AI-Driven Features of Cisco Webex Contact Center

AI-Driven Features of Cisco Webex Contact Center

During a January Cisco analyst briefing, Javed Khan, SVP/GM, Cisco Collaboration & Contact Center, and Jono Luk, VP Product Management, Webex Contact Center, shared progress around AI for the Webex portfolio and dug into contact center strategy. Khan reiterated that the view on AI is not just large language models (LLMs) but will also encompass a real-time media model that can extract audio and video intelligence. This functionality will be used across the Webex ecosystem, including contact center.

It was refreshing to hear the company’s measured approach to rolling out AI features, with Khan sharing that adoption is the key metric for full launch. Webex wants to see the AI functionality being widely used and proof points demonstrating it is making people’s lives easier via improved communication and collaboration. Right now, AI Assistant for Webex is currently in beta, and the company is receiving a lot of positive feedback from top brands trying it out.

AI Within the Webex Contact Center

At Cisco WebexOne this past fall, the team laid out a roadmap of Webex AI capabilities for its “built from the ground up” cloud contact center solution, and the company is showing progress against goals. Again, Luk emphasized that the solution aims to help companies drive proactive communication and engagement, have self-service to resolution using a virtual agent platform, and have the ability to bring in a human as needed to ensure issues are resolved with seamless transition. This “automate where you can, use humans where you must” approach is presented by Cisco as an ongoing cycle of optimization with the end result being less waiting time for customers and reductions in cost for companies.

Customer interactions and the channel that is chosen by customers to have them in is highly dependent on the nature and urgency of the issue, and while there is so much focus on digital, Luk pointed out that voice is still a very important channel and one that must be managed correctly and efficiently. This area is one where AI can support by understanding signals from voice and tone in real time. A new AI Codec in Webex will also be able to support higher quality audio interaction and will result in cleaner audio, that in turn will result in better interaction summaries that can be used for further analysis. The functionality for proactive outreach, background noise removal, and self service are all generally available today.

AI for Agent Support

Some of my favorite announcements and demos at WebexOne were the ones that focused on how AI would be used to support agents, who will be more frequently tasked with handling increasingly more complex and unique interactions. The Webex team provided an update on them and while none of these features are currently generally available, all should be rolled out over the course of this year.

The first one in the queue is a tool that helps agent wellbeing through agent burnout detection. Agent churn and the recurring need to recruit, hire, and train new employees is costly (and demoralizing!). Webex has implemented AI to detect fatigue in agents as their shift progresses through the day while analyzing sentiment to get a view into scenarios when a burnt out agent and an angry customer might collide. These situations can be brought to light, and agents have the opportunity to get a bit of a breather and reset. There is a partnership in place with Thrive Global to support this feature. Thrive Reset will be integrated into Webex Contact Center, delivering a science-based agent wellness solution in the form of 60 second reset, de-stress, and recharge breaks between customer interactions. Preliminary data is promising, with trial customers seeing up to a 3%-4% reduction in average handling time in certain cases. Trial customers have also seen a 13% reduction in agent stress level. This capability is currently in beta.

Other upcoming enhancements include:

  • Automatic conversation summaries and recommended next actions (Beta Q3 CY24)
  • Proprietary agent answers and suggested responses (Beta Q4 CY24)
  • Coaching highlights for supervisors (Beta Q4 CY24)

Key Takeaways

The use of AI in contact centers has predominantly been focused on practical use cases that can remove mundane activities, save time, increase efficiencies, and support self-service. With the ability to tap into the wide ranging Webex AI innovations, Webex Contact Center can more easily also use AI to really focus on areas that are a bit more unique, but no less important, such as audio quality. I look forward to seeing some of the other capabilities in the pipeline to be introduced this year that are more data focused, particularly the automatic customer satisfaction score and auto-generated customer sentiment insights, which will enable companies to more quickly see how customers are feeling without the need to rely on surveying.

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.

Other Insights from The Futurum Group:

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Unleashing the Power of AI: Cisco’s Bold Webex Strategy

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.


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