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Courtesy of Tech Mahindra's Sreejti Ankarath, below is a transcript of his speaking session on 'Conversational AI - Trends, Solutions and Best Practices' to Build a Thriving Enterprise that took place at RPA & Intelligent Automation Live.
Conversational AI - Trends, Solutions and Best Practices
I'm talking about Sri Git and Caress, who I believe is coming from, not so far away from our math. I think he's in Dallas, Texas, I'm here in San Antonio, Texas. ... is a global leader with more than two decades of rich corporate experiences across growth, innovation, and strategic consulting. He has mantra, several startups, and is a part of leading incubator clubs in the United States in Asia, and also serves on several companies advisory boards. He's a postgraduate in Management and Management and Economics and holds several other academic pursuits in artificial intelligence, Strategists from catalogs, Business Process Design from MIT, Digital Marketing, Digital, Analytics and Insights Certificate Programs at SMU Dallas, C O P C. Design thinking, six Sigma and Balanced Scorecard.
True Oracle off methods People, Process technology with us, shrewd yet, what a pleasure to have you with us. Thank you so much for taking the time to share your expertise with our global audience today.
Pleasure is entirely mine, and it's always a great opportunity to be interacting with you.
It was a very happy to be here today, with all the global audiences that, you know, been entertaining for the last 2 or 3 days and giving them a lot of learning.
Yeah. We're waiting for you to show your screen.
Yes. Sorry if it was.
When lagasse visual technology is, I hope you guys can see the screen today.
I think I think he may be coming up. Yes. It's on Now. Is sure you just Thank you.
So, good morning. Good afternoon.
Good evening, and a very warm welcome to all the guests who have joined this webinar from all over the world.
And really appreciate you. And thank you for joining us today.
Conversational AI is one of the hottest topics in the industry.
And, one, that has fundamentally changed the optics of digital transformation, if you will.
I'd been a keen learner and a student of the space over the last several years.
And looking at it from the last five years or so, it has made significant progress, right, across a lot of industries, and markets.
And now, and I'm very happy to share my learnings on what we've been able to achieve in this space. Having worked with several companies, cause customers, and also partners, right in this space when we work very closely with. So let's, let's get straight into it. Right?
So, if you really look at it, and everything that's been going around us, from a corporate perspective, it is very, very apparent that digital innovation is imperative.
All right, it's a question of how, to what extent can you involve your initiatives to enable the customer, be more digitally happy, right, in terms of, whatever they need to do, is what, what it's all about today, that's the game, which is all about.
So, if really look at.
But, in that perspective, conversational AI, AI, again, is a, is a huge, augmenting aspect, which improves the overall customer experience for the various companies and and and global markets.
So if the, the, the, a conversational AI market is, was about five billion in about 2020 and it's it's slotted to reach about 16 to 18 million, which is a CAGR of almost 30% the next 4 or 5 years? So people are expecting a lot of growth in this area. And in my last count, there are more than 300,000 conversational AI.
What's an assistant or pods, that everybody is playing around, across the globe? So, it's a very, very, large number.
In a recent survey, on what AI solutions, do you really think we will have the largest? Impact the business, which was run by one of our, one of the analysts groups?
What is it assistance? conversational AI chatbots? They were almost at about 50% in terms of the the largest impact on the business. So clearly, there is a lot of momentum. There is a lot of expectation in this space, right?
So let's figure out In terms of where has this space been in the last couple of years, and where does it today and what is next right, in terms of what? What can you expect from this particular space?
And, again, I'm a keen observer, a learner, so I'm very happy to share my perspectives on where we are and where we are headed as a part of the whole conversational AI aspects.
So, I see this world of conversational AI, and, in three generations, if I really look at it, the first generation was a simple chatbot.
A script payson interactions, which was engaging on a single channel, right?
And, then, when, most of the times, it had one single source of interaction, Right? And, they know most of the logic, well, hard coded, which is what I call the heart.
The chatbot generation then came the virtual assistant generation, but, it was more about conversations. Right? You know, people started figuring out how to have slightly better conversations with the, with a virtual assistant or a chatbot.
It started getting better in terms of trying to understand what the user is, saying, what the user intent is all about, and at least be able to handle one or at best too intense in terms of what it has been asked. Right.
So, if you were to ask a question, hey, I am looking for my order, right?
It can understand this in a fairly natural way, right? And try to respond to you based on the context, or the fact that it is, it is it is integrated with your CRM like Salesforce or anything else. And then it is able to retrieve that information. So, very, very slightly, more generational, more conversational, and also able to execute certain amount of actions by integrations of it at the backend.
