looking at conversational AI,” said Wang, “and we’ve taken these into consideration when compiling our ShortList of solutions.” Remembering ELIZA Cognigy’s enterprise software for CAI platform automates customer and employee communications. Available in on-premises and SaaS environments, Cognigy.AI enables enterprises to have natural language conversations with their users on any channel: webchat, SMS, voice and mobile apps – and in any language. “The origins of conversational AI date back to the 1960s with the first chatbot software developed at MIT in 1966,” said Cognigy’s senior vice president Hardy Myers. “It was a computer program named ELIZA that used natural language processing to emulate a psychotherapist’s responses to patients.” Of course, it would be years later when contact centers began to adopt CAI. Myers said that adoption paralleled advances in natural language processing and machine learning that have made chatbots and voicebots viable and complementary to (human) customer-facing and agent-enabling technology for improving CX. “Most enterprises today believe that delivering superior CX is critical to their current and future ability to compete,” Myers said. “Contact centers are embracing CAI as part of this mandate to improve CX while improving efficiency. “The necessity for CAI-driven automation in the contact center was further amplified during COVID-19, when the current generation of contact center technology and the existing labor pool were challenged to meet the increased service demand in certain verticals most impacted, e.g., airlines, health care providers and insurance carriers,” Myers said. CAI or AI? Despite the growing efficiency of CAI, many companies still promote their use of artificial intelligence (AI). So, what’s the difference? “IBM defines artificial intelligence as ‘technology that leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind,’” Myers said. “Conversational AI is the set of AI-based technologies that facilitate more natural conversations between humans and machines. “The practical application of CAI is the modern day chatbots and voicebots that you now experience when interacting with the contact centers of larger, more innovative organizations that are focused on transforming their customer experience,” he added. One reason some companies may not be switching from AI to CAI is cost, Myers suggested. “The latest generation of CAI technology is relatively new, and its benefits not yet widely understood. Other technologies that don’t have the same CX-transforming or efficiency impacting results can get prioritized.” CX is high priority Optimistically, Myers said the situation is changing because CX is such a high enterprise priority, and automated CAI solutions are necessary to help solve the problem. “Candidly, it’s incumbent on the leading CAI vendors to better educate customers of how transforming this technology is to their CX initiatives,” he said. Advantages to switching are “very clear and readily measurable,” Myers insisted, citing improved CX, improved efficiency and improved agent engagement. As examples he cited how service requests can be processed more efficiently with customers able to access their accounts 24/7. Also, agents can be onboarded more quickly, leading to lower training costs, higher agent availability and improved customer satisfaction. While there are advantages to CAI, limitations also exist. For starters, CAI is a new, complex technology with limited levels of industry expertise in design and deployment, while generic natural language understanding (NLU) models may not be “smart” enough to understand or speak accurately with customers in certain applications/ use cases. Solutions also can lack the flexibility to support legacy infrastructure and systems of record, while insight into activity or how to improve the results of a CAI deployment can be insufficient. To overcome these limitations, Cognigy has built a low-code enterprise CAI platform that is less complex and much easier to use resulting in faster and more successful deployments, said the company. It also developed a robust set of technical tools includWhich activities are the most time-consuming? Source: ICMI; Nice contact center sur vey Source: Palo Alto Networks Routine or mundane administrative tasks Routine or mundane customer interactions Trying to find the answer or information Training Reporting Coaching Sheduling and forecasting 26% 34% 18% 14% 17% 14% 17% 17% 8% 7% 11% 6% 9% Overall Agents What factors drove increases in volume and complexity? Source: ICMI; Nice contact center sur vey Number of customers Staff competnecy or training Use of additional channels, digital, and/or self-service channels Customer competency or education Compliance or security Number of staff Scope of services offered New systems, equipment, or devices 46% 34% 35% 35% 34% 45% 34% 39% 36% 19% 29% 22% 32% 33% 22% 20% Volume Complexity U.S. Employee Engagement Trend, Annual Averages % Engaged % Actively disengaged 26 18 16 17 15 20 18 19 19 17 14 30 28 30 28 29 30 32 33 3 26 19 REMOTE WORK SOLUTIONS rwsmagazine.com
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