AI Customer Service: All You Need to Know + Examples

As the COVID-19 pandemic forced employees into remote positions, many training teams began using AI to construct simulations to test employee aptitude for handling various situations. Previously, the training involved a blend of classroom training, self-paced learning and a final assessment — a routine that’s much harder to implement in remote or hybrid offices. The right mix of customer service channels and AI tools can help you become more efficient and improve customer satisfaction. Customer expectations are higher than ever — 72% of consumers say they will remain loyal to companies that provide faster service. And 78% of service agents say it’s difficult to balance speed and quality, up from 63% since 2020.

Arist introduced a content creation assistant that allows users to build new courses with existing content. By effectively capturing knowledge and value that’s already been created, Arist is able to inspire learner confidence and drive learning initiatives with their customers and employees. Businesses must design intelligent experience engines, which assemble high-quality, end-to-end customer experiences using AI powered by customer data.

How to integrate artificial intelligence and customer service

They need the right tools to make swift, efficient decisions and provide the kind of personalized customer care needed in today’s competitive environment. AI solutions become virtual shopping assistants working together with human support agents for one purpose—leaving customers happy and satisfied with their shopping experience. By combining human intelligence with the efficiency and self-learning capabilities of AI, support workflows are streamlined. It allows for a better structure and, ultimately, better customer experience with shorter wait times.

Or if a customer is typing a very long question on your email form, it can suggest that they call in for more personalized support. For example, when you call your favorite company and an automated voice leads you through a series of prompts, that’s voice AI in action. That means you can use AI to determine how your customers are likely to behave based on their purchase history, buying habits, and personal preferences. With improved workflows, AI can give you better customer response metrics. By registering, you confirm that you agree to the processing of your personal data by Salesforce as described in the Privacy Statement.

Examples of AI and automation in customer support

That’s how you’ll train your own AI model to categorize data according to your specifications. Customers are happier when they get speedy support, artificial intelligence customer support and happy customers are stronger brand advocates. Unstructured data lacks a logical structure and does not fit into a predetermined framework.

What’s more, this technology has the potential to shift the way customer service solutions are developed. Introduced as “Macy’s on Call,” this smartphone-based assistant can provide personalized answers to customer queries. It can tell you where products or brands are located or what services and facilities are available in each store.

AI can improve customers’ experiences when implemented effectively by reducing wait times, tailoring experiences, and giving them more resources for solving problems without having to contact an agent. From customer service agents to the enterprises employing them, here’s what users on the back end can gain from AI. Agents can use as many tools as possible to help them bring a ticket to resolution efficiently, and AI can expand that toolbelt dramatically. By synthesizing data based on factors like ticket type, past resolution processes across team members, and even customer interaction history, AI can automate action recommendations to agents.

A generative user interface (GenUI) harnesses the power of GenAI to dynamically create a customer interface in real time in response to each user’s unique and specific requests. The resulting interface continuously adapts over time to account for the user’s navigation choices, behaviors, preferences, and context. In practical terms, this capability means that companies will no longer have to design a string of user interfaces. Instead, they will design automated systems that dynamically generate services, recommendations, and experiences in real time and become increasingly customized to suit users’ unique interests and characteristics. For designers, GenUI could transform the digital landscape by reducing manual design work, increasing sales, and democratizing design at scale. Implement a data management system that ensures a seamless flow, organizing and processing customer queries efficiently.

Some forms of AI technology can detect certain keywords and then respond with prompts. You can program AI to provide your internal team with answers to difficult questions. Dialpad’s real-time Assist (RTA) cards, for example, pop up on their agents’ screens when callers ask specific questions. Conversational AI can provide natural, human-like communication to your customers.

Let’s also examine its real business value and discuss what tomorrow may hold for CS with artificial intelligence in place. The recent rapid advances in generative AI are already transforming the ways in which companies manage their critical customer service functions. Now, companies must anticipate how the technology’s considerable capabilities could even more profoundly disrupt their business models. Exhibit 2 lays out the variety of use cases across the typical customer service journey—from initial customer contact to final response and resolution—that will likely be augmented by generative AI. For example, ING Turkey collaborated with conversational AI company, Sestek, to develop an intelligent, conversational interactive voice response (IVR) system to manage collection calls that are automatically diverted to it. This increased efficiency, freeing up support staff for other valuable interactions.