So, that was what I, that, is what I call as a second generation chatbot.
Now, come today. Right, and come tomorrow.
What we are seeing is, generation three are a generation for chatbots, where the context of conversations via a very advanced, analytic capabilities extremely rich. So, you can literally talk, like, how you and I are speaking as humans, and there is an ability for us to integrate this with both boys, as well as text.
So, you can use either a channel of now, you want to do it by voice, or you can start typing it, and know interacted with a chat, with it with a text.
And it is also capable across all channels, right? When I say all channels, right from your messaging channels, and on your whatsapp, and Facebook Messenger of the world, or it can be a voice channel through your IVR, that you can interact or any of the channel of your choice. Right. So, it has omnichannel.
And it also today, now, a lot of conversational AI is able to integrate its data sources, which is both structured and unstructured.
So, it gives a lot of options for us to be able to then, have information sources that can be readily available at the beck and call of both the customer, as well as the employee who's handling the particular aspect of it.
So, this is how I see the generation of conversational AI come through in the last couple of a few years. And, it's interesting to understand in the same context, right? What next? And they don't.
I'll be will be speaking about it as we go by and the next few slides. But, I think it's time for me to understand from the context of the audience that's taking two.
Where are you in the journey? And I would probably encourage I would ask Jose to run my first poll here.
If you want the, the poll is with generation IVS, are you currently implementing in your respective organization, So, Hosea, if you can, Hi, audience.
I will do that right now. The first one would be, Which generation IDAs are you currently implementing in your respective organizations? So, for the audience, now, you're gonna be launching this show if you could take your votes as quickly as you may, which generation IDAs are you currently implementing? Go ahead and the poll is open now. Go ahead and vote on that.
It's this being distributed. So, which generation IDAs are you currently implementing your respective organizations, is a first generation, second generation, third generation basic script, Bayes Single Channel, multi turn Single Intent Conversations Multipoint Thant low effort deployments. You are all awesome. You're already voting volt quickly, so that we can tip the, the presentation. Moving at a good place and getting your input on this. So what generations do you have, if any, first, second, third, what does it look like in your organizations? Where does the level of maturity right now, when it comes to conversational AI?
So, again, for those of you who may be a little distracted, the post up right now, and I'm waiting for you to vote in one of these three options and. Awesome, almost, everybody has voted great audience, as usual. I'm gonna close this poll now, and I will share the results with everyone, and I'll read them out loud for you, should jet.
So while we see here in, this audience is that 53% of them ARR, first generation, 42% second generation, and only 3%, I'm sorry, 5% at third generation?
Yeah, I think it is very much in line with what we are seeing in the market in terms of various geographies and whatever is happening elsewhere.
So not a lot of companies are beginning to be in the stage of between the second and the third, not necessarily the first, but yeah. It's, again, depends on the maturity, the organization's on several aspects.
So I'll say, I also want you to do one more poll very quickly.
If you don't mind that the poll is about the scale of conversational AI deployments in the organization today.
Terrific, we have just shared that is being distributed to the participants right now. So, the next poll here, What is the scale of conversational AI deployment senor support organization?
Is a nation proof of concepts currently evaluating multiple vendors, a few deployments, still exploring solutions, or fairly broad line on the solution, stack and architecture. So, please go ahead and take your votes from, ah, what is the scale of conversational AI deployments now from your support organizations perspective.
So, take the most educated guess if you're not necessarily, you know, close to your support organization. I would suggest, take an educated guess, where you think your organization is out of this three options here, very, very well aware we're almost past the halfway point in terms of participants voting. We're going to wait a couple of more seconds here, and I'm going to close it right now, closing it, and sharing the results. And what we have here, should git, is that the first option of nascent and proof of concept has 35% of the votes, the majority are 59%, is that a field deployments is to explore solutions. And only 6% is fairly broad.
I think, yeah, I think we have a very slightly more educated and a mature audience, who's playing around with quite a bit of conversational AI it looks like.
And it's always exciting, because I always tell our customers that, with the beginning, the journey, still evaluating options is a great way to test a few aspects on proof of concept, because that gives you a feel of what is available in the market, what is out of the possible.
So, great to see, That is alignment into what the world is doing, and some of our audiences and the leaders out there.
So very quickly moving on, and I really appreciate this, Jose to put on this poll for us.
