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Gartner Predicts Conversational AI Will Reduce Contact Center Agent Labor Costs by $80 Billion in 2026

Gartner Forecasts Conversational AI End-User Spending to Reach Nearly $2 Billion in 2022

By 2026, conversational artificial intelligence (AI) deployments within contact centers will reduce agent labor costs by $80 billion, according to Gartner, Inc. Worldwide end-user spending on conversational AI solutions within contact centers is forecast to reach $1.99 billion in 2022.

“Gartner estimates that there are approximately 17 million contact center agents worldwide today,” said Daniel O’Connell, VP analyst at Gartner. “Many organizations are challenged by agent staff shortages and the need to curtail labor expenses, which can represent up to 95% of contact center costs. Conversational AI makes agents more efficient and effective, while also improving the customer experience.”

Gartner projects that one in 10 agent interactions will be automated by 2026, an increase from an estimated 1.6% of interactions today that are automated using AI. Conversational AI can automate all or part of a contact center customer interaction through both voice and digital channels, through voicebots or chatbots, and it is expected to have transformational benefits to customer service and support organizations within two years.

“While automating a full interaction – also known as call containment or deflection – corresponds to significant cost savings, there is also value in partial containment, such as automating the identification of a customer’s name, policy number and reason for calling. Capturing this information using AI could reduce up to a third of the interaction time that would typically be supported by a human agent,” said O’Connell.

Technical Complexity and Fragmented Vendor Landscape Limit Adoption

While the benefits of conversational AI are compelling, the technology is still maturing. A fragmented vendor landscape and complexity of deployments will result in measured adoption through the next two years.

“Implementing conversational AI requires expensive professional resources in areas such as data analytics, knowledge graphs and natural language understanding,” said O’Connell. “Once built, the conversational AI capabilities must be continuously supported, updated and maintained, resulting in additional costs.”

Complex, large-scale conversational AI deployments can take multiple years as more call flows are built out and existing call flows are fine-tuned for improvement. Gartner estimates integration pricing at $1,000 to $1,500 per conversational AI agent, though some organizations cite costs of up to $2,000 per agent. Therefore, early adoption of conversational AI will be primarily led by organizations with 2,500 or more agents with budget for the requisite technical resources.

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