With the emergence of ChatGPT, it became obvious how artificial intelligence (AI) customer service may look in the near future. Even though it’s been in use in companies to some degree behind the scenes, AI is now being used more robustly in team and customer-focused applications, like customer support chatbots and more, bringing it to the forefront. How can AI in customer service benefit companies and end users?
Behind the scenes, artificial intelligence (AI) has been getting weaved into back-office IT operations for years. But this year, it’s exploded into day-to-day conversation thanks to ChatGPT becoming accessible to the masses. According to PwC, 86% of people recognize AI as mainstream.
The impact of AI is profound. And moving fast. In 2018, global companies reported having 1.8 applications that used AI. In 2022, it doubled to 3.8. In 2024, the figure is predicted to become 488 applications, which is close to 4% of the IT budget.
Here are a few other AI projections that are breathtaking in their boldness:
- AI is projected to boost profitability in some industries by 38% on average by 2035.
- 90% of the processes and products of advanced enterprise apps will be supported by AI in the next 18 months.
- PwC estimates that AI may contribute 15.7 trillion to the global economy by 2030. (Yes, that’s a T!) That’s more than the combined output of China and India!
AI is rapidly changing jobs and our interactions with brands. Specifically, AI is showing up in new consumer-facing applications every day. Customer service is one of them.
How is AI improving customer service?
A few years ago, Aberdeen released a study that concluded companies using AI achieve a 3.5 times greater increase in customer satisfaction. It may seem counter-intuitive that when machines step in, customer satisfaction goes up!
Executives appear to be embracing AIs entry into customer service. During a 2023 Gartner webinar series, 2,600 executives were asked about their AI adoption - 38% said customer experience was their top driver for AI adoption, and only 17% cited cost optimization.
Six examples of AI in customer service today
What does AI-powered customer service look like in practice? Check out these real-world applications of AI, specific to customer support and customer experience management.
1. Internal knowledge delivery
AI helps surface answers quickly, locating and pulling out the necessary guidance that’s currently housed in a variety of resources.
Our CXMEngine customer experience management platform is one example of this. It uses AI to offer smart suggestions to our internal users so they can provide more accurate and faster service to customers by surfacing articles, suggesting tags that will make reporting and data analysis more robust and suggesting replies to end-users based on the conversation thread. AI customer support solutions can optimize performance by delivering knowledge to the right person at the right time.
2. Customer self-service
By integrating AI, specifically large language models, customer service has taken a remarkable jump. That advance is now becoming customer-facing, allowing end users to self-serve knowledge when they need it, using AI-empowered chatbots and sending queries to knowledge bases.
Chatbots, leveraging AI, have begun to deliver precise answers to end-user questions in seconds, removing the need for a customer to scan multiple help documents to find needed information. They receive answers faster and with much less effort on their part.
AI in customer service can drive up to 30% in cost savings.
In addition, AI-powered chatbots can help customers during off-hours, holidays, and otherwise busy periods in a more comprehensive way, so customers receive assistance and organizations can better manage resources during these challenging staffing hours.
Learn more about Messenger, our updated web chat tool.
3. AI-generated customer support summaries
Customers expect the companies they work with to know them… really know them. AI is making that easier by leveraging models like GPT-4, PaLM-2 to pull together customer interaction data into summaries of their history and engagements automatically.
Anyone servicing a customer will quickly see the full context of previous activity, including notes, conversations, events, resolution steps and even obstacles to resolution. In one place, in a single summation, they're provided with the history and context to better understand the comprehensive ongoing and future needs of the customer.
AI customer service tools can even string together multiple engagements to provide a holistic view of a customer’s customer service experience even when it crosses products, teams and organizations. These AI-powered summaries string disconnected interactions and contacts into a seamless view of the entire relationship.
4. Automated routine interactions
Intelligent chatbots can do more than just chat; they can be programmed to complete certain transactions. For example, some businesses allow customers to place orders, update contact information, or find nearby locations from a customer support chatbot on their website.
Customers appreciate an AI-powered messenger or chatbot that allows them to quickly schedule a service call, report an issue, or make changes to their account – all without waiting for a support agent to address them. Once again, this frees up support teams to assist other customers with complex customer servicing issues that require a human touch.
See OvationCXM’s Conversations module in action.
5. Intelligent routing
When customers cannot be fully helped by a virtual assistant, AI will use intelligent routing to direct the customer to the right teams or departments for further customer service. This smart routing can also be used for after-hours and holiday routing too.
6. Suggested responses, by channel
As generative AI is integrated into platform after platform, models like GPT-4, PaLM-2 and others can be used to enhance customer service replies based on conversation history, context and even sentiment. AI customer service tools can also locate similar customer service cases and recommend resolutions and highlight patterns in these similar cases to cut the time it takes to solve the issue and/or identify areas where the customer journey may need to be adjusted.
By 2024, it's predicted that the global chatbot market will be worth $9.4 billion.
It can also tailor these responses by channel, expanding the response for email or making it shorter and more concise for SMS or chat. Even as AI customizes responses by channel, it can ensure the brand’s voice remains consistent. Companies can use AI to set their tone of voice whether it's polished, friendly, formal, etc. to apply to every channel.
Using AI to deliver exceptional customer support
AI is an impressive tool to enhance customer service to keep up with the competition and meet constantly-shifting consumer expectations.
CXMEngine, our customer experience management (CXM) platform uses AI to empower users to be more efficient in customer service across any journey, and to instill greater loyalty and satisfaction through that customer experience. Our platform does it within guardrails that pull value from the AI while ensuring it supports the organization’s goals and brand promise.
Moving from touchpoints to customer journeys
We believe customer service experience should not be about optimizing a string of disconnected touch points. Instead, it should create seamless holistic customer journeys across different products, teams and even third-parties in a cohesive, singular experience that aligns with an organization's brand promise. Within this journey framework, our CXMEngine platform uses powerful drag-and-drop journey orchestration tools, plus AI to help automate and trigger next steps that ensure customers reach their goals and are satisfied with their experience.
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