Artificial intelligence is increasingly being used in customer interactions, but it is important for companies to be able to explain the decisions made by their systems, to give greater transparency to a world, in some cases, still viewed with distrust by users. That is why explainability in AI has become a priority as organizations seek to make automated processes more understandable and reliable.
What is Explainability in AI?
When it comes to Explainability applied to AI., we refer to the ability to understand and explain how artificial intelligence models make decisions. In other words, it is about making AI decision-making transparent so that it is understandable to humans. Explainability is critical to ensure that decisions made by AI are justified without compromising the efficiency and accuracy of the models.
Explaining decisions helps improve systems
By refining the explanatory capabilities, it is possible to identify any biases and errors in the model and make necessary updates to prevent this pattern from repeating itself.
Transparency increases customer and partner trust
With a clear and limpid communication mode in explaining its machine learning processes, one is also more trustworthy to possible customers and partners who will see the brand as a guarantee.
Bias, referring to the AI world, refers to artificial intelligence systems that systematically and unjustifiably produce less favorable, unfair, or harmful outcomes for members of specific groups of people. Usually these biases reflect socially widespread opinions and preconceptions such as, for example, those about race, gender, biological sex, age, and culture.
Explainability in customer care
In managing interactions with end customers, it is critical that companies are able to explain the rationale behind the responses provided by chatbots or virtual assistants.
The importance of Explainability in Customer Care
Leveraging the explanatory capabilities of artificial intelligence in the contact center world proves to be very important for, essentially, 3 main reasons:
- Improves customer trust: explainability applied to the customer journey enables customers to understand the decisions made by AI during customer service interaction. When a customer understands why a particular decision was made, it increases trust in the company and in AI itself.
- It helps to handle any complaints and requests for clarification: if processes are obvious and clear, any difficulties in interacting with particularly difficult users also become more immediate, because there are no "hidden tricks" but the way algorithms learn and manage customer care is there for all to see.
- Explainability as a lever for continuous improvement: AI can make mistakes, but if explainability is built into the system, any problems can be quickly identified and corrected. Access to explanations of decisions allows possible errors to be identified and improvements to be made.
Explainability in XCALLY solutions
XCALLY understands the importance of explainability in AI in customer care. XCALLY's omnichannel suite uses advanced artificial intelligence algorithms that are designed to be transparent and explainable. This means that the decisions made by the AI during the customer interaction can be clearly understood and explained. XCALLY is committed to providing a high-quality customer experience based on understandable and reliable decisions.
XCALLY's Approach to Explainability in AI.
XCALLY takes a well-rounded approach with respect to explainability in AI, which includes the following aspects:
- Intuitive interface: The XCALLY suite offers an intuitive interface that enables customer care workers to easily visualize and understand the decisions made by the AI. They can access detailed explanations of how AI reached a particular conclusion.
- Data transparency: XCALLY ensures the transparency of data used by AI. Customer care practitioners can access information on data sources and metrics used to train models, enabling them to better understand the context of decisions made.
- Continuous monitoring and updates: XCALLY performs constant monitoring of AI performance and makes regular updates to improve the efficiency and accuracy of the system. This includes analyzing customer feedback and adapting artificial intelligence models to meet changing needs.
Benefits of applied explainability
- Customers best understand the answers of our virtual assistants
- Our experts can analyze the behavior of systems and optimize their performance
- Maximum transparency is guaranteed to partners who choose our solutions
Thanks to explainability, artificial intelligence systems become fully understandable and transparent, fundamental features for better managing customer interactions. Through the use of transparent and explainable algorithms, such as those offered by XCALLY, it is possible to ensure that the decisions made by AI are understandable, reliable, and can improve the customer experience. Choose XCALLY as your partner for omnichannel management of contact centers means gaining the benefits of a transparent, high-quality system that promotes trust, efficiency and innovation in customer care.
Don't wait any longer, find out how XCALLY can revolutionize your business and offer state-of-the-art customer care.
