Interactions with Generative AI: Q&A with Jay Choi on Gen AI

Generative AI (“Gen AI”) is one of the most exciting and disruptive technologies of its time: Its ability to create human-like responses to just about any prompt imaginable is changing the way that many are thinking about how we interact with technology. Generative AI has the potential to radically alter the landscape of many different areas of business, with customer service being one major space for innovation. 

Generative AI offers transformative new capabilities for customer service organizations, but AI is only part of the equation. To realize the value of these powerful new AI tools, they must be available at customers’ fingertips within existing interaction channels, and at agents’ fingertips, baked into their existing workflows. Glia’s newly enhanced universal AI Management framework enables financial institutions to do just that: It is a breakthrough tool that enables financial institutions to  seamlessly integrate AI and gen AI powered assistants directly into Glia’s interaction channels and agent workflows. This means financial institutions can build and introduce Generative AI assistants from leading companies like OpenAI, Anthropic, Google, Amazon, Microsoft and many others, and embed them into Glia, unlocking new efficiencies and functionalities.

We talked with Jay Choi, Glia’s Chief Product Officer, to learn more about Glia’s universal AI Management and the ways that generative AI is being utilized within the platform. 

Q: What motivated you to launch this new product?

A: We’ve been following the developments of generative AI for a long while now, and were impressed by the potential of this technology to enhance customer service and the customer experience. We saw that generative AI could not only help automate simple and repetitive tasks, but also handle complex and nuanced conversations, such as providing financial advice, resolving disputes, or upselling products.

We also realized that there was a gap in the market for a solution that could seamlessly integrate generative AI with existing customer service platforms. Many organizations have been focused on developing their generative AI model, but how it integrates into the overall agent and customer experience is usually an afterthought. Most generative AI solutions are also standalone products that require a lot of customization and integration work: We wanted to offer our customers a plug-and-play solution that could leverage any generative AI provider they choose, without compromising on quality or security.

Q: How does Glia AI Management work?

A: Our product is an extension of our existing platform, which already supports chat, voice, video, CoBrowsing, and AI. Our product allows our customers to connect their preferred generative AI provider to our platform via APIs. You’re then free to implement this AI system however you see fit: Be it directly interfacing with customers as a virtual assistant, or assisting your agents with pre-written responses and analytics. 

Q: What are the benefits of using Generative AI? What are its weaknesses?

A: As with all new technologies, there can be just as many reasons to be cautious about using it as there are reasons to be excited, and the risks of Generative AI are even more pronounced in financial services. With a good framework and smart implementation, however, you can get the most out of generative AI without needing to worry about any of the downsides that could come with it. 

The obvious positives that come from utilizing generative AI are the possible efficiency gains. It can reduce the workloads for your live service reps by automatically handling certain interactions, and can also help to improve the consistency and quality of those conversations. This can also provide the additional knock-on benefits of an improved customer experience, as users experience faster and more personalized service, as well as enhanced business outcomes from better identification of cross-selling and upselling opportunities. Generative AI can also help reduce churn by detecting and resolving customer issues automatically. 

On the other hand, there are risks associated with generative AI: Data quality and security immediately come to mind. As generative AI requires a large amount of data to train and operate effectively, you must be sure this data is high-quality, up-to-date, and compliant with security and privacy concerns. There is also the element of human oversight that must be considered: generative AI is ultimately unpredictable when it comes to the outputs you might get, so ensuring that human staff is still able to vet responses before they reach customers can be a great asset. We’ve been sure to address both of these concerns with our own AI Management framework, ensuring high-quality and industry-specific data as well as providing human agents with full access and simultaneous integration with the bots.

Q: What are your future plans for generative AI?

A: There’s clearly a lot of excitement around the capabilities of generative AI, and we definitely have a lot of plans for how we’re going to take advantage of it in the future. This includes expanding on the range of AI providers we support to give our consumers the maximum flexibility, enhancing the capabilities of generative AI to allow it to help out with more complex scenarios, as well as exploring new uses of generative AI within our workflows.

We’re fully committed to exploring the new possibilities for how generative AI is going to shape the future of customer service, and how we can use it to help provide excellent experiences for both financial institutions and their customers. We want to ensure that Glia delivers the best possible platform, taking advantage of new emerging technologies in ways that maximize their output and minimize their risk.