CLOUD COMMUNICATIONS

November 12, 2018

Avaya Makes the A.I.Connect-ion

Last week, we posted Part 1 of our interview with Avaya’s Jon Alperin, who will be speaking at the upcoming The Future of Work Expo. Here’s Part 2 of the conversation with Alperin, who is director of partnerships and alliances for DevConnect and A.I.Connect at Avaya.

The Future of Work Expo is a new event from TMC that will explore how artificial intelligence and machine learning are challenging and improving what’s possible in business communications and collaboration, customer service, marketing automation and personalization, and sales acceleration. It will run Jan. 30 through Feb. 1 in Fort Lauderdale, Fla.

EXP360 is among Avaya’s A.I.Connect partners. Tell us about that.

Alperin: EXP360 has a very distinct and unique offer, particularly for the hospitality and retail market segments. Their solution brings augmented reality/virtual reality capabilities to the customer interaction, allowing a contact center agent to essentially ‘push’ visually oriented, 360-degree views of locations or product images to the callers’ smartphone/heads up display device.

The AI elements of the solution include a visual representation of interest, or ‘hotspots’, rendered back to the agent based on where the callers’ eyes are focused within the AR/VR environment being rendered to them. This gives the agent a greater sense of the specific point of interest that the caller may have, and the opportunity to provide more focused answers or selling based on the additional piece of knowledge.

What about Avaya’s partnership with Afiniti?

Alperin: Afiniti has been a long time technology partner with Avaya through our DevConnect ecosystem, with a large number of mutual customers already deploying Afiniti’s solution within their Avaya-powered contact centers.

As we refined our strategies for the AI-enabled contact center, it was immediately obvious that Afiniti’s predictive capabilities for behavioral agent matching would be a crucial element of our Smart Routing strategy, and we jointly developed plans to deepen our relationship along both technical and go-to-market aspects.

At its core, Afiniti AI uses behavioral pairing based on past interactions, demographics, psychographics and other pieces of historical and real-time information to match agents and callers. With a native integration to Avaya Aura release 7 now available, there’s essentially no setup required to get started with Smart Routing, and the solution is considered so powerful that customers pay only when they receive the benefits of the solution. So far, Afiniti customers have seen financial benefits in the 100s of millions of dollars through increased upsell or decreased customer churn results.

What do commercial AI-based solutions look like today?

Alperin: While AI as a field of study is over 70 years old, and we’ve gone through several hype cycles as it related to different types of AI capabilities, many AI solutions are still in their infancy today. I’ve heard reports that over 5,000 new startups with an AI focus or element to their solutions were created in just the first 6 months of 2018, so there is clearly an explosion of innovation being driven by the promise of AI and ML in all its forms.

One of the reasons we formed the A.I.Connect initiative was to bring some structure and validation to our partnership efforts, building upon the core programmatics and interoperability testing capabilities offered through our DevConnect Technology Partner Program. 

Most AI solutions on the market today are cloud-based, due in part to the large compute power required to manage the enormous data sets upon which models are built and refined. Depending upon the enterprise, this can lead to concerns for data privacy, PCI compliance, HIPPA concerns, or more.

At the same time, certain types of solutions, such as robotic process automation require a high degree of integrations within the enterprise, with varying levels of complexity based on the approaches taken by individual vendors, whether mimicking human agent usage of existing desktop GUIs, or integrating via programmatic APIs across back office applications.

In many cases, gathering training data can be a major up-front effort in the journey to implement AI solutions. Some solutions lend themselves well to using ML to self-training, while others require a level of information discovery and consulting to be done up-front before a reasonable level of accuracy has been attained that would support a go-live deployment.

What will they look like 5-10 years from now?

Alperin: I think that the fundamental change is that we won’t be talking about AI or ML at all … it’s simply going to be sufficiently embedded and ubiquitous in everything that we use to have become irrelevant to talk about specifically.

Consumer acceptance for auto-suggested text in email clients, speech-driven user interfaces, driver-assist systems, or for smart home devices that learn your preferences for setting and adjusting temperature controls, we don’t really focus on the ‘AI’ value proposition as much as on how they improve our personal lives.

In 5 to 10 years, we probably won’t notice AI and ML capabilities that are crafted in to the products, services, and solutions we use until we come across something that lacks those capabilities. Much like trying to use a manual typewriter, we’ll probably take a moment for nostalgia over the old ways of doing something, and then start complaining about how difficult it is without AI to assist us.


 



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