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Webinar Bytes

All your Contact Center AI security questions answered

We’ve taken one of our webinars and broken it down in to smaller video segments.  Check out some of the most important parts of the webinar below.  Then watch the full video by clicking the link below.

Artificial intelligence (AI) is proven to offer many benefits: personalized customer service, increased operational efficiency and improved customer satisfaction. However, many business and IT leaders are concerned about the security implications of using bots and predictive AI technologies in their contact centers.

Join us for the “Ask Me Anything” webinar in which we address top questions related to Contact Center AI security. Meet the experts from the Genesys and the Google Cloud Contact Center AI teams to learn how to deliver secure customer service with human-like conversational AI.

Watch the full webinar by clicking this link.

Meet the Speakers

Kishor aher webinar image

Kishor Aher
Lead Architect for Contact Center AI
Google

Toby tobkin

Toby Tobkin
Technical Solutions Consultant, Cloud AI
Google

Webinar janelle mattews

Janelle Dieken
SVP, Solutions and Product Marketing
Genesys

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Wendy Mikkelsen
Senior Director, Product Marketing
Genesys

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Thanks, Wendy. So, contact center AI offered by Google and Genesys

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is an integrated solution. And what it means is that it gives you

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the best of both worlds. Genesys is a leader in

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contact center space and Google is in AI space. So,

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we come together, we integrate our products and we offer

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it to our end customers. It is an omnichannel solution so that

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means you can have a chat integration, voice integration and

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social media integration out of the box. Typically, contact center

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AI solution needs to take care of three different kinds

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of stakeholders. First stakeholder is the end customer. So, end

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customer calls in into the contact center and they are

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either interacting with the bot or they are interacting with

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the human agent. So, human agents are our second stakeholders.

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And the third stakeholder are basically agent managers or customer

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experience executives because they need transparency into the contact center.

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Remember contact center, mostly handles unstructured data that is like

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voice or chat. And it is very important to take this unstructured data and create structure and information out of this data. And Google AI can help

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you dig this unstructured data and create structure out of

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it. Toby, do you want to add something to that?

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Yeah, definitely. I think that I’d also like to break it down a little

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bit about where the technology comes from and what it

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actually means for contact center operators. So, just to set

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a little bit of interesting background here. So, contact center

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AI is actually made up of, I’d say three big

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separate components that are integrated into Genesys ecosystem. One of them is

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CCAI virtual agents, which is based on a piece of

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software called Dialogue Flow. Dialogue Flow is actually a platform

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that’s used program, Google Assistant at Google. So, this is

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actually the same piece of software that developers use to

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actually build their voice applications for AI assistance. On the

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second one is Agent Assist. This is actually a piece

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of software prides provides AI augmentation for our contact center

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agent’s job helping them go and fill in fields automatically

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or giving them turn by turn guidance for solving a

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complex issue. And finally, there’s also Insights AI. And so,

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what this does is it actually surfaces all the information

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that the artificial intelligence is actually seeing out in the

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field at your contact center in a digestible format. So,

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what does it actually mean? Especially, I would say Dialogue

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Flow is the one CCAI virtual agent, which based on Dialogue

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Flow is when I get the most questions on from contact center

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operators. This is a combination of some things there are

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net new and also things that are kind of just

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like next generation of tasks you already do for your

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contact center. I’d say the most relatable thing is the

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thing that most next generation. So, if say your program

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menu, oftentimes nowadays you’ll use a keyword recognition system, something

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where if somebody says something like pay my bill, that

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will go to the pay bill menu and walk you

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through that. The next generation gear, when you actually using

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something like CCAI virtual agent is people can express themselves

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however they want and the system will still capture it.

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So, something like, ” Hey, I want to pay my bill

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now. Is it possible to do it by a credit

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card?” It would be able to actually go and pick

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up that utterance and still classify the intent as being

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pay my bill, even though it was very open ended

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and freely expressed. I would say that menu replacements tend

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to be the first step that most people actually do

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when they use the system. And then they tend to

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move on to much more sophisticated use cases, where we

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do say automated diagnostics or a resolution of issues even

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if it’s quite complex. a good one, everyone.

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