GlobalEdgeTalk

Expert Networks in the Age of AI: Transformation or Replacement?

• Alex Romanovich

Share episode

Send us a text

What happens when specialized human expertise meets artificial intelligence? That's the fascinating question at the heart of my conversation with Alex Khomyakov, founder of Productera and expert in the knowledge economy.

For years, expert networks have connected investors and researchers with subject matter specialists who possess real-time insights not yet captured in public sources. While AI and search engines can tell you what happened yesterday, these networks connect you with people who know what's happening now. The distinction is crucial for those making million-dollar investment decisions.

But beneath the polished surface of these premium services lies a surprising reality: an operational infrastructure still heavily dependent on manual processes, spreadsheets, and institutional memory. As Alex reveals, approximately 80% of labor in expert networks happens behind the scenes, managing everything from expert sourcing and compliance to scheduling and transcription.

This is where AI enters the picture—not as a replacement for human expertise but as a powerful augmentation tool. AI promises to transform expert networks by improving matchmaking between clients and experts, breaking down language barriers through real-time translation, and offering scheduling flexibility across time zones. These innovations could democratize access to specialized knowledge globally, making expertise available regardless of language or location.

For tech entrepreneurs and product developers, the opportunity lies not in creating flashy front-end solutions but in addressing the operational challenges beneath the surface. Alex wisely notes, "The value of investment insight is proportional to how fast you can get it." Those who can leverage AI to increase speed and efficiency while maintaining the human element will define the future of this industry.

Ready to learn more about how AI and human expertise are converging to create new possibilities in the knowledge economy? Listen to our conversation for insights that might change your thoughts about accessing specialized knowledge in the AI era.

Support the show

Alex Romanovich:

Hi, this is Alex Romanovich and welcome to Global Edge Talk. Today, we have Alex Khomyakov with us directly from Lisbon, Portugal, one of my favorite places. I'm sure yours as well. Alex right, welcome to our studio.

Alex Khomyakov:

Thank you for having me.

Alex Romanovich:

Wonderful. Alex and I met, I would say, about six months to 12 months ago, and it was really amazing to talk about a variety of different things, including productization, including software development, artificial intelligence obviously who doesn't talk about that right now? And on a very important topic, which is expert systems, and Alex is an expert in expert systems. He's built some, and we will talk about that as a topic among many other topics as well. Alex, please say a few words by yourself and your background.

Alex Khomyakov:

Yeah, first of all, the industry is called expert networks. It's kind of systems, but a common name for that would be expert networks. Okay, apologies, no worries. No worries about that. I've been running a software development company called Product Terra for the past nine years now, and out of which five last years we've been developing solutions exclusively in the knowledge industry or expert networks, built beautiful products, been through several exits with our clients and still more to come.

Alex Romanovich:

Amazing Product Terra. I love the name. It kind of spells the productization and product packaging and I believe that's part of your background as well with some of the larger organizations in terms of product management, product development. So we'll talk more about that. And then you also mentioned expert network economy when you and I talked yeah, what exactly does that mean, expert network economy? I'm kind of intrigued by that.

Alex Khomyakov:

Well, I would rather call it knowledge economy.

Alex Khomyakov:

In a sense, it is an easy way for us, as human beings, to tap into very niche knowledge which is very up-to-date. And how I was drew to this economy, to knowledge economy, I stumbled upon expert networks and I started to do the research. What are they about? And main users and that's changing, by the way. We'll be talking about it soon but main users are financial firms, private equity investment firms, analysts, analysts and they're using expert networks as part of their research process to get the latest knowledge about the subject that they're researching. So think of it as everything that is in the web or everything that AI knows up till this moment is actually that's been happening in the past. So this is the past knowledge. What's happening now is available only to people who actually hands on to the subject that you're researching. So expert networks opens the door to these experts so that people who are interested in this knowledge can tap into this via phone calls and interview them and ask those smart questions and get up-to-date knowledge so they can make their investment decisions better.

Alex Romanovich:

Interesting. So it's almost like a cloud of expertise available to you, someone who's seeking expertise. It could be a company, it could be an individual, but let me ask you, why do you think I mean? You mentioned to me also that the industry of expert networks segment itself has been kind of slow to innovate, despite being so information heavy and service oriented. And, of course, now we have artificial intelligence. How does all of this now work together?

Alex Khomyakov:

Well, to answer this question, first of all, we need to understand how this economy and expert network in particular, expert network operates behind the scene. So when we talk about expert network infrastructure, we mean everything that has to happen between the moment a client says we need to speak to an expert and when the insight from the conversation is actually delivered. So what does it mean? It includes expert sourcing, vetting, compliance, clearance, scheduling, call logistics, transcription, billing, feedback loops, and what's interesting is that none of that is client-facing. But what I've discovered over in the working industry that's where 80% of the labor happens in this business.

