Agent Force, HubSpot launched agent Dot. I Dharmesh, you know, push that product out, which is a marketplace of AI agents. And now every other big company in in SAS, in B2B is launching agents of some form, so is going to be a standard offering by the end of the year.

00;28;43;18 - 00;28;51;06

Jeremiah Owyang

In fact, most announcements happened in fall. So we should expect to see that, happen across the entire industry.

00;28;51;09 - 00;29;22;23

Geoff Nielson

Yeah. Wow. So yeah, it sounds like in one form or another, they're the agents are here and they're, you know, starting to have an impact on, you know, organizations of all sizes. Jim, I wanted to ask you about that impact specifically and who you see as kind of being most at risk of disruption from this. And there's all sorts of different answers from, you know, more junior employees to more mid-level staff to, you know, the types of organizations that are going to be disrupted and how it changes the industry.

00;29;22;27 - 00;29;27;10

Geoff Nielson

Well, what are some of the macro patterns that you're starting to see emerge?

00;29;27;12 - 00;29;52;10

Jeremiah Owyang

Thank you. So we should first start with some humility. So when I speak at conferences I ask the audience, raise your hand if you think people, people around you in your organization will be replaced by AI. And of course, everybody raises their hand that I say, raise your hand if you think your job will be replaced by AI.

00;29;52;12 - 00;30;19;21

Jeremiah Owyang

And only like 5% of the hands go up. So what's going on here, friends? We got to be honest. Everybody's at risk. Unless of course, perhaps your in giving, you know bedside manner like a nurse, right? Or you're in a market where there's more demand than there will ever be. Which it's just hard to see. Like that's going to be impacting the mass majority of people should be at risk, and even VCs are at risk from AI.

00;30;19;24 - 00;30;37;09

Jeremiah Owyang

Everybody's at risk. So I think we need to understand that if you work behind a digital device, mobile phone or laptop or tablet, your actions are being recorded and therefore they can be reproduced if your actions physically are being recorded on a camera, that will feed the world models. And eventually we will see robotics in the prime industries.

00;30;37;09 - 00;31;00;28

Jeremiah Owyang

Like what are we seeing that's in dark warehouses? It's it's happening. The most common job code in the United States is a professional driver or trucker, where self-driving cars are common. Carmen, Carmen, Carmen in San Francisco. We it's a normal thing to see. So there's significant impacts coming to society. So the roles I prefer to think about the tasks.

00;31;00;28 - 00;31;23;10

Jeremiah Owyang

So the tasks that are replicated and they're of high value, those will be automated very fast. So those are most likely to happen now people there's a big question around will developers be automated? There's still a high demand for developers. And we've seen some of the salaries being offered by the big tech giants, $10 million packages, up to $200 million packages over four years.

00;31;23;13 - 00;31;49;28

Jeremiah Owyang

Obviously, the computer scientist, the actual inventors, there's still a massive shortage for the top talent. So it just depends where you look in the market. We probably are seeing already an eradication of customer care. Tier one customer care. I've seen so many startups replacing STR sales. BTR sales, that's already being replicated. Content. Content marketing, the the the communications agency.

00;31;49;28 - 00;31;55;18

Jeremiah Owyang

Media industries are generally shrinking. So I'm definitely seeing those impacts happening right now.

00;31;55;20 - 00;32;20;23

Geoff Nielson

So what's the for? I guess for us as a society, whether we think about education or workforce, what are some of the implications here? What what do we need to be thinking about both individually and collectively as we go through this period? And I don't know if inevitable is too strong a word for you, Jeremiah, but it feels like there's almost an inevitability to this, disruption to the labor force itself.

00;32;20;26 - 00;32;41;09

Jeremiah Owyang

I think one thing that so think about, and I have a specific question I asked I leaders in this question gets to the heart of it, and you might want to think about using this question with your experts as you bring across the show. The question is this how are you raising your children? So I ask that to my CEOs all the time.

