For more than a decade, artificial intelligence (AI) has been steadily gaining ground as a force within customer experience (CX). It lends speed, scale, personalization and efficiency to manual or time-consuming tasks, enabling organizations to improve the way they serve customers in both business-to-business (B2B) and consumer (B2C) settings.
According to Boston Consulting Group, the percentage of companies that use AI has jumped from 22 percent in 2018 to 50 percent in 2023. Of these, 80 percent of leaders and 20 percent of frontline employees regularly use generative AI. Generative AI refers to the use of AI algorithms to generate new and unique content, such as text, images or even entire customer interactions.
The main uses of generative AI in CX
Initial applications of AI in CX focused on enabling companies to engage with B2B customers more effectively. For example, using AI to pinpoint relevant contacts within a customer's organization and understand their preferences, such as the best time to reach them and the types of devices and communications channels they use.
Predicting customer behavior is another common way to use AI in CX. This could be useful for understanding the next steps in the customer relationship, which prepares customers for what is to come and allows organizations to predict the propensity for customers to engage or renew.
AI can also be used to identify recommended actions to customers, which helps them understand the best ways to move forward, such as during the product or service adoption or renewal phases. The goal is to help them make progress with the products or services they have invested in and achieve value faster.
Today, as generative AI takes the world by storm, it is exciting to see the possibilities for its application in CX. When used correctly, it offers incredible potential for allowing CX professionals and their organizations to deliver more personalized, memorable experiences to customers.
Although generative AI is still in its infancy, it is already being deployed to enhance CX – using machine learning (ML), deep learning, or natural language processing (NLP) – in five key ways, as outlined below.
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Improve personalized customer interactions
Whether a company is large or small, if its leaders want to deliver CX at some level, they typically need to collect, retain and leverage customer data.
The insights this data holds lets CX teams better understand customer preferences, behaviors, and historical interactions – and take action where needed. But most (if not all) companies do not have the resources to effectively use their data to unleash high-quality, personalized interactions.
Generative AI changes all that, allowing organizations to automate how they create and deliver recommendations, tailored responses and even proactive suggestions based on ongoing data insights. The result is a highly personalized experience – one that demonstrates that a business really cares.
Engaging, real-time content creation
As the customer demand for greater personalization and immediacy continues to grow, it has become nearly impossible for businesses to engage them at the right place, at the right time and on the right channel without the power of automation and AI.
Generative AI can automate processes for creating dynamic, relevant content that maps to various touchpoints in the customer journey. Content assets ranging from product descriptions and email campaigns to social media posts and more can also be generated with the support of generative AI.
Furthermore, those assets do not have to be robotic just because they are developed by AI. As part of your prompt, simply ask your AI tool to generate friendly or engaging content.
Get more out of virtual assistants and chatbots
When trained using generative models, your virtual assistants and chatbots will become more contextually aware and will be able to interact with customers in a more human-like way. This, in turn, will unlock CX benefits like faster issue resolution for support cases and improved customer satisfaction.
Predict what customers want
We all want to know the future, and with generative AI, that is now a reality – in real-time. It can be used to quickly analyze historical customer data to develop predictive models that anticipate customer preferences and behaviors. This allows CX teams to proactively address customer pain points, anticipate demand and personalize recommendations.
Level-up voice and speech recognition
Backed by generative AI, voice and speech recognition technology is having a moment with the capability to yield more accurate and authentic customer interactions, including voice-activated customer support and voice-driven product recommendations.
As CX professionals increasingly embrace generative AI, the importance of using it ethically and responsibly cannot be underestimated. Transparency, privacy and human oversight are essential every step of the way to maintain continued trust with customers. Despite the cautions, CX leaders have every reason to be excited about the way generative AI stands to revolutionize our field.