Conversational AI In B2B & Enterprise

Meet Our Speaker

Meet Our Speaker Karthik Balakrishnan

Karthik Balakrishnan

CTO @ Wysdom.AI

As CTO at Wysdom.AI, a Conversational AI as a Service (CAIaaS) for enterprises, Karthik heads strategy, innovation, R&D and product at Wysdom, helping organizations adopt, transform and grow with AI. Karthik has had over a decade of hands-on experience and proven global expertise in transforming enterprises through the adoption of emerging technologies such as AI, microservices and eCommerce, which got him recognition as one of the top 19 of 2019 Tech Titans in Canada - an award which honours Canada’s most prominent innovative technology leaders who have either led a digital transformation project or disrupted an industry with innovative technology to deliver enhanced business value.

 

more about Karthik

Karthik Balakrishnan

CTO @ Wysdom.AI

As CTO at Wysdom.AI, a Conversational AI as a Service (CAIaaS) for enterprises, Karthik heads strategy, innovation, R&D and product at Wysdom, helping organizations adopt, transform and grow with AI. Karthik has had over a decade of hands-on experience and proven global expertise in transforming enterprises through the adoption of emerging technologies such as AI, microservices and eCommerce, which got him recognition as one of the top 19 of 2019 Tech Titans in Canada - an award which honours Canada’s most prominent innovative technology leaders who have either led a digital transformation project or disrupted an industry with innovative technology to deliver enhanced business value.

In his past role at Amdocs, he held several leadership positions globally, spanning in India, Cyprus, the U.S. and Canada. His ability to radically redefine problems with a Systems Thinking approach and come up with unique solutions, along with deep expertise in applying Machine Learning to drive automation and decision making, has made him an extremely respectable figure and a prominent speaker in the business and tech communities.

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Event Q&A

Do you think the two factors, discoverability and invocation name, are holding back the enterprise adoption for voice and conversation? And what are your strategies to mitigate this?

Khartik: Are they holding back enterprises? Yes, absolutely. And in fact, a lot of enterprises have various types of internal projects where they try to do something and they face a lot of challenges in mining the historical data and then they give up. They give up because of the challenge of technology and to know how to mine historical data to create some sort of data corpus, and then essentially train your AI on the data, and then iterate.

Khartik: I think it's a bit of a technology gap, of a know-how gap, of metadata logic gap. In terms of mitigation, realistically, you need to focus on being able to mine data. And as you started mining, what you also do is you liberate a lot of your data that you've just been sitting on for years.

You mentioned automating the design process with a human in the loop. Can you unpack that means?

Khartik: There are several technologies out there that don't even have WYSIWYG (what you see is what you get) UI, so the ability to design a conversation. A lot of the conversational AI technologies out there, unfortunately, don't even have that. So you need to be a developer to stand up apart right now.

Khartik: For example, Microsoft Azure Bot previously lacked a UI, and you would go write code to design a conversational flow, which is incredibly cumbersome. They recently launched something called Microsoft Power VA, which gives an editor that now lets us chart you know, drag & drop boxes, you can train from within each box, and then connect the boxes to basically put a conversational flow together.

Khartik: You can take that a step further and allow training in line so you don't go off to a separate page, you're essentially able to train in line. As a designer, all the elements you really need for design is right there.

Khartik: Now, what makes that even better are recommendations. So if you're adding certain types of training data, an algorithm can actually predict the doubting that will skew the model or it will corrupt the training data, or it will cause the understanding of something else in the system.

Who are the typical buyers of conversational AI in large organizations?

What are some top use cases for sentiment analysis for enterprise clients? And what are some potential ethical issues with using this as kind of getting insights from customers?

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Slides

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Curated Resources By Voice Tech Global

Get Started With Conversational AI In Enterprise

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Conversational AI In Enterprise Use Cases

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Curated Resources By Voice Tech Global

Get Started With Conversational AI In Enterprise

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Conversational AI In Enterprise Use Cases

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