{"id":2961,"date":"2023-04-27T15:58:13","date_gmt":"2023-04-27T15:58:13","guid":{"rendered":"https:\/\/salarydistribution.com\/machine-learning\/2023\/04\/27\/what-is-agent-assist\/"},"modified":"2023-04-27T15:58:13","modified_gmt":"2023-04-27T15:58:13","slug":"what-is-agent-assist","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2023\/04\/27\/what-is-agent-assist\/","title":{"rendered":"What Is Agent Assist?"},"content":{"rendered":"
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\u201cPlease hold\u201d may be the two words that customers hate most \u2014 and that contact center agents take pains to avoid saying.<\/p>\n

Providing fast, accurate, helpful responses based on contextually relevant information is key to effective customer service. It\u2019s even better if answers are personalized and take into account how a customer might be feeling.<\/p>\n

All of this is made easier and quicker for human agents by what the industry calls agent assists.<\/p>\n

Agent assist technology uses AI and machine learning to provide facts and make real-time suggestions that help human agents across telecom, retail and other industries conduct conversations with customers.<\/p>\n

It can integrate with contact centers\u2019 existing applications, provide faster onboarding for agents, improve the accuracy and efficiency of their responses, and increase customer satisfaction and loyalty.<\/p>\n

How Agent Assist Technology Works<\/b><\/h2>\n

Agent assist technology gives human agents AI-powered information and real-time recommendations that can enhance their customer conversations.<\/p>\n

Taking conversations as input, agent assist technology outputs accurate, timely suggestions on how to best respond to queries \u2014 using a combination of automatic speech recognition (ASR)<\/a>, natural language processing (NLP), machine learning<\/a> and data analytics.<\/p>\n

While a customer speaks to a human agent, ASR tools \u2014 like the NVIDIA Riva<\/a> software development kit \u2014 transcribe speech into text, in real time. The text can then be run through NLP, AI and machine learning models that offer recommendations to the human agent by analyzing different aspects of the conversation.<\/p>\n

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First, AI models can evaluate the context of the conversation, identify topics and bring up relevant information for the human agent \u2014 like the customer\u2019s account data , a record of their previous inquiries, documents with recommended products and additional information to help resolve issues.<\/p>\n

Say a customer is looking to switch to a new phone plan. The agent assist could, for example, immediately display a chart on the human agent\u2019s screen comparing the company\u2019s offerings, which can be used as a reference throughout the conversation.<\/p>\n

Another AI model can perform sentiment analysis based on the words a customer is using.<\/p>\n

For example, if a customer says, \u201cI\u2019m extremely frustrated with my cellular reception,\u201d the agent assist would advise the human agent to approach the customer differently from a situation where the customer says, \u201cI am happy with my phone plan but am looking for something less expensive.\u201d<\/p>\n

It can even present a human agent with verbiage to consider using when soothing, encouraging, informing or otherwise guiding a customer toward conflict resolution.<\/p>\n

And, at a conversation\u2019s conclusion, agent assist technology can provide personalized, best next steps for the human agent to give the customer. It can also offer the human agent a summary of the interaction overall, along with feedback to inform future conversations and employee training.<\/p>\n

All such ASR, NLP and AI-powered capabilities come together in agent assist technology, which is becoming increasingly integral to businesses across industries.<\/p>\n

How Agent Assist Technology Helps Businesses, Customers<\/b><\/h2>\n

By tapping into agent assist technology, businesses can improve productivity, employee retention and customer satisfaction, among other benefits.<\/p>\n

For one, agent assist technology reduces contact center call times. Through NLP and intelligent routing algorithms, it can identify customer needs in real time, so human agents don\u2019t need to hunt for basic customer information or search databases for answers.<\/p>\n

Leading telecom provider T-Mobile<\/a> \u2014 which offers award-winning service across its Customer Experience Centers \u2014 uses agent assist technology to help tackle millions of daily customer care calls. The NVIDIA NeMo<\/a> framework helped the company achieve 10% higher accuracy for its ASR-generated transcripts across noisy environments, and Riva reduced latency for its agent assist by 10x. (Dive deeper into speech AI by watching T-Mobile\u2019s on-demand NVIDIA GTC session<\/a>.)<\/p>\n

Agent assist technology also speeds up the onboarding process for human agents, helping them quickly become familiar with the products and services offered by their organization. In addition, it empowers contact center employees to provide high levels of service while maintaining low levels of stress \u2014 which means higher employee retention for enterprises.<\/p>\n

Quicker, more accurate conflict resolution enabled by agent assist also leads to more positive contact center experiences, happier customers and increased loyalty for businesses.<\/p>\n

Use Cases Across Industries<\/b><\/h2>\n

Agent assist technology can be used across industries<\/a>, including:<\/p>\n