Great insights from the audience, As always, so I'm going to quickly turn my slide over and talk about what are the trends, right, that the enterprises are embracing When you talk about conversational AI, right, and then, so for me, I look at it from five perspectives, right?
So the world is all about convergence, and it's my favorite topic.
But if you look at everything that's happened, whether it is RPA to start with as an intelligent Automation Suite. When more cognitive, today, you have RPA in the context of converging that with everything that you can think of an extraction perspective or integration perspective, or even go into the cloud from that from that world. If you look at conversational AI, what I see is a world where, which is converging around voice.
So like I said, if you call your IVR today, right, it is not the press one an oppressed to anymore, right? You can talk to the IVR as much as you would like to talk to, and to an agent, or to a person.
And the conversational AI, the voice bots, or otherwise, virtual assistants, will respond back to you in the same length as you would talk to a to a to a person.
And also, it has an ability to understand that you're struggling, right? And then accordingly connect with the human in the loop, right? Which, which, you know, enriches your overall experience, right?
So, it's become very much a play of integration across voice, text, which is how it started off predominantly. And we're also seeing very interesting applications of image, when I say image, right? I've had a conversation with product companies in the space, where you can actually show your phone or a picture of what your challenges if you're troubleshooting, for example, in a technical environment. And then, the person on the other side of the of the screen can actually troubleshoot within your context of what you're going through. Let's say, for example, your modem is, has gone bad. And, you know, your signal, you got only one light. But as a, as a million, or as a person who was not very savvy on technology. You're struggling to understand what these lights are. You can take a picture, show it to them, Right? And the person at the other end, right?
As a board, as a virtual assistant, can understand what you're talking about an interpreted, right, similarly, we are also seeing huge amount of deployments, where we, using GIS maps, integration of GIS images, understanding of the context of GIS imagery into the context of conversational AI. So a lot of a lot of convergence of technologies in this space is what I'm saying.
And the next is the most important aspect. Right?
The augmented AI.
When I say Augmented AI, what I really mean to make the audience understand is that we are still far away from everything be managed by a virtual assistant or a conversational AI intervention.
That needs to be a human in the loop, right? There needs to be human intelligence, which will augment the whole process or the value chain.
And this is where more and more it is getting complex, because most of the basic stuff can be handled by a conversational AI today.
I do not see any any human taking a call on basic FAQs, for example, on a retail product, or a financial product. Now. This has already been handled, and mine is extremely well by a conversational AI, but the moment that gets a slightly more complex right, and where you need a guidance from somebody. And you're struggling because you're, there is a that is a sentiment attached to this. So, for example, I can understand if you are struggling because of my voice, My tone, so, I'm injecting speech analytics in the context of conversational AI hamster, I'm trying to understand visual cues that you're presenting, and then I realized, you know what? Maybe as a, as a customer, I'm not very happy with what is happening in the, in the world of what my interaction, those experiences, and then I connect to a to a human human in the loop, who can better handle that conversation. So, a lot of contextualization and personalization happens by ensuring that we are able to take digital clues, right, and then hand it over to an agent with everything that you can understand on the interaction basis, and then the entire composition is completed.
The next important trend is, it has started from natural language processing, natural language understanding, and today, conversational AI products, right? At least the fourth generation products are also able to generate content, right, through artificial intelligence.
And this is one of the most exciting trends, that I'm personally looking to explore more, because there are very few people who are integrating all these elements. But the fact that the NLP, the NICU, and the energy is coming together, It was a great way forward, in the context of conversational AI, right?
The, what we're also seeing, as in terms of conversational design, is, like, in like an RPA and other other aspects of intelligent automation, everybody is trying to come to a stage where there is very minimal build of a design, right. Of a journey.
And which is almost zero, right? In terms of what the expectation is, that thinks that, that's the, that's a goal that everybody's chasing. And the fact that, you know, you can, you can readily deploy a conversational AI by the industry, by the value chain, by the vertical, or horizontal lot of market, or a particular problem statement. That is what everybody is going after. And the last one is, what is one of our favorites in Tech Mahindra, where you know we are trying to do this at the market, at very large scale, is what we call as the four C's.
Now, Foresees is the coming together of creative content, creative, commerce, and care, all in the same breath.
So, today, conversational AI is being looked at solving for all the foresees, which involves ensuring that the content is first understood.
They are able to understand the context of where the customer is in the journey, right? Ensured that they were able to give the right creative, in terms of giving the information that is right for them. Right, through various forms, it could be reach media, it could be text, it could be message, as it could be. A voice call, it could be an outbound call into the customer, could be anything in terms of designing the content through various creative ways.
