Artificial intelligence is taking the world by storm.

The term was once used only by techies and gaming enthusiasts, but AI is now disrupting every industry on the planet. That goes for automobiles, education, and even stock market trading (though, for the record, this article was written by a human).

One of the most intriguing opportunities for AI is in the way it interacts with human beings. Known as conversational AI, this new field of technology powers Apple's Siri, Amazon's Alexa, and many other voice-to-text cognitive consumer devices that you've likely already come into contact with.

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Several interconnected glass windows, each depicting a conversation taking place

Image source: Getty Images.

Conversational AI technology is also progressing incredibly quickly. Companies like Artificial Solutions are already developing enterprise-grade platforms that can handle increasingly complex tasks, such as preparing sales quotations or answering customer questions. The nuances of natural human conversation make training the AI much more difficult than just serving as a vocal command prompt. And the demands of the enterprise are far greater than those of consumers.

Gartner predicts that by next year, people will have more daily conversations with chatbots than with their spouses. An Oracle report predicts that 80% of large companies will have fully implemented chatbots by the same time.

Artificial Solutions will be taking things a step further next month, as it prepares to become publicly traded. Soon to be listed on the Nasdaq First North stock exchange, the company will give investors a way to capitalize on the growth opportunity offered by conversational AI.

I recently got a chance to speak with Artificial Solutions CEO Lawrence Flynn. In our conversation, he described how the market for intelligent assistants is different for the enterprise than for consumers, how the company is modeling its go-to-market strategy, how data privacy regulations could actually be a big opportunity, and what "tipping point" individual investors should be aware of as the technology matures.

Our discussion is captured in the following video, with a full transcript provided below.

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Motley Fool Explorer Lead Advisor Simon Erickson: Hi everyone. I'm Motley Fool Explorer lead advisor Simon Erickson, and I'm joined by a very special guest this morning. Lawrence Flynn is the CEO of Artificial Solutions, which is a company that's a leader in conversational AI, for companies to better understand the needs of their customers. Lawrence is joining me from the United Kingdom. Good morning for us, but good afternoon for you, Lawrence. Thanks very much for joining me!

Artificial Solutions CEO Lawrence Flynn: Good afternoon to you, Simon. It's great to be here.

Simon Erickson: Lawrence, we'll talk a little bit more about your company in a minute. But let's start with the big news. We just had an announcement from Artificial Solutions yesterday that your company will soon be publicly listed and traded on the Nasdaq First North stock exchange. Can you start us up by telling us a little bit about this coming event and the transaction?

Lawrence Flynn: Yeah. This is great news for us, obviously part of our long-term journey and plan. We plan to become a publicly traded company. And as you correctly say, we put out a press release yesterday informing people that we will be entering the market, if everything goes according to plan and to timetable. We expect the first day of trading to be the 12th of March of this year. As you say, it's the Nasdaq First North market in Stockholm, being a Swedish-headquartered company. We're doing this as part of a reverse takeover of an existing company, which is a method that we've chosen to enter the exchange, which is rather tax-advantageous for some of our international shareholders.

So it's an exciting piece of news from us; we're really looking forward to it. It will be the second time that I've run a public company, and I think it's going to be a really good-news story for us, our customers and our shareholders, and our employees too. So yeah, we're very excited about it.

Simon Erickson: That's great. I'd like to double-click on that, that you mentioned about this being a reverse takeover. From the release it says this will be a reverse takeover of Indentive, which means it's already a publicly traded company [in Sweden]. They'll be changing their name to Artificial Solutions. Why did you choose this path instead of the more traditional IPO [initial public offering]?

Lawrence Flynn: Well, the truth was, we had both options in front of us, and, in fact, much of the preparation work is the same for an IPO as it is for a reverse takeover. It so happened that we identified Indentive as a suitable candidate for reverse takeover, and on closer examination, this was a better and more tax-efficient option for many of our larger investors, who are not Swedish nationals. So they get tax benefits from doing a reverse takeover, which they couldn't get if it was a regular IPO. So that's the reason we've gone this route.

Effectively, the transaction is a reverse takeover of Indentive, but it's a massive reverse takeover. We alone will end up with 97.75% of the shares. So, really, you can think of the transaction as a reverse into a shell, because the Indentive business will be dividended out to their own shareholders, and they'll continue their business elsewhere, on another market.

