Artificial Intelligence: What Is It, and How Exactly Is It Used in Your Contact Center Tools?

This is the year of automation, and with that everyone is talking about Artificial Intelligence (AI). But what does that mean?

IBM defines AI as leveraging computers and machines to mimic the problem-solving and decision-making capabilities of the human mind. However, this doesn’t mean a tool with AI is fully self-sufficient. The AI component can be as small as collecting your customer’s search history and suggesting similar products, or as complex as self-driving cars.

There are plenty of tools out there that claim AI capabilities, but that can come in many shapes and sizes, so it’s important to understand exactly what the AI component is, and how your tool utilizes it to help your cause.

  • Is AI improving internal system efficiencies?
  • Is it optimizing your marketing efforts?
  • Is it tracking and analyzing your data?
  • Is it improving your customer experience?
  • Is it detecting tone in your customer interactions?

“AI” is a shiny buzzword that we’re all attracted to, but when selecting vendors or tools that offer this skill, you’ll need to understand exactly what the AI component is and if it matches with your end improvement goal.

Let’s dig into some examples of how Callzilla utilizes AI in our tools and services.


We utilize TomBot as our ChatBot platform, which is a very user-friendly service for both customers and creators. Creating a custom ChatBot from scratch, we determine basic business rules for the bot to follow and input specific questions and answers that we anticipate to come up. We refer to these anticipated questions as expressions and the answers are flows. These can be a simple input/outputs, or a complex web that directs customers through the conversion.

Since we obviously can’t anticipate every question that customers will have (or every version of that question), that’s where AI comes in. TomBot’s self-learning tool pulls out untrained queries and places them in a separate tab in the platform for review. Untrained queries are the expressions or customer questions/concerns that we hadn’t previously trained the bot to address. The self-learning tool then analyzes the new expression, and takes its best guess at an appropriate response based on the flows we already have set up. If it is 80% certain of its response, it will automatically respond to the customer and add the expression to the associated flow on the backend. If it’s less than 80% certain, it will still take its best guess but leave the expression for the bot moderator to manually accept or change.

For more details on this process, check out our more detailed blog post on our ChatBot’s AI capabilities.


A similar structure to ChatBot, the purpose of our VoiceBot is to interact with customers with a similar cadence to a live conversation with an agent. However, this tool utilizes AI in a slightly different way. We manually implement a decision tree in the backend of the bot, so it has guidelines for the conversation. Within that decision tree, we set “if/then” rules for if the customer says “this”, then take “this” path. We have the option to implement pre-recorded messages throughout, or utilize a text-to-speech option which does it’s best to sound human-like.

AI is used in this case to analyze the customers responses to the prompts, convert them to text, and then follow the decision tree accordingly. This conversational virtual assistant could be utilized for something simple as an inbound IVR that directs customers to the correct department based on their needs, or a full-fledged conversation to qualify them for a special promotion. This comes with a cost saving for our clients who can use the VoiceBot as tier 1 support and save agents for more complicated phone calls, but it also comes with benefits to the customer. Since the bot can handle multiple calls at once, the wait time is reduced, and customers get where they need to go much faster.

Check out our blog post for 10 ways to utilize VoiceBot in your business.

Speech Analytics

Our Speech Analytics software powered by Observe.AI plays an important role in our quality assurance (QA) process. Our goal was to use AI to take over the time-consuming task of monitoring customer interactions so our Quality Analysts could focus their time and energy on the bigger picture, like analyzing patterns, developing action plans, and coaching agents.

For the manual piece, our QA Manager designates moments within the tool, which are the guidelines for what the tool should be looking for in each interaction. We categorize each moment as positive, negative, or neutral, and this lets the tool know how to rate the call when it detects these moments. Observe.AI then monitors and analyzes 100% of our call recordings with customer 3x per day, and then translates the audio into a written transcript. It flags the designated moments in each interaction, and then creates a QA score based on the guidelines we set. Most notably, it can recognize tone and emotion in the customer’s voice to determine satisfaction levels. This AI capability not only improves the efficiency of our QA team, but gives them more insight into trend tracking for a specific program or across the board. This team now plays a bigger role in the development of our agents, coordinating with the Operations and Training teams on a daily basis. Our efforts our shown in the improvement in our agent’s call handling and a strengthened customer experience.

For a deeper dive on moments and the speech analytics process, check out this blog post.


Meet your customers where they are! SMS is a text messaging service that can be utilized to reach consumers straight to their phones. This service can be utilized as a way to mass deliver announcements for your business, or as an interactive customer experience. We also offer an implementation through WhatsApp for global communication.

The AI component of SMS is similar to ChatBot. The bot communicates with customers based on predetermined business rules, but it can also learn from your customer’s responses to build its knowledge base.

For specific examples on how to implement SMS in a way that improves your customer experience, check out this blog post. 

You can find Callzilla’s full list of automation options on our website, here. Don’t hesitate to contact us to get your AI journey started! Our end goal is cost savings for our clients, and a better customer experience for your customers.

About the Author: Neal Topf

Neal Topf, a seasoned contact center expert, is dedicated to transforming customer experiences. With years of industry wisdom, he guides businesses to excellence. His articles provide actionable insights for live answering, tech support, appointment scheduling, and implementing automated services, ensuring unparalleled customer experiences and operational efficiency.