And then lot of companies today are benefiting by mixing kamaz in every touchpoint of conversational AI.
I've had an example of a very large partner that we work with who have generated almost half a billion of additional revenues for its customers. So lot of a lot of interesting aspects.
And almost 60, 70% of companies who the e-commerce, retail, and financial sectors of deployed commerce using conversational AI are seeing a huge uptake in terms of the overall revenue that they are able to generate through this channel. So a lot of lot of action there. And lastly, care, which is how it started off, right? Ensuring that the customer journey is managed at every touch point. So, this is what some of the large trends that I'm seeing in the market, when it comes to conversational AI.
And I'm hoping that some of the audience are already playing with that, or did you give them a good clue on when they're looking for products and services in this particular space?
Quickly, moving on. So really look at what are the use cases, right? And this is something, again, everybody wants to understand.
If you talk about UA, enterprises wanting to get into the virtual assistant or a conversational AI, like, What are the use cases that, that, you know, people are doing?
And, again, here, again, now, the expert opinion is that 85% or 90% of the customer interaction will be handled without write an intervention that is meaningful from a human agent. So, lot of, lot of expectations in terms of what can be automated, and what are the use cases that we are seeing in the market?
So, again, I see this in three parts. Right? Now, if you look at conversational AI, there is a conversational AI who can essentially talk to a knowledge base, right? That is the first level of use cases that we are seeing.
So, let us say, you have thousands of documents spread over the entire knowledge management in your organization. It can be PDFs. It can be embedded as part of a CRM and ERP system of record system of interaction, or it can be voice calls or text analytics, right. So, we have data everywhere. Now, how do you connect all these data sources tied to a knowledge base? Right. Which then, forms a part of the knowledge base.
So, you have a list of use cases that organizations are doing. Which is talking to a knowledge base. So, that's the first level of conversation or use cases that organizations are readily able to do.
And the good thing is that, this is a great starting point, because a lot of these are internal, that's how they started off. And once they're very comfortable with internal knowledge base, and how the conversational AI is mature in this particular design, and they know the experience part of it, they use the same knowledge base and to the customer as well.
So, there are, there are knowledge forums today, which, you know, a lot of companies like photos are very popular for. But every company has as a knowledge base, which is extended to the customer. and this again here, again, conversational AI is able to intervene meaningfully and, you know, and and ensure that a lot of support calls into the centers are eliminated, So, that's the first conversation that of use cases that you see, the second is talking to an application.
Like I said, in the second generation of the third generation today, a conversational AI product, both the voice context and the text context, or an image context, can talk to several applications, right at the same time. So, we have enough amount of APIs, that total of all the organizations are either extending it, or at the product level. We are able to ensure that the APIs are available for you to integrate with.
So, whether you have a SharePoint servers now, you have an Active Directory integration. That is required now, Racal, It does not matter what it is that all the conversational AI products out there in the market today of scale can integrate with any application with a custom application, or otherwise, which is available. Right, which is what we are seeing. So if you If you combine the first and the second. Right, there'll be a lot more use cases that you can extend both internally and externally.
The last last and what we are also seeing as talking to excuse me for interrupting, but your audio has ceased to broadcast Oh, this you can do a check there. Making sure you're on your connections, OK, we are not able to hear right now.
We can see when I hear, Oh, OK, are you able to hear me now?
Can you hear me now?
Can you give me an app?
Is it possible to hear me now?
Now unfortunately, I still am not able to hear you.
Oh my God, I just on.
But he says it said 400 megapixel over and PBS, So I don't know what is going on. So I'm gonna let you proceed, and audience if you are able to hear should get right now. I just want to make sure it's just not something maybe on my own sign.
Let me know. Should you go ahead and proceed? I'm gonna wait for sending it back to us. I think they can hear fine. And maybe something on my, and on this case, I apologize. Please carry on.
OK, Got it.
Because, again, the third type of conversation that I'm seeing, is talking to a contact center, right, and ensuring that, we are able to automate a lot of call types, which is getting into the contact center.
And there is a huge amount of cost leverage that organizations are able to achieve by ensuring that the conversational AI is as an intervention is, you know, as, you know, reaching the support centers, and augmenting the human.
Where you're able to do multi turn conversations, judgement, incentive, concept, work on conversations, and several other aspect that I told you as trends, Again, I just want to quickly pause and take a moment and check with Jose.