00;32;41;09 - 00;33;05;21

Jeremiah Owyang

I ask that to IVC all the time, and they tell me what my child to learn how to be a leader or learn to have empathy so you can influence others or understand what people need or community. The fact that there's 200 and I events in person in Silicon Valley right now, even in the summer, is an indicator that people want to be together, even those that are building AI.

00;33;05;24 - 00;33;26;16

Jeremiah Owyang

So there's actually there is opportunities if you learn how to look like what those future walls will be and they won't be replaced. So that's the question I ask people how you raising your children. So those are skills, right? Or it's not a specific hard skill that I think like ten years ago we said every child needs to learn coding.

00;33;26;19 - 00;33;47;18

Jeremiah Owyang

I think that's helpful. But it's also going to be useful to know Spanish. Right? You know, I just not sure that there's one thing, one specific skill that you have to do. So learning how to overcome obstacles and be resilient is key. So I have children. Every year they do a Spartan obstacle race. It's like a military obstacle race out in the dirt, right?

00;33;47;18 - 00;34;02;19

Jeremiah Owyang

I've done over a dozen of them. And so my kids do it and I cheer them on. And, you know, they train for it. And there's a different obstacle. There's a wall, literally a wall of different sizes. You got to go over it, under it, through it, like, whatever, get over it. You got to do it. And so they have to learn or there's monkey bars.

00;34;02;19 - 00;34;26;12

Jeremiah Owyang

And that's a way to teach resilience. How do you overcome obstacles in your life and be ready to adjust this next generation, generation Alpha? Gen Z is already in the workplace. Generation Alpha is the next. They. So I was I'm digital native. The internet came when I was in high school. College. I'm Gen X, but Generation Alpha is going to grow up with AI.

00;34;26;12 - 00;34;58;14

Jeremiah Owyang

So they're AI native. So they're going to be used to getting information and recorded experiences from AI. And in some cases, like permutations of wisdom, that's never happened at that level before. And I will start to know their environment and give personalized guidance to them. That's just not something we've ever seen before. And of course, with every technology going back to the advent of fire, right, or steam engines or the industrial revolution with, with coal plants, you know, creating lots of products.

00;34;58;14 - 00;35;25;28

Jeremiah Owyang

But then we have emissions issues, right? Every technology set has amazing upsides, but also almost always equal downsides. Although we're typically in a better place in most cases. So with AI, we will also have great upsides. And there's going to be some drawbacks, but we don't really know what all the drawbacks are to society yet. But being connected to AI all the time, will help us in many ways, but will also cause us to be dependent on AI.

00;35;25;28 - 00;35;34;05

Jeremiah Owyang

And if it guides us astray, of course, that's going to be an issue. And that's a big political topic. Even this, around the world right now.

00;35;34;07 - 00;35;58;15

Geoff Nielson

So, the AI native piece is, is one that's really interesting to me. And, and that the piece that I've been reflecting on lately is just, I guess the power or, and maybe in some ways, the tyranny of expectations, right? When you've got that AI native piece, you can get the answer so quickly. And any services that are plugged in, there's such minimal friction to getting you what you need.

00;35;58;17 - 00;36;31;26

Geoff Nielson

What does what does that mean for? Yeah, you described earlier enterprise organizations as being kind of slow and lumbering. And, you know, I think, you know, that the two of us and many people listening to this know that there's an awful lot of slow, lumbering enterprises out there that are kind of burdened by legacy systems and processes that are, you know, customer or patient or student or citizen facing that are just really cumbersome and slow.

00;36;31;28 - 00;36;53;05

Geoff Nielson

Oh, it is this wave of technology going to make the extinct? Is it going to force them to adapt? You know what? What's kind of your advice for organizations like this to get to make sure that they're not, you know, the losers of the future and are instead the winners?

00;36;53;08 - 00;37;09;14

Jeremiah Owyang

It's a big question. So some of those organizations, if they're government, there's no competition, right? There's no I only have one government where I live and I can't choose a different one. There's no capitalism around that. It's just there's one government. There's one DMV. Like, I don't have a choice so they can go at the pace that they want.

