Over the past year, we've seen the launch of ChatGPT, which has not only reshaped the frontiers of artificial intelligence, but also revolutionized the public's perception of AI technology. Because the launch of ChatGPT (and its successor tools) has moved AI out of cyberpunk fantasies and into a practical tool in everyday life, it has changed people's basic understanding of artificial intelligence. AI is no longer just a hot topic for the C-suite, but has become a tool that everyone can access and utilize. At the heart of this shift is the shift from simply understanding conversations to being able to create and process them. This leap from understanding natural language to generating natural language marks a big leap forward in AI technology.
The rise of generative AI (GenAI) has sparked a fundamental change in the way brands do business almost overnight. Not only does it help people write emails, write software, analyze data, but it also helps us better understand what our customers think and feel. In 2024, this impact has already extended to call center operations.
Customer service technology has come a long way, from traditional machines and taking notes on laptops, copying Q&A scripts in Word to using ChatGPT to automatically reply to customer questions. Modern businesses are leveraging AI models, using machine learning to create simulations of the work of human agents, and great progress has been made in processing efficiency, but meeting and exceeding customer expectations, the process experience of handling tickets, and emotional satisfaction are just as important.
Enter the AI-powered call center
What is an AI Call Center? On the basis of the original call center, artificial intelligence (AI) technology is used to manage multi-language, omni-channel, and query and interactive tasks throughout the customer life cycle to achieve the effect of helping enterprises improve customer satisfaction, improve team productivity and expand the scale of operations.
Common use cases for AI-powered call centersMake a text summary of a voice call and label it with a work order, without the need for manual operation by agents.
Translate the voice content into Chinese, and analyze the ** content for quality management and on-the-job training for customer service personnel.
Guide customers to digital channels such as official apps and social networks to reduce call volume.
Advantages of an AI call center
Improve customer satisfaction: According to Zendesk's 2024 Customer Experience Trends Report, 81% of consumers say that resolving inquiries or complaints quickly and accurately affects their purchasing decisions, and that faster responses are especially important. With chatbots, you can achieve 24-hour response, intelligent summarization capabilities, and save agents from manually summarizing practices so they can serve the next customer faster. Improve agent efficiency and productivity:Automation can handle routine tasks such as routing assignments, agent handling that assigns response skills based on channels, allowing agents to focus on more complex and valuable ticket handling. According to statistics, the average call center customer service needs to spend 102 minutes (17% of its time) for post-call wrap-up. With Zendesk AI, calls can be automatically summarized and a call log created so agents can save valuable time without having to double-check the completeness and accuracy of this part of the summarization. Expand operations and reduce call center costs:The report found that 71% of organizations primarily use digital channels for initial contact and use ** as the primary channel for resolving complex customer issues or escalations. In fact, consumers see their phones as a channel to solve subtle problems. AI can help support teams scale up by guiding customers through digital channels to make quick questions and direct requests. This can also reduce call center overhead, as digital channel communication costs are lower than ** fees. AI-driven QC&QA enables managers to quality control calls and train new agents. For example, AI-powered tools like Klaus automate QA by auditing and analyzing communication records, pinpointing areas for improvement, and automatically sending personalized feedback surveys. AI can also provide guidance to agents by providing real-time suggestions on how to resolve issues. AI's QA software proactively analyzes agent interactions, pinpoints conversations with positive or negative sentiment, identifies customer churn risk, and more. **Future workload and ensure quality:By collecting and analyzing historical data to understand future trends, customer behavior, and potential challenges. For example, call center workforce management tools (WFMs) such as Tymeshift leverage artificial intelligence to**: future workload, staffing required, and appropriate shift scheduling. These AI-powered WFM insights help call centers proactively optimize resource allocation and develop strategies to improve employee satisfaction.
Application of AI in call centers
CX leaders are constantly exploring new ways to integrate AI into customer service:
Improve self-service and knowledge managementAI optimizes customer self-service and knowledge management to reduce call volume. By deploying AI knowledge base software, customers were able to quickly access accurate information and handle common issues independently, while simplifying knowledge management for call center teams. For example, Zendesk Content Cues is able to check support conversations, identify deficiencies in help center content, and update outdated articles, while Zendesk's generative AI tools help support teams write self-service content with simple bullet points.