Simon Erickson: Certainly. And now, Lawrence, let's talk a little bit more about conversational AI. I know this is a hot topic, especially for people that like to follow technology. Just to set the framework for this, we've seen some research that says that 85% of people won't actually be talking to a human being in managing their relationship with a company, and that 80% of larger companies are planning to implement chatbots, or digital assistants, by 2020. That's just next year, so this is happening very quickly. A lot of our audience that's listening to this is probably already familiar with the Amazon Echo and [Alphabet's] Google Home and a lot of these consumer market assistants that are already out there.

And those run off a fairly simple rule-based system; sometimes they get things wrong, sometimes we even think that it's not as effective, or demanding, as it is in the enterprise. Your platform, Teneo, is not going after the consumer market initially; it's going after the enterprise. How is Teneo different than these consumer-branded digital assistants that we're already familiar with?

Lawrence Flynn: Yes, you're absolutely right. Our product is Teneo, and Teneo is a platform. So, one of the main differences between Alexa and Teneo, for instance, is that Alexa is kind of a thing, it is an artifact, it's something that you can talk to. Teneo is a platform that you might build something like Alexa with, OK? So if you are an enterprise, if you're a bank or insurance company or healthcare provider or a telco and you want to conduct your business with your customers, you might want to put a conversational interface between you and them in an automated way. So, instead of, for example, having a large call center handling people's queries, you might automate that through a chatbot. You might automate that through an intelligent assistant on a website, or on a mobile-phone app, might be speech-enabled.

And you would have to build something that is very unique to your use case, because the way in which one telco handles its mobile-phone customers is different to the way that another one would, and they all have different tariffs and different services and different rules and contracts and so on and so forth. And the intelligent assistant needs to be able to understand all of the complexities of that, and deal with very sophisticated queries, because they're not like the consumer products which are kind of relatively straightforward: single-utterance, single-response conversations. What happens in the enterprise world is that you have much more of a dialogue.

It tends to be not a simple question, but a series of exchanges between your company and the customer, leading to some sort of outcome -- either an upgrade to your account or a cancellation or an airline booking, or whatever it might be that your service is, or your products are. And you're basically embodying your business processes in an intelligent assistant in some way. And Teneo is built with that in mind; it enables people to collaborate, whether they're developers or whether they are subject-matter experts, the guys who understand the business processes well and understand how they construct dialogues.

And they can collaborate together in a very pictorial and graphical way, in order to bring those business processes to life in a conversational form. And Teneo enables them to do that, at the very highest level of commercially available intelligence, and it enables them to do that very quickly, it enables them to do it on all sorts of different channels: from Twitter and Facebook to websites and mobile phones and mobile computing, even Google Homes, and so on and so forth. It allows them to do it in 35 languages, if they so choose. So, it's a complete solution for the CIO [chief information officer] of an enterprise who wants to deploy one, or in fact, very many different virtual assistants, or intelligent assistants, or conversational interfaces, to all sorts of different departments and divisions within their business.

Because our customers tend to be some of the world's largest ones. They tend to be large B2C [business-to-consumer] companies, because clearly the more customers you have, the more you can advertise the investment in automating the conversations with them. So it makes sense to these people to be pioneering investments in this sector and bringing these solutions to life. So, Teneo is a language-specialist platform, a conversational AI platform that works in all sorts of different use cases, but it tends to focus on the enterprise because it's much more capable of sophisticated, humanlike, intelligent, and capable dialogues.

It will handle dialogue interruption and resumption, it'll handle multistage conversations, and it'll handle the vagaries of us as people. And as you correctly say, enterprises are seeing this as a sensible and prudent investment for the future. Enabling them to reconnect with their customers, which many of them have lost proximity with their customers as they leverage things like mobile computing and the internet to automate processes with them. And they close branches and banks, and so on and so forth, only to find out 15, 20 years down the track that, actually, they don't have a means of having a dialogue with their customers. And actually, a conversational interface, an automated conversational interface, not only gives them the opportunity to reconnect with them, but also to learn from every single conversation that takes place.