00;37;09;16 - 00;37;28;24

Jeremiah Owyang

And it's just you can't stop that. When it comes to, like, health care, that sometimes we have choices. Not always. Sometimes we're locked in. And, you know, banks tend to be slow as well. And in some cases, it's good that they are slow because they're keeping important information or making life changing choices. They got to be careful and cautious and reduce risk.

00;37;28;27 - 00;37;50;09

Jeremiah Owyang

And I'm I'm okay with that. But there's other industries where we will see AI competitors emerge and they will be a direct threat if they don't move quickly. In fact, even in the enterprise technology space, the SAS companies, traditional SAS companies box. Let's talk about box, for example. That's a rather large traditional enterprise company that lives near me.

00;37;50;09 - 00;38;11;05

Jeremiah Owyang

I live near the office and, the CEO, Aaron Levy Levy, is focused on AI first, even though his company is like over 20 years. Right. So you can see they're trying to change that the culture as fast as possible. And he's talking about that constantly on LinkedIn. So the tech companies in traditional they're changing as fast as possible.

00;38;11;05 - 00;38;28;02

Jeremiah Owyang

And the other industries like consumer auto, they're going to be the second movers hospitality. And then the the laggards will be finance and health care and then government. And that's a standard rollout in adoption that I've been tracking in enterprise. And I don't expect that to change anytime soon.

00;38;28;05 - 00;38;46;20

Geoff Nielson

So with that in mind, you know, I'm curious on your perspective because you probably have a more, you know, inside view than most. The what you've described in some cases can be like really, done with a lot of integrity, and in some cases it can be an example of, you know, what you've probably heard is described as eye washing.

00;38;46;23 - 00;39;00;29

Geoff Nielson

Right? And just like trying to slap an eye label on everything, to what degree are you seeing either and, you know, do you have any tools and tricks for being able to distinguish one from the other?

00;39;01;01 - 00;39;27;06

Jeremiah Owyang

Yes. So I review 100 applicants per week to my event Lama lounge. That's average. And I'm reviewing dozens of companies that are startups that apply to demo. And then literally as I'm driving or an Uber or in a self-driving car, I see the billboards here in Silicon Valley of the large tech companies that are eye washing, and it's very obvious when you visit their website they they've added GPT so you can have a natural language process with their with their data.

00;39;27;08 - 00;39;55;10

Jeremiah Owyang

It's really not impressive and innovative at all. So you can tell pretty fast, like who has something that is just a AI wrapper versus somebody who's integrating like AI native company, so I can spot it most of the time. But that's my job, right? Is to filter that out. I wouldn't say I have any specific skills, it's just that I've seen so many patterns I can tell, on who's doing that.

00;39;55;12 - 00;40;08;16

Geoff Nielson

Right. And then the flip side of that is, you know, you mentioned there's an awful lot of CEOs and leaders out there who, you know, are saying something like, well, I don't run a hospital anymore. I run a tech company. I don't want a car company. I run a tech company.

00;40;08;16 - 00;40;09;00

Jeremiah Owyang

Yeah.

00;40;09;02 - 00;40;16;26

Geoff Nielson

Yeah. Is that a good thing? Is it, you know, a mix thing? Is it sometimes a good thing? What? What's your reaction to that?

00;40;16;28 - 00;40;39;26

Jeremiah Owyang

Well, they're running a tech enabled business. It's they're really not a tech company at its core. And and they should be more realistic on that. But to be tech first obviously is wonderful. But don't lose track of who your end customer is. Right. So over so right now we're in this the hype of AI where everybody's slapping AI and agent on everything.

00;40;39;28 - 00;41;03;15

Jeremiah Owyang

There will be a point where it just becomes noise and we return back to a customer business obsession with. And then I would just be expected there to provide personalized experiences or forecast what's going to be needed or improve operations. But we're still a period away from that happening. CEOs are talking more and more, though, to your question about AI, and you can read that in the transcripts from the annual meetings.

00;41;03;18 - 00;41;20;08

Jeremiah Owyang

So they know they have to talk about it. Whether or not they're actually doing something is a whole nother question. Right? I think with the enterprise is one of the biggest challenges that they have is that they do have a great integration with AI. You should have cleaned up data and in most cases their data is already is a big mess.

