Generative AI in customer service: Benefits, Risks and the Future

Using artificial intelligence (AI) in customer service has gone from persona non grata to being more enthusiastically embraced than gräddtårta on Nationaldagen.

But here's the thing:

Many still don't know HOW to successfully implement AI in customer service, WHAT to expect, and WHY combining generative AI with conversational AI is the winning formula.

And who are we, if not the superheroes 🦸‍♀️ helping you bridge that knowledge gap with this blog post? So buckle up as we take you on a journey into the evolution of conversational and generative AI, exploring their benefits, risks, and how to use them effectively in customer service.

Ready? Let's go!

The Overpromise-phase

Although the first chatbot was developed as early as the mid-1960s, it wasn't until around 2010 that chatbots and artificial intelligence gained widespread popularity. This period, which we like to call The Overpromise Phase was marked by high expectations and ambitious goals.

Companies, including enterprises like Facebook, H&M, and Bank of America, invested substantial amounts of money in chatbot solutions. However, the technology wasn't yet intelligent enough to deliver on its promises. The chatbots developed during these years faced significant challenges in providing a seamless and satisfactory customer experience. They struggled to understand and interpret human language accurately, leading to frustrating and ineffective user interactions.

The Does it Work?-phase:

Fast forward to 2018, a crucial turning point in AI, particularly in natural language processing (NLP) technology. As mentioned earlier - before NLP, chatbots could only understand specific words and phrases. They couldn't understand different ways of saying things or complex sentences.

But NLP changed all that. NLP made chatbots smarter and improved their ability to understand the intended meaning behind people's words, even if they didn't use the exact keyword or phrase.

With this new AI technology, companies could start using chatbots for handling specific tasks and automating work. These chatbots were (still) not great at having human-like conversations, but they were efficient at solving specific problems. This phase we like to call the Does it work?-phase.

The Rise of Generative AI: a new era begins

Now, let's zoom ahead to 2023, a year when AI is once again making waves, thanks to the introduction of generative AI.

But before we dive into how generative AI has revolutionized chatbots and what possible challenges it brings, let's take a moment to sort out the difference between generative AI and conversational AI.

• Conversational AI: The technology powering most chatbots, utilizing natural language processing techniques to understand user input and respond accordingly. It focuses on understanding meaning, context, and emotions.

• Generative AI: Unlike conversational AI, generative AI can generate original and contextually fitting responses using advanced machine learning techniques. It learns from various data sources, including human conversations, to create human-like text.

Phew, terminology can sure be tedious, but sometimes it's necessary.

Now, back to 2023. ⬇️

This year will probably forever state a mark in AI history as the year that brought generative AI into the spotlight through the AI system called ChatGPT.

Introduced in December 2022, ChatGPT quickly became the fastest-growing AI system in history, attracting over 1 million users within a week of its launch. With ChatGPT, we witnessed a return to ambitious objectives and lofty anticipations reminiscent of the overpromise phase. However, this time, the chatbot technology didn't only meet those expectations but EXCEEDED them by far -- surpassing everything we could have ever imagined.

However, even if the technology IS groundbreaking, with the benefits come certain challenges, especially if using generative AI in customer service.

Generative AI in customer service 🤝

Generative AI brings numerous benefits, including more human-like conversations, smoother flows, and scalability.

However, incorporating generative AI into customer support also presents challenges.

❌ Misinterpretation and Errors.

Despite advancements, there may still be instances where generative AI models misinterpret customer queries or provide inaccurate responses. This challenge affects the reliability and accuracy of information delivered to customers, especially when it involves crucial details like order status or company policies.

❌ Privacy and Confidentiality.

Another major concern with generative AI in a business context is the potential sharing of personal customer information, which could lead to compliance issues and data breaches. There's also the risk of unintentionally revealing confidential information and threatening business secrets.

Related blog posts: Chatbot safety: potential threats and how to overcome them

❌ Lack of Actionability.

While generative AI models excel at generating content and are great at simulating a human-like conversation, they cannot perform actions on behalf of customers, such as retrieving order information from another system or assisting with logging into customer accounts.

Related blog posts: ChatGPT vs paid chatbot platforms - what sets them apart?

The solution: Combining Generative AI with Conversational AI

Do these challenges mean we should avoid using generative AI in customer service?

Hell, no! 🙅‍♂️🙅‍♂️

The solution lies in combining generative AI with conversational AI, creating a symbiotic approach that maximizes benefits and mitigates risks. Businesses can maintain more control over chatbot functionality by leveraging conversational AI with business-specific data and controlled integrations. Generative AI can then be applied to enhance the conversation experience, providing a more human-like interaction without compromising privacy or risking unintended data disclosures.

Conclusion:

Generative language models have undeniably transformed how we use AI chatbots and opened up new possibilities we never thought were possible.

However, challenges such as misinterpretation, privacy concerns, and lack of actionability need to be addressed. By combining generative AI with conversational AI, businesses can strike a balance between leveraging advanced technology and ensuring a secure, reliable, and customer-centric customer service experience. ✨

About Ebbot 🤖

Ebbot is a Swedish tech company specializing in Conversational AI, with live chat and AI chatbot solutions as our flagship products. Powered by advanced AI technology, our platform offers tools to automate customer interactions, enhance service efficiency, and deliver exceptional user experiences.

Psst..!

We have now launched our own GPT model - tailored for customer support and 100% GDPR compliant. Learn more about EbbotGPT here.

Feel free to reach out for a walkthrough of the platform or sign-up for a 30-day free trial.