Is audience able to hear me, or, do we need to do something about this?
Can you guys still hear me OK?
I think I will continue. In the interest of time.
What are we seeing as use cases across across enterprise, right? And, again, this is not an exhaustive list, This as mostly popular list that, you know, all of us are trying to do in the various horizontal and vertical spaces. That's available for us.
So, if you look at banking, banking services, account management, ATM services, these are some of the use cases.
We look at insurance again, quota policy, proof of insurance, policy statement, and reconciliations rounders, anything around premiums, uh, telecom billing assistance. So you get a plethora of use cases that we are seeing.
And what is interesting, also, is that, what we are seeing is that almost 40% of millennials are engaging with the conversational AI, a very effectively. Right? And it'll just not be the new generation of the Gen as the current generation, which is able to use the chat pod.
But you're seeing a lot of extended use across generations when it comes to conversational AI, which is, you know, really encouraging, especially when it comes to democratizing this as a, as a meaningful intervention intervention for various organizations.
Just taking a pause here in terms of what, what, what customers can expect when they are deploying conversational AI solutions?
For me, the essence of a deployment of conversational AI begins with a human centered design, where you start with empathy, design thinking, right? Mixing context personalization, right? And ensuring that you're able to meaningfully intervene at every touchpoint and channel right, in a very highly secure environment. And that is a minimum that you should expect when you deploy conversational AI product in the market, any company, rather.
Right, and this is where we are making a lot of interesting beds in terms of combining and converging various aspects of what I spoke about, right?
The foresee impact.
If you can combine content, creative, commerce, and care, right in your conversational AI deployment, I think you would see larger Ottawa in terms of everything that you are wanting to experience.
So whether it is a customer experience you want to improve, or do you want to ensure that every touchpoint is maximized, in terms of upsell, and cross sell.
Right, If you're able to combine these four C's, right in a conversational AI deployment, and that, that is yielding a lot of benefits for our customers. Is what we are seeing.
Right, And what is also interesting is that today, most of the conversational AI products out there in the market are able to learn over time.
They're scalable across all channels, and they know they can, and humans aren't necessarily only managing higher order transactions. I don't know, accomplish transactions, and that, that's what we are seeing from a deployment standpoint.
So areas with business impact, in terms of conversational AI.
For me, there are four basic benefits that we are experiencing with customers. one is, especially when it comes to supporting organizations through their contact centers, or support centers at the back office or the front office.
one of the biggest benefit that we are saying is the cost stakeout, right?
Because traditionally, if you look at why channel is the most costless channel across all engagement with the customer, right, and today because of various other digital interventions, which includes messaging, right. You know, ...
that, you, talking about bots, which can handle a lot of support queries on its own. There is a lot of cost takeout and less pressure on organization from a scaling perspective.
What is also interesting is that, today let us say if you are running only a, let's say a 5 by 7 or 8 by 7 kind of support, right? You can extend this 24 by 7 because a virtual assistant can run 24 by 7. So a lot of cost takeout that organizations are experiencing by implementing conversational AI.
The other one is, this is where it has really taken off in a in a positive way where, especially in the e-commerce space with the retail banking to a large extent and wherever companies like even CPG companies are exploring conversational AI as an intervention, they're able to generate incremental revenue.
Again, the stresses on incremental revenue, right.
So the conversational AI channels are able to deflect digital traffic into more meaningful higher order transactions and then the ability for organizations to generate additional revenue, that is what we are seeing as other benefit.
And then we're also starting to see positive impact on experience, whether it assumes that NPS or loyalty.
So there is a favorable customer experience that is, you know, been currently manage through these channels as well without having any dilution of it. And then, we're also seeing, especially in the onboarding, scenarios, we're able to see much more customer engagement, brand conversations, and thereby, the overall stickiness, in terms of acquisition to loyalty. The entire value chain. We're seeing a lot of value.
So, again, broad areas of where we are seeing higher value in terms of deployments of conversational AI is that these are the four major take out that we are seeing.
And this will give a little bit more, in terms of revenue, right, for example.
All of these are various aspects of how we have improved overall business value, or how we're measuring business value, if you will. So, age and co creation rights at all. How do you qualify a prospect transfer to the right person, What is the metric that you will use?
So, the Bot transfer Ratio is something that would be bot to Human Transferees, transfer ratio, for lack of a better word, right. To make it simpler, that is something that a lot of people are tracking us as a metric, which is different from the earlier ones.
Similarly, there is also the, the conversational AI, the amount of revenue that is people are generating, right?
