Will AI eat call center jobs?

Technology analyst Gartner predicts that within three years, one in ten interactions with call center agents will be with bots thanks to advances in conversational artificial intelligence (AI), as well as the labor shortages and high human resource costs.

If that’s bad news for call center workers, it could save companies around $80 billion in labor costs by 2026, the analyst said.

Gartner estimates that there are approximately 17 million contact center agents worldwide today, and that these human agents can account for 95% of contact center costs.

10% automated interactions in 2026

The projected savings in labor costs by 2026 are much larger than Gartner’s current forecast that enterprises will spend approximately $1.99 billion on conversational AI solutions in 2022.

Still, the analyst predicts that automated interactions with contact center agents will grow from 1.6% of all interactions today to 10% in 2026.

Chatbots are already a common, and sometimes useful, feature on many websites in the insurance, banking, technology and other industries.

Advances at Google, Meta, Microsoft and AWS

Meanwhile, Google, Meta, Microsoft, and Amazon Web Services are making progress with their conversational AI systems, but these are based on cutting-edge use of large language models and other forms of AI to emulate conversations. between human beings.

Google last month opened up its AI Test Kitchen to give the public a taste of its LaMDA, or language model for dialog apps, but warned it was still prone to offensive statements. Similarly, Meta warned that it had not addressed security issues by opening its Blender Bot 3 to the public. These measures are not necessarily intended for call centers.

However, in June, AWS made its Amazon Lex automated chatbot designer available to all customers. Which the company says could help reduce the upfront cost and “long” process of designing a proper chatbot. It is aimed at those building chatbots for contact center services, websites, and messaging channels like Facebook Messenger.

In 2018, Google unveiled Google Duplex, which is available in most US states and some other markets. It helps smartphone owners to make reservations and buy tickets. At the time of its launch, some feared that Duplex would replace call centers. But so far this has not happened.

Gartner notes that call center operators may automate some or all contact center interactions through voice or applications such as chatbots, and therefore uses a fairly broad definition. It also means that there are many ways to implement “conversational AI” and calculate the savings.

Entrust the AI ​​with basic information

Not everyone is happy to find themselves talking to a robot and often want to get in touch with a real person to explain their problem. But having bots handle some basic information could save everyone time.

“While automating a full interaction – also known as ‘call containment’ or ‘deflection’ – can provide significant cost savings, partial ‘call containment’, such as automating the identification of customer name, contract number and reason for calling is also of interest,” said Daniel O’Connell, vice president analyst at Gartner.

“Capturing this information using AI could reduce interaction time by up to a third that would typically be handled by a human agent,” he said.

Expensive technology

But actually deploying conversational AI is difficult at scale. Gartner estimates the price of integrating such a system to be between $1,000 and $1,500 per conversational AI agent. However, some organizations have cited costs of up to $2,000 per agent.

The analyst believes that companies with 2,500 or more agents — and with sufficient budgets and technical resources — will lead the adoption charge. In other words, these are companies that can budget around $3.75 million for a conversational AI system and then fund it.

Post-implementation, conversational AI must be supported, updated, and maintained, which incurs additional ongoing costs. “Implementing conversational AI requires expensive professional resources in areas such as data analysis, knowledge graphs and natural language understanding,” says O’Connell. “Once built, conversational AI capabilities must be continually supported, updated and maintained, which incurs additional costs. »

Source: ZDNet.com

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