Up until recently, machines mainly focused on analyzing large, existing amounts of data and finding patterns for a multitude of use cases. This is called “traditional AI.” But lately, machines have also started creating new content. And this is now known as “generative AI.”
And given the rise of ChatGPT and its peers, generative artificial intelligence (AI) has quickly emerged as one of the most transformative technologies in recent years.
But how realistic is a meaningful shift from generating new content to transforming customer experiences in the short term?
The Background
Recent developments in large language models (LLMs) have enabled human-like, at-scale conversational experiences for users across domains.
Image Source: LivePerson
LLMs are a type of generative AI model that understands and generates text from patterns across billions of underlying words. They present an inflection point in the evolution of consumer-facing artificial intelligence, where AI can now understand users and respond with natural and
personalized answers. It essentially learns patterns from historical data and uses those learnings to create new content (whether code, synthetic data, text, image, audio, or video).
ChatGPT is perhaps one of the most widely-known use cases of generative AI. GPTs (generative pretrained transformers) are machine learning algorithms that can generate ideas, advice, human-like responses to questions, and more.
Image Source: OpenAI
The Use Cases for Generative AI in Customer Experience
Given these remarkable technological advances, generative AI now boasts the speed, accuracy, and underlying knowledge conducive to helping businesses build outstanding customer experiences.
And while there is a plethora of emerging generative AI tools on the market, which are addressing a variety of different use cases, there are a few particular areas within customer experience where these technologies are already having a meaningful and material impact.
Customer service & support chatbots
Chatbots and other customer service tools powered by generative AI can help businesses reduce costs while improving the customer experience. These technologies can produce immediate, relevant, and accurate conversational responses and provide customer support 24/7. And they can do so via an omnichannel approach – whether it’s via a website, chatbox, or SMS text support channel.
Tool spotlight: Intercom
This GPT-powered AI tool helps you instantly generate replies, recap conversations for other agents, and create new help articles. And it can help you resolve up to 50% of your support questions instantly.
Image Source: Intercom
User customization & personalization
Generative AI can provide customized user advice and recommendations, based on relevant data analysis.
For example, the technology can offer similar or complementary product recommendations based on past purchasing history.
Tool spotlight: Aidaptive
Founded by the Google AI team behind Google Ads and Payments, this AI tool is powering the next generation of commerce with an enterprise-grade artificial intelligence, machine learning, and predictive analytics platform built by the world’s top engineers.
The platform personalizes the shopping experience for every single visitor, thereby driving more conversions and revenue for businesses.
Image Source: Aidaptive
Marketing content generation
Generative AI can create high-quality content (or at least a solid first draft) for use across different marketing channels. For example, it can create engaging email campaigns quickly and easily. Furthermore, it can generate attention-grabbing social media content. Lastly, it can also create website content or blog posts.
Over time, leveraging the technology for this use case results in more content, lower costs, or resources re-allocated to higher-priority tasks.
Tool spotlight: Copy.ai
This AI tool will help you generate captivating marketing content, including social media posts. Copy.ai can help cut writing times by up to 80%.
Image Source: Copy.ai
Artwork creation
Generative AI can also create cutting-edge, original visuals, audio, and videos – for use on your website, in product demonstration videos, and elsewhere.
For example, you could opt for an AI tool that helps you create custom avatars by language, voice, appearance, and script. Or you could use an AI tool to create high-quality audio as background music for your website.
Tool spotlight: DALL-E
This AI tool generates original, realistic images and art from a text description. And it can combine concepts, attributes, and styles.
Image Source: DALL-E
The Key Takeaways
Generative AI has solidified itself across personal and professional use cases, significantly changing how users gather information and interact with innovative technologies.
However, while the technology continues to improve and evolve, several key challenges remain and should be effectively managed, particularly for use cases in customer experience.
Firstly, given its training reliance on historical but worldwide data, generative AI content should be checked for accuracy, relevance, and biases – particularly in more sensitive communication channels. Moreover, the technology could succumb to plagiarism by ignoring the original content’s creators. Thus, businesses should ensure to proofread any content before publication.
Secondly, generative AI operates with a generic voice. Thus, businesses should adjust any material content to ensure a consistent brand voice and personalized touch for their particular target customer.
Finally, numerous AI tools are springing up daily, and it takes patience to identify the optimal ones. Also, given their increasing popularity and usage, some free(mium) AI tools are experiencing timeouts and could prove inaccessible during critical times. In that case, paid AI tools might be the short-term winners in high-impact business areas.
And yes, while generative AI is still very early, its applications are already impactful. We can’t wait to see what else the future holds for this space.