The amount of time saved for the contact center agents, right, in terms of efficiencies, so a lot of and then not with the least, can you meaningfully intervene through competitive intelligence, right, and create a product recommendation, right, with us which is associated with your brand. So let's say you are buying chips. So, Diana, can you, can you also add a sauce with it, right? Can you add a solid start with it? So there are a lot of combinations where there are nudge algorithms, which are helping us to improve the overall upsell, cross, sell, but in conjunction with a conversational interface, like a, like a wider set of chatter.
Got Virtual assistant, kind of, scenario.
Jose, I want you to launch another poll right now, if it is OK?
Also, give me some time to, So, that is, what, what challenges do you organization phase for widespread deployment of conversational AI solutions?
So, here we go, what challenges, use your organization facing, or widespread deployment of conversational AI solutions? So please, go ahead and take your vote right now. What is it? What are the challenges you're facing? Is that, leadership core team talent?
Is it a name, which is, aligned on a solution, architecture, across the company?
There's a lack of use cases or the Roi.
Is it NL U solution?
So what do you what what are the challenges in your organization. Of course, you can only pick one here and pick the one that you think is the most important challenge in your organization out of this four options.
So thank you all of you already voting, I'm going to take a moment here. Votes are coming in.
Give you five more seconds here to take your vote out of the four options, What is the biggest challenge, you're facing?
most important challenge, perhaps?
Well done, so I'm going to close. And at this point I know some of you are still voting, but I have to close it now and, and now share the results with everyone.
And, and what it looks like is that, Leadership, Core, Team and Talent, still, the top driver at 38%, unable to align our solutions, 25%, lack of use cases, 31%, and L U solutions, 6%.
Very interesting, very interesting, and surprised me a bit. To be candid.
I thought, wow, a lot of products are, or at least claiming that there is a low code deployment and, you know, to the extent that is not so much of investment, then a talen effect of that, you know, institutionalize that can resist layer, but, yeah, I think we're still a long way to go. That means interesting insight.
I also want you to run my second poll, if you don't mind. This is, what are the most important attributes that you look for in a conversational AI?
Launch it that one right now should jet And what do we have here for the audience is that the most important Attribute that you're looking for?
In a conversation a our partner what you're looking for in a good partner is a brand, and scale of deployments is a price in the effort of deployments Or is it the product roadmap and solution maturity. You have to pick one of these three here. What is the biggest driver for you? What is the most important attribute, well done?
No, you're taking your votes already.
We have about 10% of the audience voted already, and I'll give you a few more moments here to choose the most important attribute out of this different options.
Um, is the brand and scale, price and effort, product roadmap, and solution maturity.
So, come in and all 70% of you already voted well done. You're very getting good at this.
All right, so I'm going to wrap up now.
And I'm going to share the results and what it looks like is that Brandon scale of deployments is only 13% price and effort of deployments is 25%.
And product roadmap and solution maturity is 63%.
Very, very, very heartening to see that.
I think that's the most important attribute, tried because this is an evolving space and there are big players that are hard core product companies which are giving the big organizations a run for their money.
So, when I say big organizations, everybody right from Google, Microsoft, Amazon, all of them are obviously trying to lead this pace in one way or the other, but there are very, very good unicorns and startups which are giving almost on parallel or better known value in terms of the deployment story and, such, so, that they have achieved. So, it's, and this space is forever, going to evolve for another. Maybe 1 or 2 years, is what I, what I feel looking at the current, is what we are trying to do. So, it is always imperative that there are multiple use cases with different product companies, and the and the enterprise partners that you can play with, so that you get a sense of pride, both their vision and the solution maturity, right, Over a period of time, as well as the next generation.
And that is very critical, especially when you want to start aggregating your architecture at an Angular level, right.
And today, what we're doing, essentially, as an organization, is that time has come where we can create, almost like a common architecture, which can use the best of the breed solution.
So, think of it like, you know, you might run a five different nano use at the back end, right? But I can still affects the most important and the best of the breed solution in terms of response time, and then, use that to power our conversational AI, responds to the, to the customer. Right? In the way, especially smart about intent recognition, and multiple intent that you need to recognize. So that is the best of the breed architecture, which is available today. It's almost like a common architecture that you can reference, and then, you know, that that's an important development, which will further help you to, to take a call. And what is really working better for you as an environment.
So, very quickly, I'll also more when, you know, I think we are also almost defining the close of the R and what, I would love to take some questions, I just want to check with Jose. Are we, are we good with time? How much time do I have?