Alex Khomyakov:

So the problem that we see that most of the infrastructure of expert networks is still manual. You'll see teams tracking projects in Excel, using shared inboxes to manage outreach campaigns, relying on recruiters' institutional memory to avoid duplicate sourcing. So it's highly reliant on people and very brittle at scale. In short, I see that this infrastructure is broken in a sense and it was never designed as infrastructure. So that's an interesting part. So that's kind of the infrastructure side. Now, when we talk about inefficiencies we talked about, you know, all the manual process, about how the process is very manual. We can probably drill it down to three main steps where we see the most potential for the technology Sourcing, knowledge capture and compliance and that's where I see the biggest shift in the industry and that's where we already built several products successful products in the past, and that's where you see most of things happening right now. Got it.

Alex Romanovich:

You know it's interesting because I used to be a World Council member for GLG, for Gerson Lerman Group.

Alex Khomyakov:

You probably know them well.

Alex Romanovich:

And you know, every now and then I would get a call or get an email saying Alex, a hedge fund is interested to talk to you about EPAM systems. Or you know, alex, a hedge fund is interested to talk to you about, you know, advertising technology or whatever else, whatever else they were looking for. You know, it always fascinated me that, the concept, the fact that in half hour they could talk to an expert and probably make some kind of a multi-million dollar investment decision or aggregation of expertise, and so forth. But now let's enter the world of AI, artificial intelligence, right, which is advancing so rapidly that it's making our heads spin. And all of a sudden you can have an expert Alex, an expert Alex, an expert Bob, and an expert Chad, gpt, or expert Anthropic, or expert Gemini, you know, and so forth.

Alex Romanovich:

How does that either augment the industry, the business? Is it going to absolutely kill it, or is it going to, on the contrary, is it going to make it a lot more efficient? And still, the human expertise is going to be extremely important and maybe AI will now enhance it, whether it's going to be through LLMs and SLMs and different models, or is it going to be through aggregation of expertise, or do you see somebody like GLG, for example, creating their own huge base of knowledge using artificial intelligence?

Alex Khomyakov:

Yeah, that's a good point, and I think GLG is the biggest player in the market, right? They have tremendous resources. So they will probably build something with AI, if not yet. But back to your point, I think it's all going to be somehow connected. Let me break it down to several points. So, first of all, it is still an art of expert networks up to today to match right experts with the right project brief, so the matchmaking game. So it's still done manually in most of the expert networks. And the reason why it's done manually? Because you have to have lots of background, knowledge and expertise, understanding all the nuances of the client, all the nuances of the industry, particular project. So it's all done manually. But I believe it's going to change. I believe the AI will play a big role in matchmaking, just because it can handle all this contextual cloud of different inputs. So this is one aspect. Another aspect, one that I mentioned before, right, so AI, as a knowledge source, knows everything that's been in the past. It doesn't know exactly what's happening now and sometimes the subjects of this conversation is very niche and it may not be publicly available, even though it's not like material and public information for the analyst. But still it's quite close information and it's not easily searchable and available to the.

Alex Khomyakov:

Another point is, which is also very interesting, is expert networks as a business have been really popular in call it Western world right, northern America and Europe. And the reason why it's been so popular? Because most of people there speak English. I mean, even in Europe, most of you know experts would be okay speaking English. What's happening now is that? Okay, I have a great expert in India that only speaks Hindi, or I have a great experts in China that only speaks Mandarin, or you know that doesn't matter. So in the past, and you know, in most cases today, to get a hold of this expert you will need to have a third body on the call, a translator, and that brings you another level of complexity to arrange this call, to schedule it, to find the right person, the right translator and not to miss important things in the translation. So what we've been seeing in AI in the recent presentations of Google, apple they're doing live translation. So what we've been seeing in AI in the recent presentations of Google, apple they're doing live translation. So I think AI will play a big role in that.

Alex Khomyakov:

And, finally, ai can actually interview people. Scheduling is a big part of it. So imagine you have a great expert who is in London and you are in West Coast in the US, so you have only a few hours overlap that you can actually chat. I'd say scheduling dense again to find the right slot on everybody's calendars to talk. But imagine you have an AI that can be available 24 multiple languages at the same time, right? So you're kind of killing two problems at the same time and then talk to this expert whenever expert is available. So if you're available now, fine, press a button. Here we go, we're talking now. So that's where I see you know things are happening with AI. So it's not like AI is going to replace the knowledge economy driven by experts, but I think it's augmentation, augmentation step.

Alex Romanovich:

I tend to agree with you because it'll be a while. I mean, it may happen very quickly, but it'll be a while until the expertise in any particular topic is going to be aggregated, right, Captured, aggregated, processed. I mean, the processing of that knowledge is much faster now because you have AI. The capturing and distribution of that knowledge might be better, might be faster as well, depending on how each particular company is going to use AI to distribute this knowledge and how they're going to monetize it. You know, and so forth and so on, and maybe the monetization of it is going to be a little bit different than the productization of it, right? So if GLG before they were distributing this information almost in semi-manual type of a fashion, gathering information, I mean, I still have platforms similar to GLG reaching out to me and saying, hey, would you be available for a 15-minute call? And I'm wondering what can you possibly accomplish in 15 minutes? Right? What can you possibly accomplish in 15 minutes? Yeah, what can you possibly share in 15 minutes? But maybe they're only looking for the customer may be looking for a simple answer yes or no or whatever just a simple conversation. But the monetization of it has also been somewhat partitioned in the sense that if I was able to charge $300 an hour, for example, or $200 an hour for a 45-minute conversation at GLG, and that was like maybe 10, 15 years ago, now we're looking at 15 minutes for 40 bucks, right, 15 minutes for 30 bucks or something like that.