Reduce talk time with intelligent routing:AI reduces call time, prevents frequent transfers, and shortens customer wait times by intelligently routing agents to direct them to the right agent based on their skills, expertise, language, or past interactions.
Perform call quality controlAI helps with call quality control, reviewing call transcripts by analyzing them, leveraging AI-driven analytics tools to gather insights, and using AI algorithms to evaluate agent performance. This process not only improves the quality of conversations between agents and customers, but also identifies trends, customer preferences, and sentiment to help managers identify customer service training needs.
Reduce post-incident time:AI significantly reduces the amount of time agents spend on call summaries by automating tasks such as summarizing tickets and providing full transcriptions. AI-powered systems can analyze call recordings in real-time or after a call, generate accurate summaries, and use natural language processing (NLP) to identify key points and important details. This results in a concise summary that highlights key information such as customer complaints, solutions, and action items. In addition, AI call transcription tools convert spoken conversations into written text, either in real-time or from a recording. These summaries and transcriptions are automatically added to customer conversations, saving agents the effort of manually summarizing.
Detect customer sentiment:Artificial intelligence also plays a key role in detecting customer sentiment in call centers. AI utilizes NLP algorithms to analyze voice cues, intonation, and language patterns to determine customer sentiment in interactions. This allows agents to effectively assess the situation, respond appropriately, and escalate interactions when necessary, especially when dealing with negativity. When strong negative emotions are detected, AI can automatically escalate interactions by alerting managers or shifting the call to a more experienced agent or department, providing faster, more proactive support and improving the customer experience.
Call Center AI Trends for 2024
Zendesk's 2024 Customer Experience Trends Report provides an in-depth look at the top three trends in the call center space:
The continued importance of speech and human interaction
Despite the growing number of digital methods such as chatbots and automated emails, customers still tend to communicate with a real person when faced with complex issues. According to statistics, 71% of organizations first engage with customers through digital channels, but still rely on human service when it comes to solving complex problems or escalating processing. This phenomenon underscores the continued importance of human touch in the customer experience. 
**The rise of sexual customer service management tools
Leveraging AI for workload** and agent management will help call centers allocate human resources more efficiently and improve service efficiency. However, 69% of customer experience leaders say that accurately** future workforce needs remain a significant challenge. This challenge underscores how much we can do to optimize resource allocation and improve efficiency. 
Emphasize immediacy and real-time interaction in customer service
Customers increasingly expect an immediate, personalized and efficient service experience, requiring call centers that can respond quickly and deliver real-time interactions. According to the data, 80% of consumers expect chat and support agents to be effective in helping them solve their problems. This underscores the importance of real-time and instant interaction in customer service.
Best practices for implementing AI in call centers
Before introducing AI, it is key to have clear goals and expected outcomes to help ensure that AI implementation aligns with the organization's business strategy and customer service goals. How to add AI capabilities to your customer call center, we recommend the following:
Define goals and objectives:Establish clear, achievable goals for AI implementations that align with business strategy and focus on improving customer satisfaction, reducing costs, or increasing agent productivity.
Take advantage of the free trial:Start with a free trial of call center AI software to evaluate its compatibility with your business needs and customer experience strategy.
Provide customer service training and change managementProvide customer service training to help agents become proficient in the use of new AI tools. Emphasize the important role of customer service to alleviate vicarious concerns and promote the acceptance of AI. Because of the management and customer service's awareness of AI, according to our statistics, there is still a big cognitive gap.
Ensure data privacy and security:Strictly adhere to customer data privacy regulations and implement strong security measures to protect data processed by AI systems.
Evaluate and monitor AI performance:Continuously monitor AI performance and gather feedback for improvement, adapting AI models, workflows, and processes based on feedback and changing business needs.
AI-powered power for intelligent decision-making
AI-enhanced call center tools give your business the ability to easily handle more conversations while delivering a great customer experience without adding additional manpower. With a combination of generative AI, intelligent chatbots, QA** content summarization and transcription, and deep data-driven insights, your customer experience management will take it to the next level.
ZenDesk's integration of these advanced capabilities, with its expertise in the customer experience space, naturally incorporates AI call center tools into our product portfolio to optimize customer service solutions. By adopting AI-driven customer service, you'll get intelligent knowledge management, efficient routing and classification capabilities, and granular sentiment analysis—all of the tools you need to improve the performance of your call center.
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Reference: CX Trend Report 2024