Well, we are at the Q&A time already here, so we have seven minutes for Q&A. And whatever time you have left here, I would suggest that, you know, you just wrap up when, when, when? you can, so we can jump into the Q&A. Yeah. I'll just take another, maybe a minute more, and this is my favorite slide, right?
So, I've been in the transformation space for the last 10, 15 years, and what I see is, what I call the a B C D. Of transformation, right?
So, augmented AI, I still feel human is the most important element in the transformation roadmap for you, right?
And that, that is what I see as the first one. Right?
So, how do you combine the conversational AI, the parts of the virtual assistant, right? Everything that you've seen in artificial intelligence. Along with the human.
Right. That is most ... way, and that is of the human centered design, that, that, that is important from a transmission element.
Dennis, about ..., what I mean by ...
vacation is that the other, when we started getting democratized, there was almost a vision of a bot for every employee, every customer.
I think very soon conversationally also will will reach that stage where you're able to create your own conversational agents that at a beck and call, put it on your desktop or and I'll put it on your mobile phone. Run with it, right? So I think a democratization of quantification is going to happen.
Convergence side, we spoke about this earlier. Right? Again, touched on democratization through the modification process. And, lastly, but not the least, all of these have to be done in the context of creating a favorable customer experience.
To me, this is the in totality what, what I would call, a true Transformation. As a final comment, right? And everything has to play its part. Automation has to play its part, Analytics has to play its part, like, conversational AI, right?
Has to play its part and human, like, obviously, is the most integral part of the human centered design that you have to generate for organizations.
I'll take a pause here. I'm happy and open to more questions.
The audience might not, That is fantastic. So, would you please, stop showing you your screen, and I will bring the my camera back on and the questions from the audience?
You have about five minutes, so I want to get right into it with some good mix of technical questions and the kind of like higher level approaches. I'm going to start with some of the technical questions that came up.
We have this, we have a question from ... in Azure Murray, and he asks that most of the conversational experience tools provide second and third generation solutions.
He's really asking for some guidance here, is there any tool that can help in proactive, predictive, AI, voice messaging on the notification? He says that that's possible with RPA. But he's curious if there is a conversational AI tool that that is for proactive, predictive, AI, voice messaging, and they'll fit notification?
Yeah. So they found something like, and I'm going to call, some names are not necessarily because, you know, there is a favoritism to this, but, you know, these are solutions that I've looked at work closely in some form, There could be others in the market, until I'm going to put some caveat to this answer.
There are two ways to look at this type.
Lot of algorithms are the backend of a conversational AI, in which we call as ..., and this is working for us extremely well, in the commerce use cases. So, like, I said, right, so, if you want to, if you bought a product and you can always buy additional products with it, then there is an algorithm which is powering that aspect of the analytics. And then the push of that is through messaging channel, right?
So there are players like, for example, live by simple example is a huge example that we work very closely with, who has done a fantastic job of combining proactive messaging and write, for example, the rest of the conversational AI, whether it is a bot or anything else. Similarly, we also have also we have also fonts and flexes from companies. Like for example, Amelia IP soft as another example that we have done very well. On the Asia Pacific side, you know I I know a patent called Yellow Messenger. So there are various players who have done.
Quite well. combining elements of Nudge algorithms, put notion vacations, right. And messaging and everything else around it.
That's what he was looking for. Yeah. No, outstanding, outstanding. That's that's a good reference and guidance right there. The next question comes from the ... Gupta, and the ... is asking and this may be a tough question because we know the projects come in all sizes. But if you look at, maybe, kind of the average, maybe, middle point type of project, for Conversation, AI, what is typically the time duration for implementing a project like that?
OK, I'll break this into two parts, like anything simple, medium, today, just as a proof of concept stage, people should be able to do this and bought 4 for 4 to 6 weeks, right? Maturity of this, right? From a design perspective, when public, somebody who's really happy and there is no real handoff, very little maintenance is required, that's going to take you anywhere between 3 to 6 months, depending on the complexity of use case. So one is getting your environment ready, making it, go live, start interacting with it, right? That should be done in about 4 to 6 weeks. The complete maturity will take anywhere between 3 to 6 months.
That's what we are seeing in the market.
And then, if your voice channel integration, then it could be longer. Because there are stakeholders with the organization. So, again, I don't think there is a limitation of the product to do the interface. A lot of the change management aspects, and the, and the prioritization within the IT teams, within the voice teams, right? Within the product, teams, Right, And, that is still taking a lot of time. An organization. So, it's not necessarily a limitation from a product perspective, but it's more of an internal perspective. The organization change management, that is taking time.
