Calabrio’s 2023 State of the Contact Center report found that 97 percent of consumers cited their interactions with customer service as having a direct impact on brand loyalty.
This report comes as more and more organizations are turning to generative AI as a resource for contact centers, though more than two-thirds of contact center managers say they believe they will have more agents over the next decade, with AI being used as a tool to make their jobs easier.
Let’s review some of the generative AI solutions currently available for contact centers from Amazon Web Services (AWS), predicted contact center trends for 2024, and how organizations can leverage both to improve productivity, costs, and the customer experience overall.
AWS Generative AI Solutions for Contact Centers
AWS recently held the Generative AI-Powered Contact Center Transformation session of its Generative AI Use Case Enablement Series, which highlighted AWS services and Contact Center Intelligence (CCI) solutions presented by AWS Global Use Case Leader Amit Singh and AWS Principal Partner Solution Architect Andrea Friio, both of whom work in Generative AI Partner Acceleration.
“Contact center transformation is one of the most common and very popular use cases of generative AI,” says Singh. “There are some challenges, but generative AI can help provide the right kind of support, as well as augmentation in terms of improving productivity and driving better customer experience.”
When it comes to generative AI solutions for contact centers, Amazon Bedrock and Amazon SageMaker Jumpstart are the two flagship systems to start with, depending on your use case.
“I think that’s the beauty of it,” says Singh. “Because of the general purpose, nature, and the vast amount of data and the number of parameters these models have, they can be applied or further customized for a lot of different scenarios.”
Once you have chosen and refined the foundational models needed from either system for organization-wide or individual use cases, they can then be integrated with systems like Amazon Connect to run as a cloud-based contact center, with services including the following:
- Enhanced omnichannel self-service capabilities using natural language chatbots, interactive voice response, and automated customer voice authentication
- Real-time analytics to determine customer sentiment and determine escalation needs
- Empowering agents with communication history, applicable tools, and insights
- Automated personal customer experiences to streamline and organize next steps
“Imagine the possibility of not just sourcing all the internal knowledge of your customers, but also extracting [it] in a clever way, generating a meaningful answer while the agent is talking with the customer,” says Friio. “For the people out there that are used to dealing with the customer experience, it means potentially, when you need to transfer a call, you can transfer with a summarization.”
All user data remains private and protected thanks to AWS safeguards that let you implement your own privacy controls, including what individuals or systems have access, and the ability to encrypt data both in transit and at rest.
“We guarantee that no matter what solution—Bedrock or SageMaker—you choose, and which foundational model—third-party or first party—we will never provide [your data] to a third party,” says Friio. “Your confidential data will always be stored and encrypted in the security of your environment.”
Evaluating Contact Center AI Trends in 2024
When one of the most popular generative AI programs, ChatGPT, became publicly available on November 30, 2022, it set off a snowball effect that made this new technology more prevalent in both personal and professional capacities.
As such, 2023 saw an increase in the awareness, accessibility, and adoption of generative AI, and 2024 shows no signs that this trend will change any time soon, as evidenced by a Boston Consulting Group survey that found that 95 percent of global customer service leaders expect all customers will be served by an AI bot at some point in the next three years.
“We encourage you to start proof of concept to identify your customer use case, determine ferociously what the KPIs expected, and start the POC,” says Friio. “There is no barrier; it’s extremely simple; you deploy an architecture, you have the generative AI. Now, just to start the POC, you don’t need much else.”
Born Digital reports that 73 percent of customers now expect to have their specific needs understood through an omnichannel approach, with the ability to resume support using voice, chat, email, social media, or VR/AR, regardless of the channel they started with.
Additionally, Gartner estimates that conversational AI will be embedded in 40 percent of all enterprise applications in 2024, a sizable increase from the five percent reported in 2020.
“For the conversation analytics, typically with the post-call analytics, we have already a huge set of capabilities,” says Friio. “But for generative AI, now you have the capability of generating abstract summarizations . . . analysis of the data, prompts that can be included in the agent scripting; closing the loop from analyzing the data to provide insights that are really helpful to change the customer experience.”
Leveraging AWS for Contact Center Transformation
The three largest use cases—as defined by AWS—for implementing some form of generative AI in contact centers are as follows:
- Using self-service virtual agents to resolve customer queries with automated responses
- Assisting live agents to improve productivity through automation coaching
- Gaining insights into customer conversations and agent performance using analytics
“You can either decide to use the foundation models as-is, or you can connect them with the data sources and look at the retrieval augment generation architecture,” says Singh. “You can also bring in your data and customize or do the fine-tuning. You can try all of these different techniques in terms of getting the best result in terms of accuracy or performance, as well as the price point that you are constrained by. That can give you the right level of customization that you’re looking for, and the results that you want to drive for the use case.”
By transforming contact centers through improved contact communication for fast and effective resolutions and simplified management, AWS has helped organizations achieve an average 241 percent return on investment.
“In preliminary results, we are looking at boosting productivity in the range of 35 percent,” says Friio. “[This is] a significant improvement in customer satisfaction because of the consistent accuracy of the answer.”
Now that you have a better understanding of the generative AI contact center solutions available from AWS, what experts are predicting for 2024, and how you can best use both to improve your business, contact the experts at nClouds to get started with a no-cost consultation.