Which is a unique and new thing for them, that they's the ability to listen in on every support call, on a customer service call. It's the ability to listen in on every sales conversation and to learn what your customers like, what they don't like, what works, what doesn't work, and so on. And by obviously using that data to improve your products and services, you're hoping not just to reduce cost and make your customers happy, but to maintain longer relationships with them, to have less churning [of] the customer base, to increase the account value per customer. And all those sorts of metrics that are very, very important to large-scale enterprises.

So we think it's a big and important market. And we're really pleased to be in the middle of it.

Simon Erickson: Absolutely. Lawrence, we spoke a few months ago with the chief marketing and strategy officer, Andy Peart. And he said that for the enterprise, there are needs, as you just mentioned, that are very different than the consumer market. There's contracts from online sales quotes. There's liabilities at stake; the enterprise is very demanding in a lot of ways.

And I wanted to ask: How is the business model of a company? Do you offer it on a per-license, per-user fee that then can expand and collaborate between the customer service of the company? And then also a sales group? How are you bringing this to market, and how are you modeling the business?

Lawrence Flynn: So, we bring it to market as a platform proposition, so you can either, essentially, buy one of two ways. You can buy what we call an application license, so if you have one particular need that's, let's say customer-service chatbot, you can just license the chatbot. Or you can license the entire enterprise and build as many different chatbots, or as many different business units and languages and what-have-you as you would like. On the way that you buy it, you have, we have a term license for the platform, and then we charge a usage fee which is based on the number of dialogues that you have. And the logic behind that being that, each dialogue that you have generates some value for our customers, and we take a small piece of that value so that it's a win-win for everybody.

We typically go to market in conjunction with our business partners, who are the same organizations that are servicing large enterprises, so I'm talking about Deloitte and Accenture and KPMG and Cognizant and people like that, Sapient, who are in the business of providing implementations to large enterprises; that is their bread and butter. And because we've made Teneo a highly graphical and collaborative tool, we can train people within those systems, integration companies, to use our products in order to realize projects on behalf of their customers. Many of our customers have relationships with our partners, first and foremost, and our partners leverage our technology to deliver the solutions on behalf of their customers.

So that's how we do it from the go-to-market point of view, and from the licensing point of view, it's based on usage, which we believe is the fairest way, because everybody gets value from the usage.

Simon Erickson: Certainly. Lawrence, [I] want to talk a little bit about data privacy. GDPR [the General Data Protection Regulation] was a big topic here a few months ago, which is, of course, much more strict regulations on consumer data privacy. Now, originally, I might have thought that this could have been a hurdle for a company that's deploying conversational AI, but I think that the more I think about it, this could actually be an opportunity for you all. Can you talk a little bit about this role of regulations and how this plays -- I guess a role in the future of your businesses as you grow larger.

Lawrence Flynn: Yes, you're right. I mean, with a European heritage, GDPR has been a big thing in Europe for many years and we've -- it's part of our DNA. So, as you correctly pointed out, we have to operate in environments where GDPR is a big concern, and where other things are a big concern. Like regulated environments like banking and finance, where it's not just the data but the processes that are important as well. And as far as the data's concerned, well, yes, there are lots of rules and regulations that, of course, our customers do have to comply with; they all have their own data policies in place, and they all have to regulate and control and police which data they are storing of some customers, and so on and so forth.

And Teneo provides a repository for the conversational component of that data. But, in order to comply with the GDPR regulations as they are interpreted by our customers in different geographies and in different use cases, you can tune, inside the Teneo platform, exactly which data use you keep and where you keep it. So, for instance, you may choose to keep only anonymized data about your customers, so that it is not possible for you to interpret anything about an individual and you're not storing any individual-related data. That is one of the options that you have when it comes to Teneo. That literally means that we never, ever write away to storage anything that is personal, non-anonymized data, so that there's never any risk of any liabilities under GDPR legislation or what-have-you.

But, if the data is anonymized, you can, as a company, at least learn from the mass of dialogues that -- maybe not what an individual by name is thinking, but you can learn across the whole demographic of your customer base what they do think, what they do like, what they don't like, where they have problems, where you have successes, and so on and so forth. So the whole data thing, it's a massive opportunity for our customers to really gain proximity to their customers, to learn what they like, to build better products and services, instead of through guesswork and focus groups -- because they're getting the first-person singular voice of the customer, and they can learn directly from that. And at the same time, they can remain fully compliant with data regulation, because it's highly configurable how you set up and what you store. And you don't have to store anything of a personal nature at all within the platform. You can entirely tune what data is stored.