00;41;20;08 - 00;41;39;01

Jeremiah Owyang

It's fragmented, there's multiple copies, there's erroneous information. They have multiple customer records. The company's so big. It's the data is not consolidated. So it's hard to provide a great user customer experience. B2C or B2B is a corporation using AI if the data is already a jumble.

00;41;39;03 - 00;41;57;20

Geoff Nielson

Yeah. Well, and you know, the depressing thing is there's no unless you have a silver bullet. I have yet to see a silver bullet for cleaning up data. Right. Like it? It can be done, but it's not like, yeah, we're going to have that clean data for you next week, right. Like it? It takes, you know, a fairly large left to get, you know, an enterprises data in order.

00;41;57;22 - 00;42;06;10

Jeremiah Owyang

Yeah. And we'll see AI platforms try to solve that for them and then also fill in, missing records with synthetic data. Right. So that starting to happen now.

00;42;06;10 - 00;42;12;01

Geoff Nielson

Yeah. So are you expecting to see, like, a leapfrog, kind of capability in that space?

00;42;12;03 - 00;42;18;23

Jeremiah Owyang

I'm operating at startup Silicon Valley strength, speed. So to me, the corporations just seem very slow.

00;42;18;25 - 00;42;39;10

Geoff Nielson

Yeah, yeah. Make sense? What's, you know, talking about these CEOs or with them, you know, do you have any specific advice for business leaders or for CEOs who are looking at adopting AI or are trying to get into this, this game and build these capabilities in some capacity?

00;42;39;12 - 00;43;00;06

Jeremiah Owyang

Yes. Obviously they should be using these tools personally. And there's been numerous occasions where they're not touching it and they don't understand the power. So they definitely need to activate that. We've referenced how Aaron Levy has been AI first, and he's trying the tools and he's encouraging people to try things and that's going to be critical.

00;43;00;08 - 00;43;19;21

Jeremiah Owyang

I see companies doing I see the largest companies setting up an AI center of excellence. Often it's propped up by one of the largest, you know, the large consulting firms selling million dollar contracts to set up this program management office. So that can sometimes speed things along from a central group and get everybody on the same, literally on the same page within the organization.

00;43;19;24 - 00;43;40;21

Jeremiah Owyang

But then it should be distributed through the organization where each business function is using AI at a rapid pace. Now, if you don't enable a business unit to do that, unless you have very strong firewalls, they're going to adopt the open source, tools right away. That's why we are seeing growth of enterprise open source tools. And so that's something you need to do.

00;43;40;21 - 00;43;51;23

Jeremiah Owyang

So the CIO needs to move very fast and enable AI within the enterprise. Or they're going to have a bigger mess on hand and have to roll and wrap everything up into a centralized bit.

00;43;51;26 - 00;44;10;05

Geoff Nielson

So so yeah, when we talk about the CIO, when we talk about this center of excellence and just how we scale this up, one of the one of the pieces that I keep coming back to, and you mentioned it earlier, Jeremiah, is the notion of skills. And you know, how we can make sure that we've got the right skills to do this.

00;44;10;08 - 00;44;39;15

Geoff Nielson

You know, in any organization. Now, you mentioned specifically and it's been fairly topical these days about, you know, some of these, you know, multi-million dollars to hundreds of million dollar pay packages for, you know, AI leaders and AI engineers. When you think about the role of skills and how organizations can be better, you know, positioned for this, is it building the skills of existing staff or upskilling them for AI?

00;44;39;15 - 00;44;46;20

Geoff Nielson

Is it bringing in AI superstars? Is it a combination of each? Like how do you structure that problem in your mind?

00;44;46;22 - 00;45;09;26

Jeremiah Owyang

It's going to vary by company and how attractive those companies are to being forward looking. Obviously the best AI talent is going two directions when they join a hyperscaler like Meta's offering those big packages, or they start their own company, that's like. That's like two routes. They may after that, join a traditional tech company, well paid, you know, have a big program to do those things.