Alex Romanovich:

So the question then becomes the expertise distribution is one thing, automation of the process is another thing, but the monetization of it, the value of it right, the value of knowledge, the value of expertise is also being driven down significantly. And then the question then becomes and it's also very targeted, very focused, and I think that's what AI is going to be able to do is to focus it on the particular topic. Don't you think that it will be a lot easier than to say look, I'm only interested in a question related to derivatives for the London Stock Exchange in this particular sector, right, and I don't really want to know anything else. And the way I'm going to access it is either by talking to you, alex, or by simply going to the database, or simply, you know, using ai interface similar to chat gpt could be a glg gpt or whatever and asking a question, getting an answer back and simply using a subscription model to get that, what do you? You think?

Alex Khomyakov:

Yeah, I mean, that's not a novel approach, right? One of the products that Product, terra was hired to build and it was a big success called Stream. It's a transcript library of expert calls. So the point was exactly that right, Like why would I have to spend my time and money on driving the expert call myself if there is a library out there where I can just query the question and get the answer? So now the product is known as AlphaSense Expert Insights and it's powered by AlphaSense AI engine. But that's not the point. The point is, like you said, so if you have a very narrow request, you would probably be good with such solution.

Alex Khomyakov:

From the technical point of view, I think the value is still there for the live calls, for the long conversations, but it's very tricky. So what I also learned over the years being in industry that not all analysts good in interviewing. It's a skill itself. You've been running this podcast for a while. I have my own podcast.

Alex Khomyakov:

We learn interviewing people and asking questions and you're not perfect from day one. You evolve it. So it's a separate skill, like journalism, and, as you said, sometimes those calls may be less expensive, more expensive, sometimes it may cost a few thousand dollars to the firm. You're always risking getting on the expensive call with an expert who has really good insights, but you're just not asking right questions because you're really focused on things that you. Okay, I got this. Okay, here we go, let's move on. But in reality, you actually had an expert on a call that could expand the horizon of investment ideas or, you know, highlight certain risks in your thesis that you wouldn't have thought about. So, again, I think there is a use case for every type of analysis, interaction with the knowledge database, and I think all of them will evolve over time with, one way or another, having AI there.

Alex Romanovich:

You also brought up a very interesting point about the democracy of the democracy, the democratization of expert networks, because of the barriers that are being broken down by translation live translations, almost immediate translations inside of the database, right where you can now. The barriers that are being broken down by translation live translations, almost immediate translations inside of the database, right where you can now have the documents available through AI in all kinds of languages, and so forth and so on. Cultural adaptation what have you Now? If you look at the entire global infrastructure of tech providers, you know software developers, product developers, experts, people who have some kind of expertise. What is your advice for them? To either build it, or how to build it, or how to participate, how to become a part of the network that may be available out there. What should an individual, what should a person do or have to be involved to get involved?

Alex Khomyakov:

That's a really good question. I think that may be applicable to other industries as well, but in particular to this one is don't get distracted by the polished surface of the expert networks business. Study the workflows that are underneath Because, like as I said before, from outside, expert networks look like you know white glove service, smooth calls, they're helpful client managers, you have a sense of premium access, but under the hood you have operational mess, spreadsheets, unstructured data, tribal knowledge, compliance bottlenecks, and I think that's where the real pain leaves and that's where the opportunity is for the builders. The real pain leaves and that's where the opportunity is for the builders. So if I were to talk to a tech founder or a B2B operator looking to break into this space, I would advise them to start asking questions like what are people still doing manually? Why do ops teams struggle doing each week? What do they struggle with doing each week? What gets deleted, duplicated or delayed? Because this business is also about speed.

Alex Khomyakov:

The investment insight is proportional. The value of investment insight is proportional to how fast you can get it. So the sooner you get the insight from this process and we talk about how lengthy this process is the higher chances that you will be on time with your investment decision. So I think that's where you can actually build leverage. So it could be sourcing engine, it could be compliance automation layer, it could be a co-logistics stack or something totally new. We never know, right Like with all the AI technology, the things that were not possible a month ago suddenly are possible today. But again, it won't be obvious unless you go deep under the surface and study the flows, got it, got it.

Alex Romanovich:

Fascinating topic. Alex, thank you so much for being with us. I'd love to you know in the future, I'd love to talk more about this topic and other topics, and it's exciting that we're going to see so many different advances, probably in the next three to five years, more so than we've ever seen in the past 10 to 15 or 20. So I'm actually excited to see this and to follow your success, to follow your steps into the world of not just expert networks, but in tech and artificial intelligence and so forth, and please say hello to Lisbon for me.

Alex Khomyakov:

I will. I will Thanks Alex for having me. It's been a pleasure.