Generative AI, an emerging form of artificial intelligence, has become a key factor in the contact center. Generative AI supports voice and audio, and adds advanced analytics capabilities to service-intensive contact centers, which benefit greatly from real-time data assistance.
Read on to learn how generative AI is being used in contact centers and how it can assist contact centers with security, ethics, and other best practices.
Table of Contents: Contact Centers and Generative AI
- How Is Generative AI Being Used in Contact Centers Today?
- Benefits of Using Generative AI in the Contact Center
- Generative AI in the Contact Center: Tips and Best Practices
- Bottom Line: Contact Centers Supported by Generative AI Technology
How Is Generative AI Being Used in Contact Centers Today?
Voice Generation for Customer Service and Client Calls
Though most people think of generative AI in the context of text or image generation, the technology has also come a long way in the areas of audio generation and voice synthesis.
With the right tools, contact centers can use artificial voices that are trained to sound human-like and take calls, answering complex questions and/or triaging calls to more experienced reps just as a human would. For contact centers where video calls are more common, artificial intelligence avatars can also be generated that both look and sound like a human employee.
Off-hours Customer Service Support
AI agents are particularly effective for international businesses, healthcare organizations, and contact centers that have trouble staffing their centers after regular business hours.
AI chatbots and agents can be on the clock 24/7 and never experience the fatigue or frustration that a human employee might feel if they worked these extended hours. As generative AI capabilities for these AI assistants and service reps continue to advance, they are becoming increasingly capable of handling complex tasks and customer requests without human intervention.
Also see: Top Generative AI Apps and Tools
Service Representative Coaching and Live Assistance
Generative AI contact center tools are frequently used to monitor human rep calls and give them feedback on how their tone is coming across, how customers are receiving that information, and other factors that may positively or negatively impact call outcomes.
Additionally, these tools are designed with administrators’ and managers’ needs in mind: although artificial intelligence can now handle most coaching tasks on its own, they also transparently share information about:
- Contact center rep evaluations.
- Previous coaching sessions.
- The number of evaluations each employee has received.
- Other data in a digestible dashboard format so managers can intervene and provide further coaching or disciplinary action if necessary.
Call Recording and Summarization
Generative artificial intelligence platforms go beyond simply recording contact center calls; they use their algorithmic training to help contact centers extract deeper intelligence and insights from call transcripts.
For example, if a customer service rep has a 30-minute call with a customer that touches on several issues and shifts tone throughout the conversation. In this case, certain generative AI solutions can quickly summarize this conversation in key bullet points, assess buyer sentiment at different points in the conversation, and make recommendations for how or if a rep from the contact center should follow up with this individual.
In many cases, these tools are also able to supplement information from the current conversation with past conversations, buying or patient history, and other data that informs employees about who this individual is and what they expect from the brand.
Omnichannel Content and Communication Enrichment
The modern contact center rarely sticks to traditional phone calls, often giving users the option to communicate with their reps via email, chatbot threads, and social media messages. When contact centers opt to use generative AI-driven chatbots and analytics tools, they can more easily embed intelligent assistance into all of the channels where customers choose to interact with them.
Because of this omnichannel approach enabled by modern AI, chatbots and AI assistants are frequently able to use their natural language skills and advanced search capabilities to extend useful learning resources and knowledge base materials to customers, helping to avoid the need for further contact center or customer service escalation.
Also see: Best Artificial Intelligence Software
Sentiment Analysis and Real-time Analytics
Live call monitoring is used for real-time analytics across a variety of demographic and customer data points. It can determine how customers are feeling and make recommendations for how to interact with individuals and customers better in the future.
Automated Follow Ups and Touchpoints
Contact centers have traditionally required reps to manually handle repetitive tasks, like accepting customer calls and messages, recording and reviewing transcripts, and following up with customers at regular intervals.
With the help of generative AI tools, many of these tasks, including reminders for these tasks, can be automated so employees are able to focus on more complex customer experience tasks. In the meantime, AI tools set up calls, emails, and other types of follow ups to ensure customers feel taken care of and are reached at key points in the customer lifecycle.
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Benefits of Generative AI in the Contact Center
Generative AI in the contact center helps businesses to better organize, automate, and respond to customer service needs. Some of the most important benefits that come from using generative AI in contact center settings include the following:
- Fill in the Gaps for Employee Shortages: Artificial intelligence can take on open roles for certain contact center tasks, like answering phones and preparing and analyzing call transcripts; generative AI agents are especially useful for 24/7 phone coverage and international availability.
- Real-Time Detailed Data Insights: Live coaching and performance tweaking opportunities are made more feasible with the help of generative AI data analytics. Both predictive and prescriptive analytics, with AI-driven recommendations, can be used to improve future call cadences and behaviors.
- Employee Training and Guidance: Employees can be trained during their calls to make better decisions and improve their conversational skills immediately with the help of AI coaches. Taking this approach avoids requiring human managers to listen to recordings and give feedback at a later time, when that feedback may be more difficult to apply.
- Learn and Improve After Each Customer Interaction: Generative AI tools themselves are trained to take customer queries and other data inputs and give customers the best possible answer. Beyond simply answering customer questions, these generative AI agents are trained to use this conversational data to improve how they interact with customers in the future.
Generative AI in the Contact Center: Best Practices
Using generative AI in the contact center can improve workflows for employees and outcomes for callers. But because of the nature of these tools and how they are trained, there are many AI-related cybersecurity and ethical considerations about AI that should be weighed when implementing contact center AI tools.
To ensure your team follows best practices that consider the wants and needs of the client, follow these tips:
- Adhere to Relevant Data Privacy and Usage Laws: This is especially important if you’re working in a highly regulated industry’s contact center, like a healthcare facility. For a better customer experience and to prevent legal action, go beyond the basics of data compliance and privacy laws and follow AI privacy best practices that put the customer first.
- Integrate and Embed Generative AI into Existing Tool Stacks: Contact centers should run like well-oiled machines, so it’s a good idea to invest in contact center tools that natively include generative AI capabilities or that integrate smoothly with generative AI tools like ChatGPT and GPT-4.
- Use Proven and Purpose-Built Contact Center Tools: Look for leading solutions from proven AI leaders and well-funded, innovative AI startups. Examples of leading generative AI contact center and e-commerce solutions include the following: Gridspace, Salesforce Einstein, Microsoft Copilot, Cresta, and Observe.ai.
- Monitor Customer Feedback Pre- and Post-AI Implementation: Generative AI agents, chatbots, and coaches may slip up occasionally, especially as they are learning how your customer base works. To catch their mistakes and train them for better outcomes in the future, continue to monitor their performance and how customers feel about AI-powered interactions.
Bottom Line: Contact Centers Supported by Generative AI Technology
Regardless of what tools you choose to use in your contact center, customers should not feel like they’ve been “left to the robots.”
For more complex call center scenarios or high value customers who are dissatisfied, humans should always be available to give them the personal touch they require. It’s also a good idea to ensure that human employees are continually vetting and updating pretrained AI responses to fit the times, buyer and/or user trends, and other changing customer expectations.
Ultimately, generative AI offers exciting new opportunities for customer engagement and automation for contact centers, but this technology must be used responsibly and thoughtfully. It’s most important that customers and employees feel that the contact center is being supported by AI rather than taken over by AI.
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