00;45;09;28 - 00;45;33;22

Jeremiah Owyang

And lots of compute credits. Fourth choice would be joining a traditional enterprise. It's just going to be less attractive. But that's why we're seeing these management consulting firms come into these and offer those solutions. I heard there's one management consulting firm. It's a name you would know. They're doing $1 billion in. Consulting, AI consulting per year already.

00;45;33;25 - 00;46;08;10

Jeremiah Owyang

It's it's incredible. Right. Because a lot of the knowledge that they're getting you can get from AI, unless it's customer interviews or employee interviews and aggregating that I'm sure they're doing that, of course. So companies are just typically not skilled yet, to be at the front of the market. But that's okay. One of the the differences with this market versus prior is the no code tools like lovable or cursor or windsurf where business owners, business, professionals within the enterprise can start to create their own apps.

00;46;08;13 - 00;46;35;06

Jeremiah Owyang

And so having classes, having courses in curriculum to teach employees to build apps, within a safe sandbox in the enterprise would be one advantage. You're not going to be able to hire the top programmers. So you should teach your existing business leaders and their teams how to use no code to build apps in the enterprise. I think that's an opportunity right.

00;46;35;08 - 00;46;55;00

Geoff Nielson

And and, you know, I love seeing examples of that citizen developer model and what it can unlock for organizations. You did say something that I wanted to come back to, though. You talked about the management consultancies and, you know, being able to spin up $1 billion practice. And I, I know I picked up maybe like, a note of skepticism in your voice about that model.

00;46;55;04 - 00;47;10;19

Geoff Nielson

If you're, if you're a business leader looking to get off the ground in AI, what would you be recommending? Spending, you know, $1 million with one of the big management consultancies to do that? Or is there a better or a different way?

00;47;10;21 - 00;47;27;21

Jeremiah Owyang

It's always best if you can do it yourself, but many of them are not capable to do it themselves or they cannot navigate the internal political turmoil. So you have to hire experts to come in and do it. Those external experts, those management consultants, they've done it at many other companies, and so they know how to do that.

00;47;27;28 - 00;47;31;16

Jeremiah Owyang

It's just a very expensive proposition to do change management.

00;47;31;19 - 00;47;32;12

Geoff Nielson

Yeah.

00;47;32;15 - 00;47;55;14

Jeremiah Owyang

The ideal sense is that your culture inside of your big company is ready for change management and can have innovation mindset. It's just not built into a company with 100,000 employees and ten levels, 20 levels between the CEO and the front line workers talking to customers, it's just it's just not possible in some cases. So you have to bring in those experts to help you.

00;47;55;16 - 00;48;17;06

Jeremiah Owyang

It's just surprising to me that, I mean, you can use AI to actually do a lot of those services now, but big corporations feel comfortable hiring, teams to do that and to spend time with them. That physical connection is just seems opposite to how people operate in Silicon Valley. The AI first mindset with the startups you don't hire people first, you use AI first.

00;48;17;09 - 00;48;25;15

Jeremiah Owyang

So that's why I use sense that skepticism from me, because I'm seeing something very different on the front edge right here in Silicon Valley.

00;48;25;17 - 00;48;43;02

Geoff Nielson

It makes it makes complete sense to me. And it's it's funny, if not sad to me about the fact that it's like, you know, if you're trying to do this in your organization, it seems like my sensors and and, you know, we have histories in similar industries. It's like, yeah, you can pull an AI and I can tell you the answer.

00;48;43;04 - 00;48;54;09

Geoff Nielson

But once your organization reaches a certain size, like having the answer is not even the hard part. It's like, you know, trying to push the boulder up the hill just to get anything done. And that's where political alignment.

00;48;54;09 - 00;49;12;10

Jeremiah Owyang

Right. Stakeholder management. Yeah. That's stuff that I can do. So I think that goes back to your prior question is like, what skills do I do to train my child? Right. So we talked about leadership, community, empathy. Those are critical in large institutions. That's probably the most important skill and the skill that I cannot do.

