The News: Amazon Connect has launched new generative AI capabilities, driven by large language models (LLMs) and other foundation models (FMs) available through Amazon Bedrock. These enhancements join machine learning (ML) capabilities that are already in place within Amazon Connect. The announcements include the launch of Amazon Q in Connect, Amazon Connect Customer Profiles, Amazon Connect Lens, and Amazon Lex in Amazon Connect. More information on these additions can be found in the press release on the Amazon website.
New Generative AI Capabilities for Amazon Connect
Analyst Take: Amazon Web Services (AWS) re:Invent was certainly heavy with announcements. In the mix of it was the launch of several new generative AI capabilities within Amazon Connect, AWS’s cloud contact center solution. Good to see these enhancements, some of which are in alignment with the steady stream of generative AI-related announcements in the contact center space while others are a bit more unique and fully featured. All should help contact centers deliver a more friction free and personalized customer experience while providing back-end efficiencies and improved tools for agents.
Amazon Q in Connect
Amazon Q was introduced as a generative AI-powered assistant with a variety of use cases across an organization. More specifically to Amazon Connect, Amazon Q provides support to agents by generating real-time responses and recommended actions. This functionality can make for faster, smoother interactions.
With the ability to determine intent, Amazon Q can provide the agent with the most accurate and relevant information quickly, without needing to escalate to a supervisor or sort through unrelated information. In addition to the generated responses, agents can be guided through even complex interactions, potentially reducing training time. This capability is generally available.
Amazon Connect Customer Profiles
Personalization is a key part to a good customer service. The best way to get that full picture of a customer so that a tailored interaction can occur is through connecting data. The Amazon Connect Customer Profile feature helps to build a view of the customer that includes preferences, purchases, and interactions. This view is built via the new ability for contact center administrators to add data sources, which could include Adobe Analytics, Salesforce, ServiceNow, Zendesk, or Amazon Simple Storage Service (S3). Amazon Connect Customer Profiles can interpret data formats, content, and their relevance to customer profiles, greatly simplifying the process for organizations. Administrators can quickly and efficiently review, edit, and finalize customer profiles. This feature is now generally available.
Amazon Connect Lens
Another new feature introduced, Amazon Connect Contact Lens, also leverages generative AI but focuses on post-contact summarization for increased productivity. Post-interaction summaries are created and can identify sentiment, trends, and policy compliance. This last piece, policy compliance, is an interesting use case and an operational time saver. The auto-generated summaries save time for both agent and supervisor and can give managers a view into possible agent performance issues or areas of improvement. There is also a (non-paper!) trail of commitments that may have been made to customers to make sure that appropriate actions are taken. Amazon Connect Lens is currently available in preview.
Amazon Lex in Amazon Connect
Now generally available, Amazon Lex in Amazon Connect makes the process of building self-service chatbots and IVR systems easier as it allows contact center administrators to simply describe what they want for self-service in natural language. Even with less common question types, models are used to correctly make sense of a customer’s response. The example Amazon Connect gave: “If a customer says they want to reserve a hotel room for ‘Saturday and Sunday,’ the self-service system correctly interprets the response as ‘two nights’.” This example is a pretty solid demonstration of a self-service system that will not need to boot a customer out to an agent because of its inability to correctly interpret wording. Amazon Lex can also be used to create question and answer chatbots and IVRs.
According to AWS, there are more than 15 million customer interactions being handled by Amazon Connect every day. This latest round of enhancements will help support more friction-free interactions with agents having tools for improved productivity and supervisors having access to information that will allow for easier identification of agent performance issues. And for customers, a more personalized experience and potentially access to self-service that is easy to use and accurate.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
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Author Information
As a detail-oriented researcher, Sherril is expert at discovering, gathering and compiling industry and market data to create clear, actionable market and competitive intelligence. With deep experience in market analysis and segmentation she is a consummate collaborator with strong communication skills adept at supporting and forming relationships with cross-functional teams in all levels of organizations.
She brings more than 20 years of experience in technology research and marketing; prior to her current role, she was a Research Analyst at Omdia, authoring market and ecosystem reports on Artificial Intelligence, Robotics, and User Interface technologies. Sherril was previously Manager of Market Research at Intrado Life and Safety, providing competitive analysis and intelligence, business development support, and analyst relations.
Sherril holds a Master of Business Administration in Marketing from University of Colorado, Boulder and a Bachelor of Arts in Psychology from Rutgers University.