And data integration is a huge challenge, So, this is only meaningful. Unless your data is not mature, then, you know, you can't do anything much, you will be restricted to doing FAQs and things like that. But, if you have more robust data, integration methods, and it's easier, and it's much faster.
Absolutely. And ..., if you look at the last 12 months to show, you know, of course, you are living through a global pandemic. Lots of disruption happening everywhere. But the pace of technological innovation continues to be brisk. And the and if not, if, nothing perhaps accelerated by by the events. I'm curious, if you look back at the last 12 or 18 months, are there new developments in conversational AI that have happened then? There's some people may not be aware off. You know, they still. When you say conversational AI, may be thinking about things that happened five years ago. Anything that's maybe gets you excited about, technically from what happened last 18 months or so.
Yeah. The fact that today we're almost moving to a stage where there is horses for courses.
OK, when I say that, people are getting super specialized in a vertical or horizontal function.
To the extent I know that there are conversational products only for sales and e-commerce.
Right. There are conversational products, we're only doing, focusing on financial services, for example. So that is super specialization, which is really getting excited because then you can, you're getting that much more granular in terms of solving problems for the customer.
That is something that has changed fundamentally. Then, like I said, and I was hoping that the audience will, will know why.
But me, when I said that, that is still less effort, and less and less effort, which is happening in terms of deployment, in terms of design tight. And I think very soon, we will reach a stage where there is minimal requirement, in terms of design and develop deployments, right? So, which is something which is exciting, which has happened.
And last, but not least, like I said, the integration of the voice text image, and competence of GIS imagery, right? You know, combining with Google Map. I'm like, there are so many things happening in terms of convergence, which is a very exciting place to be specially when you look at conversationally.
So that's the way I see that, though Some of those are some of the aspects. And one last thing, which is which I am personally involved in a project, is VR AR. So just imagine an artificial virtual reality combining with conversational AI. That is an exciting space.
Very much so strategic. Well, you know, we're out of time, but I want to make sure that we can still have a connection here. What is the best way of following your work? Is it connection with you for LinkedIn, or there are different channels that we can use? How can we follow this fascinating journey that you're on?
Yeah, I'm on LinkedIn, and we'll be very happy to connect with all our audiences, and who needs any guidance of sought more than happy to be of help.
If you are, if you are closer to my world, and you know we have a lot of networking places where I can go at least once a month, Right? And we have a very free flowing discussions, So close to Dallas of visiting dahlias.
Very happy to meet anyone of our leaders.
That is fantastic. I'm going to check you out next time.
I'm in Dallas, and there are, Listen, thank you so much for sharing your expertise of our global audience today. What a wonderful reveal and, and perspectives on conversational AI. We're much better off as a result of that. Thank you so much for your generosity and sharing your insights and expertise. Thank you, Jose, and thank you, all the viewers. Be safe. I know a lot of things that are happening across that we can control, P secure, be safe. And good luck to all of you. Thank you so much for being here today.
Ladies and gentlemen, that is, she did and crass, vice-president, Tech Mahindra and really a masterclass on conversational AI on, what are the current trends? What are the applications and use cases? And thank you for wonderful engagement from the audience throughout the valleys.
You've always impress me with your thoughtful questions, challenging questions, making sure that we're getting feedback from the speakers. There are useful for your context. And you also rescue me when my audio seems not to be working very well, which I appreciate.
So, we're gonna wrap up this session. But I'm super excited about what's coming up next. We have another tremendous leader in our industry joining us at the top of the hour. And I'm talking about ARRA ... who is the enterprise extract cheerleader for Mondelez International. And she's going to be talking to us about RPA roadmaps, trends in scope from entering from the Enterprise Architecture Perspective.
So, R is an incredible business and technical leader really blends those those areas incredibly well and that always has very insightful, practical perspective. So from someone who is implementing this things and a global organization like Mondelez International. So I'm going to close the session now. Take a break and we'll see you back again at the top of the hour. Thank you.
Global experience of over 25 years specializing in strategic consulting, digital transformation, global alliances, corporate innovation, and incubating new business/ start-up operations, mentoring start-ups.Set-up/managed operations in 10+ countries (India, Philippines, Singapore, Malaysia, USA, Brazil, Argentina, Guatemala, Mexico, Costa Rica, Dublin, Ukraine).
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