00;49;12;13 - 00;49;41;19

Geoff Nielson

Right. Right. There's a question, Jeremiah. I ask all the guests who talk, who come and talk with me on the show, which is, you know, I'm sure you hear about all sorts of use cases. You know, there's all sorts of, you know, prognoses about what's coming down the pipeline. Is there anything right now kind of in the zeitgeist around tech that you just think is kind of BS or overblown that people should be focusing less on right now?

00;49;41;21 - 00;50;09;12

Jeremiah Owyang

No. I think the market's focused on the things that, matter right now. I don't see a crazy amount of fluff, too. There's just too many startups doing the same exact problem and that that's an issue. But that will go away over time. But I think the industries focused on business problems, like most of the projects that are coming across my desk, they're focused on real problems to solve the challenges that there's too many players in the market, or they've chosen a market that's too small of a market cap.

00;50;09;12 - 00;50;32;18

Jeremiah Owyang

So like, that's an issue. But I don't think there's too much fluff at this time. I would give a warning, though, is that startups need to follow the, the principles that I shared before. You need to have an equal amount of focus on your business strategy in addition to your technical strategy. Your technical moat is not enough.

00;50;32;21 - 00;50;41;18

Jeremiah Owyang

It is really not enough. You must focus on your go to market and your business strategies with the network effects and viral effects. Or frankly, you're not going to survive.

00;50;41;20 - 00;50;53;14

Geoff Nielson

Yeah, that. And then that was a really impactful, you know, statement to me. And my my sense is that technical mode thing. It's not going to change anytime soon. Right. Like if anything it feels like it's going to continue shrinking versus going to get shorter.

00;50;53;14 - 00;50;55;01

Jeremiah Owyang

Yeah. It'll it'll get thinner.

00;50;55;08 - 00;51;13;19

Geoff Nielson

Yeah. There's one more piece that I've heard you talk about in the past that we haven't talked about today, which is, AI influencers and basically AI, as you know, kind of a marketing tool or for human interaction. What's your what do you see now and what's your outlook there?

00;51;13;22 - 00;51;23;26

Jeremiah Owyang

Sure. When you use mean influencers, do you mean like, like the AI influencers on Instagram? Is that what you mean? Or like AI changing the way we make decisions?

00;51;23;28 - 00;51;36;02

Geoff Nielson

What I mean is more the former or the ability of AI to impact, you know, call it buying habits or as you know, a marketing channel, let's say.

00;51;36;04 - 00;51;58;21

Jeremiah Owyang

Okay. Got it. Yes. All right. So let's break down the logic. And I publish about this. In 2013 I got picked up in VentureBeat. I was pretty early to publish, thinking about how the way we make decisions, whether it's B2C or B2B, is going to change. So right now, the decision process is we think about a problem. We may not know what the problem is, and then we do some Google searches.

00;51;58;21 - 00;52;15;12

Jeremiah Owyang

There's ten blue links. We go to different websites. The answer is buried at the bottom of the page. We pick up hitchhiker retargeting ads. It sucks. The information we get in one place, then they want us to contact their sales team. They get you through the pricing and then negotiation, or we get to shop in different locations.

00;52;15;12 - 00;52;39;07

Jeremiah Owyang

If it's B2C, you have to you're bounced around, do all these things on the internet to make a decision. And it's not very efficient. Now with AI agents, the AI agent will be going to those different websites collecting that information and bringing it back to you and making suggestions. And then to what? This means that you don't have to visit those websites or apps, and then two, it'll complete actions for you.

00;52;39;10 - 00;52;57;10

Jeremiah Owyang

It'll it'll centralize all that information for you in the way that you want in the medium that you want text, video or audio. And when you want. So maybe you're listening to this podcast now, but you only want it in written form, but you only want it in 140 characters, and you want it at night. So it can do that.

00;52;57;10 - 00;53;11;05

Jeremiah Owyang

You don't have to actually listen to the podcast with an AI agent. It'll do all those things for you. Or if I say, I'm going to do a speech on a webinar, you don't have to attend my webinar. You can send your AI agent to attend, get on the notes and bring it back to you. You want to buy a new car?

