Understanding AI: Key Terms Every CX Leader Should Know
Artificial Intelligence is transforming customer experience and you want to keep up, but the terminology associated with AI can be confusing. To help you navigate the AI landscape, I’ve compiled a list of key terms and concepts that every CX leader should understand.
1. Artificial Intelligence (AI)
Definition: AI refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. These systems can perform tasks that typically require human intelligence, such as recognizing speech, making decisions, and translating languages.
Relevance to CX: AI can automate customer service tasks, provide personalized responses to customers through chatbots, and provide guidance to internal agents to streamline the customer experience.
2. Machine Learning (ML)
Definition: A subset of AI, machine learning involves the use of algorithms and statistical models to enable machines to improve their performance on tasks over time with experience.
Relevance to CX: ML algorithms can analyze customer data to identify patterns and predict future behaviors, enabling more personalized and effective customer interactions.
Example: A ML model identifies that a customer is engaging with your app in a way that suggests they might churn. You can then intervene and get the customer back on track.
3. Natural Language Processing (NLP)
Definition: NLP is a branch of AI that focuses on the interaction between computers and humans through natural language. It involves the ability of machines to understand, interpret, and generate human language.
Relevance to CX: NLP powers chatbots, virtual assistants, and other conversational AI tools that can interact with customers in a natural, human-like manner.
Example: A customer asks your chatbot a question, and it interprets the meaning of the question, pointing them to the right solution.
4. Generative AI
Definition: Generative AI refers to algorithms that can generate new content, such as text, images, or music, based on the data they have been trained on. Examples include GPT-4 (text generation) and DALL-E (image generation).
Relevance to CX: Generative AI powers a conversational experience with customers. It takes information it knows about your company, pairs that with NLP to have a human-like conversation that’s tailored to the customer.
Example: Your chatbot summarizes knowledge from your help center in a way that addresses the customer’s nuanced question while matching their tone.
5. Computer Vision
Definition: A field of AI that enables machines to interpret and understand visual information from the world, similar to how humans process images and videos.
Relevance to CX: Computer vision can be used for applications such as processing product returns, helping customers with troubleshooting, and reading transaction details from a picture.
Example: A customer sends your chatbot a picture of the error message on their device, and the AI reads it to get the customer the right solution.
6. Sentiment Analysis
Definition: A technique used in NLP to determine the emotional tone behind a body of text. It helps understand the sentiment expressed in customer reviews, social media posts, and other textual data.
Relevance to CX: Sentiment analysis can provide insights into customer satisfaction and help businesses respond proactively to negative feedback.
Example: A customer has sent in feedback, but is overall happy with your service. AI identifies this and doesn’t flag the feedback for immediate intervention.
7. AI Agent
Definition: A software entity designed to perform tasks autonomously or semi-autonomously, using artificial intelligence and machine learning to interact with and understand data, environments, and human inputs.
Relevance to CX: An AI Agent can provide tailored support to both customers and employees, taking action and offering guidance based on available information and platform integrations.
Example: A customer asks a chatbot for a refund. Based on refund policies and integration with billing systems, the AI Agent can make a decision on the refund and issue it.
Conclusion
Understanding these key AI terms and concepts is crucial for CX leaders looking to leverage AI to enhance customer experiences. By grasping these fundamentals, you can better evaluate AI solutions, implement effective strategies, and stay ahead in the rapidly evolving CX landscape.
I’m committed to helping businesses navigate the complexities of AI and harness its potential to transform customer experiences. Contact me today to learn more about how we can support your AI journey.
