Understanding AI and What Does the Future Hold for Contact Service Agents

How AI improves agent experiences

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The first “chatterbot,” ELIZA was developed at the Massachusetts Institute of Technology in the mid-1960s. Originally developed for a psychological setting, ELIZA would aid doctors treating patients.

First created to demonstrate the theory that communication between humans and machines would be superficial, chatbots have turned out to be key to customer service in today’s modern contact center.

How AI is being used now.

AI currently supplements the human workforce through the deployment of virtual agents, essentially chatbots that can handle frontline activities such as account or balance lookup, password resets, and other common, yet low-complexity activities.

Aided customer self-service is another current use case for AI in the contact centre. This type of assistance quickly provides relevant information to customers, helping to increase customer satisfaction (CSAT).

As time progressed, artificial intelligence solutions also aided human contact centre agents, prompting them with next-best actions, reducing data entry, and handling other mundane aspects of the role of an agent.

Solutions like Talkdesk Agent Assist provide agents answers or support to progress the conversation and simplify tasks such as searching product information. Agent assist technology provides human agents upsell and cross-sell opportunities based on access to database information on the products and services purchased by customers.

A third way that AI is being deployed in today’s contact centres is for data collection and analysis. The volume of customer data generated through the contact centre is vast and can provide a wide array of insights, including:

  • Conversational intelligence. Provides subjective insights into the customer’s mood, how empathetic the agent was, and other aspects such as sarcasm. This data is typically exclusive to voice interactions.
  • Interaction intelligence. Comprises an analysis of every aspect of the customer experience from the minute the customer dials the phone or engages a chatbot. This includes data like estimated wait time, compared with the actual time the customer waited to engage with an agent.
  • Contact centre intelligence. Analyzes every customer interaction—conversation, email thread, and text. Contact center intelligence provides a 360 view of contact center operations and can provide recommendations for improving the customer experience.

What the future looks like for AI.

To be clear, artificial intelligence and AI-enabled virtual agents will not replace human agents in the call centre any time soon. That said, the 2020-21 pandemic did prompt many contact centres to accelerate the adoption of AI-enhanced solutions.

Future contact centres will increasingly employ a hybrid model that combines AI and human interaction. With chatbots and guided self-service rising in efficiency in handling low-level customer inquiries, human agents will continue to address more complex issues and problem-solving—as well as providing the empathetic and personalized customer service that consumers demand. Here are a few future-looking applications of artificial intelligence to keep an eye on:

  • Pre-emptive customer service. With today’s connected smart devices, it’s possible that a future customer service engagement is not initiated by the consumer, but by a device. For example, if your connected refrigerator detects a fault, it can contact customer service without consumer input. Customer support can then research the potential error and proactively get in touch with the consumer, alerting them to the issue and scheduling a technician to come service the device. These connected devices can continuously collect data that informs the brand’s contact center for additional analysis and insight.
  • Specialized human agents. As AI-enabled technologies become smarter and address more complex issues, human agents will require additional training on the most complex customer interactions, perhaps specializing in a specific product or service area. This could also include analytics training that would provide the skills needed to make sense of all the data captured in the CRM.
  • New workforce makeup. When chatbots and other AI-assisted technologies become mainstream, different skills will be needed from human agents. Agent work will become more empathetic and relationship-oriented and will involve a higher level of upselling and cross-selling to existing customers. Empathetic agents will need analytical thinking, communications skills, and problem-solving acumen.

While AI-enabled technologies have made considerable inroads into the contact center, there is still much advancement that can be made in using these solutions to perfect customer service.

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