When we build scopes of work for client projects, Artificial Intelligence (AI) inevitably comes up. It’s typically phrased as a requirement. “Any new system must use AI.” But what exactly does "It has to have AI" mean?
What makes an AI-powered technology special in comparison to other software programs is that it can ‘think’ for itself. In business, AI is being used to enhance and supplement human interaction between customers and businesses; to provide automated self-help in customer support and service centers, to create a web or chat-based sales platform, to mine data sets and provide the kind of rich intelligence a business can act on.
Just like any computer program, AI receives input, and then does what it’s programmed to do with that input, and creates an output. Type the word ‘hello’ on your keyboard into a word-processing application (input), and ‘hello’ appears in a document on your screen wherever your cursor was at the time (output). The difference between AI and a standard computer program is that standard computer programs require their input to conform to the rigid structures it has been programmed to expect. AI can take input that doesn’t follow a strict set of rules and first interpret it into something meaningful, then execute against that understanding. Think of how you interact with Siri, Alexa or Google Assistant versus a phone menu where you have to press a number key to select an option. That's AI.
AI is so powerful because rather than it being a single software program called AI with limited capabilities, the technology is a set of computing capabilities that when bundled together create the simulated natural interaction experience.
These key AI components allow integration into present systems and also can work independently to create the capabilities Call Centers are looking for today.
Here’s a summary:
Natural Language Processing/Natural Language Understanding - Natural Language Processing (NLP) is just as it sounds; computing technology that takes input from a human being, in the form of speech or text, and interprets its meaning into something useful. Making NLP computing work involves recognizing speech, understanding natural language, and being able to generate natural language responses. Allowing customers to navigate automated self-help using commands in their natural language rather than have to follow strict response rules is an example of NLP in the business AI stack.
Sentiment Analysis - Sentiment Analysis detects, classifies and analyzes the tone, wording, volume, pitch and other characteristics of a human speech (voice or text). Sentiment analysis is widely used in the contact center world to analyze recorded calls between customers and agents for quality assurance and training purposes. Sentiment analysis is also being used to drive routing and service decisions during live interactions (transfer callers who are exhibiting frustration with an automated system to a live agent, for example).
Machine Learning – Straight from Wikipedia: Machine learning (ML) is the scientific study of algorithms and statistical models computer systems use to effectively perform a specific task without using explicit instructions, relying on patterns and inference instead. Machine learning algorithms build a mathematical model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to perform the task. AI is fed examples of interaction to follow, then ‘learns’ the most successful responses so it can achieve greater and greater success at handling the interaction.
Object Recognition - Object recognition allows the camera (and other sensors) on any device to recognize and categorize objects. It is the genesis of facial and fingerprint recognition. Human beings are object and pattern-recognition machines; we can recognize all kinds of objects without much effort, even objects in differing conditions, lighting, orientation, distance, motion, etc. Computers equipped with cameras and other sensors can ‘see’ objects, but still struggle to interpret what they’re seeing. Object Recognition is a discipline in computer science that tackles this challenge, a vital component to replicating natural human interaction in the AI stack.
Augmented and Virtual Reality – Augmented reality (AR) is an interactive computing experience laid over the top of a real-world environment. Objects that reside in the actual-world are enhanced by computer-generated perceptual information. Imagine pointing your phone’s camera at a shopping high street and seeing offers and deals floating above the shops in view. Virtual reality is a fully-immersive simulated environment that replaces the real world. Both are being used in the AI stack to create richer digital interaction experiences for customers.
We hope this brief rundown of the computing power that’s driving the business AI revolution has been helpful. Next, we’ll walk you through products and services that are available now through our vendor partners so you can leverage the AI stack to create all kinds of automated workflows.
If you’ve been contemplating the implementation of AI technology into your contact center, contact us at City Communications. We can help you make the right decisions to maximize your return on investment and explore new technologies for your contact center
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