00;53;11;06 - 00;53;33;16

Jeremiah Owyang

You can send your AI agent, visit all the car sites, get that information back, do pricing negotiation. If you want to buy something, you can have your AI agent be a, your representative and purchase things for you. We bet on Sky fire dot x, y, z to do agent transactions financial transactions. So this means that the AI agent will be influencing how we make decisions.

00;53;33;18 - 00;54;01;21

Jeremiah Owyang

It will complete the actions and it will recommend products. So search engine optimization doesn't matter as much. Google doesn't matter as much. We will be influenced by AI to make those decisions. And that is a significant change, right? That destroys the media model that destroys traditional advertising or e-commerce changes. Many companies exist by the number of humans visiting their website, CPM that changes if agents are the most dominant entity.

00;54;01;23 - 00;54;24;23

Jeremiah Owyang

In fact, for some consumer sites of AI agents visiting, do you even need a brand or identity? Right? You just don't need that layer because the data layer and the presentation layer are decoupling, and AI agents just pull the data back and reassemble it on a third location. So the way that we're going to make information, the way that we collect information, excuse me, the way we make decisions, is going to be radically changed by agents.

00;54;24;23 - 00;54;37;00

Jeremiah Owyang

They'll be influencing us B2C and B2B. And I think that's a big change that that marketers go to market product managers, enterprises, fortune 500. They're not prepared for.

00;54;37;03 - 00;55;03;13

Geoff Nielson

Right. And which is super interesting and has all sorts of, you know, interesting knock on implications. But but one of them and the one that I've talked about before and I'm, you know, thinking about is if this happens. And by the way, I'm pretty sure it's already happening is that marketers more and more are going to say shit like, how do I make sure that I'm influencing the AI agents and the AI tools that are making exactly inundations?

00;55;03;15 - 00;55;25;19

Geoff Nielson

And how how long is it before some of these tools are actually earning revenue from generating recommendations from these brands? Right. And suddenly, you know, you're yeah, that's right. Your agent is telling you, like, you know, you seem you know, you seem like you could relax and have a Coke right now or something like. And what's this? What does that mean in terms of the ecosystem.

00;55;25;19 - 00;55;31;29

Geoff Nielson

And what does that mean for us in terms of people using these supposedly agnostic tools?

00;55;32;02 - 00;55;55;24

Jeremiah Owyang

That's a great question. So the biggest question is who does the AI agent serve? Now if you're not paying for it, then, hey, if you're it's not serving you. So we're going to see a number of business models. Premium sponsored free Amazon offers a free shopping agent called Rufus. Who does it serve? It's free whether you know it.

00;55;56;00 - 00;56;13;07

Jeremiah Owyang

There's multiple stakeholders that are served right. But if I'm paying for an AI agent and I'm the only one that's paying for them, it's serving me. Should be ad free. We already know that perplexity there. Search, search models. So it's not really an agent, but they have already said they want to have sponsored sentences and answers.

00;56;13;07 - 00;56;39;04

Jeremiah Owyang

Right. So that's going to happen. I expect to see e-commerce embedded into cloud and GPT two in the very near future. Right. That should happen. There's lots of there's other things, other after effects that happen to go to market team. Like every CRM needs a new field with the associated agent for every customer, B2C or B2B, because you have multiple agents that are representing the human right that's going to be happening.

00;56;39;06 - 00;56;57;22

Jeremiah Owyang

Every marketer needs to launch sell side agents to converse with the buyer side agent, so they have dialog and negotiate. All right. We might need to see a new data file or new data type on your CRM system that just shoots out proprietary data that you want the agents to scrape. In fact, you may sell that data as well.

00;56;57;22 - 00;57;08;18

Jeremiah Owyang

It might be a new business model unlocked by media companies that. So there's lots of permutations here on the new business strategies that have to come for that. And that's actually a speech I give to marketers and CMS.

00;57;08;20 - 00;57;34;09

Geoff Nielson

Thanks. So, so one of the, one of the, talking points recently, or one of the concerns in the space is that as we move to this world, you described where SEO matters last, Google is less relevant. Going to web pages is less relevant that I actually, in some ways, like actually kills the internet or the traditional web because that that whole ecosystem kind of disappears.