Simon Erickson: Well, I certainly see the advantage of having more control over the data, especially from a regulatory perspective. Lawrence, my last question for you is: Conversational AI is evolving very quickly right now. In the media, we are reading a lot of different headlines about it and people are taking this story in a bunch of different directions. But as somebody who lives and breathes this industry every day, [the] CEO of a company that's strictly related with conversational AI, I want to get the chance to ask you: Our audience is individual investors who [are] very interested in this space -- what would you recommend that we pay attention to, as conversational AI evolves?

Lawrence Flynn: Well, I think that the industry is going to reach a tipping point. It's very difficult to predict exactly when that's going to occur, but there will definitely be a tipping point in the not-too-distant future, where...from being a pioneering or early adopter of a technology like this, the need is to have a conversational AI platform for every enterprise and for every CIO; it's going to transfer onto the mandatory software stack for every large B2C company. I'm not quite sure when that's going to happen, but you're going to see that companies see conversational AI as an essential tool in their wings of interaction across all sorts of channels. So it will be ubiquitous from call centers to social media, from speech-enabled mobile devices to traditional websites. It's going to be part and parcel of the user interface of every company in the future.

And, of course, there are advances in technology all the time, and we are in the vanguard of that. We pride ourselves on being able to build ever smarter, ever more intelligent and capable solutions to deploy, literally to the extent that we can fully automate and provide service. We have built solutions which statistically perform better than humans, because they are...they never get bored, they never misinterpret the two utterances, the two sentences [as] different when they're the same. There's no variability that you might get from talking to one call-center person or another; it's 100% consistent. So we have, certainly, deployed in the field in cases where we can outperform traditional call-center markets, where, obviously, staff turnover is rapid, where training of individuals is a big issue and keeping them up-to-date with information.

Whereas we only ever have to train one robot to do it, and it never takes a day off, and it works 24/7, etc., etc. So I think that as investors, I think that it's important to recognize that the market is predicted to grow, and, certainly, we perceive that the market will continue to grow. And we perceive that, although all boats may rise on the tide, we think that the Teneo platform is a very strong, unique proposition for the enterprises. It's the only conversational AI platform that was built uniquely with the enterprise in mind. And we believe that you will see increasing examples of field deployments of superintelligent robots being delivered on behalf of our customers by ourselves and our business partners.

So, I think what investors will see is basically a proliferation of the technology. We'll wake up in five years' time, and if the company doesn't have some sort of conversational interface on the front of it, we'll think it's old-fashioned. In much the same way as my kids go up to a screen and if they touch it and it doesn't do something, they think it's broken. I grew up with a black-and-white television, so it's...the world moves on and expectations change, and I think that's exactly what's going to happen with conversational AI.

Simon Erickson: Certainly. Right now you've got the larger, regulated enterprises that are the early adopters, so to speak, of this technology. You see this in a couple of years, or wherever that tipping point may be, where smaller businesses and the larger market [catch] on. I mean, it's an arms race and everyone has to keep up with each other, correct?

Lawrence Flynn: Yeah, I think, it is an arms race to a degree. You're right, because building intelligent conversational interfaces on front of your business's a shop-window thing; it's part of your brand. So having that exposed and making sure it excels is really, really brand-enhancing for you. So, yes, it is an arms race and people will do it, and if they do do it, they get tangible benefits. Of course they reduce the cost of dealing with their customers, which is great, but they learn more about their customers, which means they can build better things for them, and provide better service to them. So, it's a win-win both for the consumer and for the enterprise. It's a technology that benefits everybody in that regard.

Simon Erickson: Absolutely. Well, Lawrence Flynn is the chief executive officer of Artificial Solutions. You can learn more about the company at, and be on the lookout for them to be publicly traded on the NASDAQ First North stock exchange on March 12, 2019, is the plan. Lawrence, thanks very much for the time with me this afternoon.

Lawrence Flynn: Thank you, Simon, it's a pleasure.

Simon Erickson: Thank you everyone for tuning in. Fool on!