3 Examples of Organizations Improving CX with Self-composed AI
Global Vice-President of Avaya Product & Offer Management
Most business leaders don’t need convincing about the power of AI: nearly 60% surveyed last year by Zendesk said they plan to increase their investment by at least 25% this year. The most powerful applications of AI help organizations do more with less without compromising – rather in many cases enhancing – their customer experience, from AI-powered bots that accelerate problem resolution to AI digital co-workers that supercharge agent performance. IDC predicts that 40% of the Global 2000 will augment their human staff with AI digital co-workers by 2025.
AI is a vast and exciting frontier, and you don’t have to hire a developer or bridge an internal capability gap to get started. Leading technology vendors have made it so that businesses can easily launch and customize their own powerful, CX-enhancing AI. The key is a cloud-native, API-based architecture that allows you to design and build AI-based applications and prove them out in a low-risk way.
Here are three examples of organizations that have improved their customer experience with a “build your own AI” approach…
1. Bayview Technologies contextualizes CX and cuts handle time in half by blending omnichannel with self-built conversational bots.
The BPO’s contact center blends various media streams (chat, email, voice, video, social) with self-built AI chatbots and voice bots using the Avaya Experience Platform and Google Dialogflow. These fully functional bots pass customer conversations through an intelligent AI engine to make informed CX decisions quickly and precisely with support for three different languages.
The organization’s handling time has decreased by 50% over the last three years and its abandonment rate has been under 0.5% most months. Conversational context collected by the bots are key for the company to see and understand problematic customer journeys and how to fix them as soon as possible.
2. A bank enhances CX, improves data protection, and reduces costs with AI-powered digital ID verification.
Traditional identity verification methods like knowledge-based authentication (e.g. “what’s your mother’s maiden name?”) take too long and are no longer the most secure option in today’s digitally advanced world, not to mention they take away from the ease of an effortless customer experience. This bank is using AI-powered digital ID verification methods like real-time facial recognition to improve data protection, reduce costs, and create a more seamless customer journey.
This is game-changing for everyday authentication, significantly decreasing the bank’s “false acceptance ratio” (the likelihood of the system incorrectly verifying a person’s identity) while increasing its scope of compliance, decreasing friction for the customer, and improving data privacy. Research also shows the time saved using AI for verification can save as much as $3 per call.
3. A university differentiates its study abroad experience using self-composed AI bots and Augmented Reality (AR).
In this exploratory case, an interested student (let’s call him Mark) contacts the university to review his options for the upcoming semester. He clicks the link provided on the website to get more information and is connected to the university’s AI-powered chat bot. The AI bot collects Mark’s details and answers a few of his questions. Mark discovers that he is eligible for a semester studying abroad at the university’s London campus. The bot then provides a link to enter the university’s self-composed Metaverse (an immersive, virtual 3D space) to explore studying in London.
The university’s Metaverse allows Mark to learn and engage via an immersive, computer-generated version of its London campus as he considers his decision to apply. AI bots and human agents can flow in and out for service assistance as needed.
Ready to build your own AI?
AI has permanently changed how organizations use technology for their competitive advantage. Our advice: start with small-scale, attainable applications (e.g. having your virtual agent successfully communicate with customers through the steps required for a given task or process like filing a support ticket or resetting a password), then build from there to start using AI in more advanced ways.