00;57;34;09 - 00;57;44;21

Geoff Nielson

And that's the ecosystem that's been feeding AI this whole time. Is that on your radar? Is that a legitimate concern? And what are some of the issues if we keep going down that road?

00;57;44;23 - 00;58;02;13

Jeremiah Owyang

And don't forget apps, enterprise apps like do you like to go and expense apps to do your expense report? I don't know anybody who does. Do you like going to HR software? Do you like managing your benefits like do you like filling out? Do you like going to slack? Do you like to fill out your TPS report? Now you don't have to.

00;58;02;16 - 00;58;22;12

Jeremiah Owyang

Your AI agent will do that for you. And one interface. So how many apps do we really need? And you already know my answer is equivalent to the number of email accounts you currently manage. That's my general thesis. Answer to that. So yes. Now we still need websites. We still need new net new data. We still need net new information.

00;58;22;15 - 00;58;43;21

Jeremiah Owyang

So that will continue. It's just like we need to prepare that the most common visitor will be the representative AI agent, not a human. You need to prepare for zero click searches when people search on perplexity or clod or GPT three, all the answers come to them. They don't click on anything. They never need to click on anything ever again.

00;58;43;23 - 00;59;03;23

Jeremiah Owyang

Right? That information has to come to them and be regurgitated in one space. Now, one caveat amazing websites that are news and a luxury and experiences and sports and social with your family and friends that you actually want to talk to you. Yes, you will lean in and you will use those apps. You will still type or talk or video like you still want to do those things.

00;59;03;26 - 00;59;13;25

Jeremiah Owyang

But for all the other stuff that we don't want to do, expense reports and, you know, booking a flight, that's very painful, actually. You send your agent to do those things for you.

00;59;13;28 - 00;59;36;02

Geoff Nielson

Right? And it's yeah, I mean, I was laughing to myself as you were talking about, you know, filling out expense reports and some of these, you know, HR apps and yeah, I've got I'm sure everybody has the same battle scars around those. So it sounds almost utopian to me. So, I love that notion. Hey, Jeremiah, just before we go, I wanted to ask if there's any sort of final thoughts.

00;59;36;02 - 00;59;41;18

Geoff Nielson

You wanted to leave our listeners with either human or AI today,

00;59;41;20 - 01;00;05;28

Jeremiah Owyang

And there are AI listeners, right? They're grabbing the information. They're pre-training their models on it. The agents are grabbing information. Right? Like so. We definitely have non-human listeners today. So you're all welcome. And to the human listeners, what I'm seeing here on the frontlines in Silicon Valley is just incredible speed. The key things I'll just repeat is the AI first mindset.

01;00;05;28 - 01;00;24;19

Jeremiah Owyang

Using AI before you do anything else is the most common thing, even with your like chores around the house, you don't know how to fix the washer, the dryer, pull out your eye and turn on the video mode and do a live chat. See if you can troubleshoot. I did that with my microwave yesterday. My VCR finally doesn't blink 12 thanks to AI.

01;00;24;21 - 01;00;53;11

Jeremiah Owyang

So understanding that, I spend two hours on average per day listening to AI podcasts to stay on top of the news. On average, I enjoy it. I want to learn it, and it's changing so fast. So I encourage you to figure out how do you consume a lot of information about what's constantly changing in this space and if you're working at a large corporation, really try to enable a segment of your company to use the no code tools or to be AI first.

01;00;53;11 - 01;01;11;14

Jeremiah Owyang

And really lean in and try to adopt these tools as fast as possible. And if you're at a startup and you're building a startup, maybe serving enterprises, please don't forget your business strategies are just as important as your technical strategy. That is one of the most important things that we see companies messing up on.

01;01;11;17 - 01;01;17;13

Geoff Nielson

Amazing. I want to say a big thanks to you, Jeremiah for joining. This have been a really, really interesting conversation. I appreciate your insights.

01;01;17;16 - 01;01;18;15

Jeremiah Owyang

Thank you for having me.