The Benefits of Voice AI Agents for Call Centers

• Integrating AI agents can significantly benefit traditional contact and call centers, reducing wait times and enhancing service quality.
• AI agents can significantly reduce the workload on human agents, thereby decreasing employee burnout and attrition.
• AI agents are transforming contact center operations, providing 24/7 customer support, automating order management, and collecting valuable feedback to inform business decisions.
• Deepgram's Voice AI Agent API works for developers building voice-powered AI agents tailored to contact center needs.

The contact and call center serves as the primary point of interaction for customers seeking assistance and resolving issues related to a business or organization.  However, these centers often face criticism for inadequate customer service, primarily due to long wait times that delay customers from quickly connecting with human agents.

High volumes of inbound calls and limited staff often cause these delays. This results in two major challenges: low Customer Satisfaction (CSAT) and employee burnout, which leads to high attrition.

So, how can contact centers address these problems? The answer lies in artificial intelligence (AI) agents.

AI agents are autonomous software systems capable of performing tasks without human supervision. These agents can also be equipped with voice technology to interact with customers via speech.

In this article, we will explore the following:

• The benefits of incorporating AI agents into the call center workflow
• Ways in which AI agents can enhance the efficiency of human agents
• Real-world use cases of AI agents in call centers
• An overview of Deepgram’s Voice AI Agent API and its applications in call centers

A typical contact center workflow involves inbound calls from customers with various queries, which human agents then handle. Let’s look at two possible call center workflows: Ideal vs. actual call center workflow.

Imagine an ideal world where the number of incoming calls perfectly matches the number of available human agents.

In this scenario, no customer would ever have to wait because each customer would be paired one-to-one with a human agent. However, this ideal situation is only possible if there are an infinite number of human agents available to handle calls, regardless of the volume. 

Of course, this is impossible. Even if a call center were to hire many agents to achieve this, it would be expensive and inefficient, as there would be times when agents would have no calls to handle.

As a result, the ideal contact center isn’t feasible in the real world. Let’s take a look at how a real call center operates.

During peak times in real call centers, there are often many customers and only a few human agents available to assist them. This creates a many-to-few situation where the high volume of customers outnumbers the available agents. As a result, customers are left waiting to be attended to.

Unfortunately, this is the reality of many call centers. Long wait times negatively impact the customer experience and lead to a higher call abandonment rate. However, this workflow can be significantly improved by utilizing AI agents. 

In the following section, we’ll explore how AI agents can optimize these processes.

Now that we've covered the real call center workflow, let’s explore some of the key challenges faced by traditional call centers.

During peak times, call centers often experience an influx of customer calls exceeding the available agents. This leads to long wait times, frustrating customers, and reduced satisfaction.

With fewer agents handling large volumes of calls, employees face high workloads. This constant pressure can lead to burnout, impacting both their performance and the quality of customer service.

Human error is inevitable in high-pressure environments. As agents juggle multiple tasks and calls, the quality of service may vary, leading to inconsistent customer experiences.

When calls are transferred between human agents, customers are often asked to repeat their information or explain their issues again. This not only wastes time but also adds to customer frustration.

Many traditional call centers operate only during regular business hours, leaving customers without support during evenings, weekends, or holidays, which can be inconvenient for those with urgent issues.

During seasonal spikes or emergencies, call centers struggle to handle the sudden influx of calls, leading to decreased efficiency in managing customer requests and providing timely support.

We’ve seen the workflow and challenges faced by traditional call centers. Now, let’s explore how AI agents can improve call center operations. Let's look at the workflow of a call center that utilizes AI agents.

In this workflow, we have customers and an infinite number of agents, including AI agents, to be exact. These AI agents can easily be spun up when a customer calls. The AI agents would try to resolve the customer’s issue, and if they couldn’t, they would route it to a human agent.

That’s the workflow of a call center using AI agents. Now, let’s explore how AI agents can help solve the challenges faced by call centers:

AI agents are not impacted by high call volumes; they can be easily deployed to assist customers. This means that even during peak hours, these agents are readily available to handle inquiries, ensuring that customer service remains efficient and responsive.

With AI agents, wait times are virtually eliminated. Customers are engaged immediately upon placing a call, ensuring they receive prompt assistance and enhancing their overall experience.

AI agents can efficiently manage routine calls to a call center, including frequently asked questions and simple requests. By handling these inquiries, these agents ensure that customers receive prompt assistance without feeling neglected, regardless of the simplicity of their task.

Consistent and accurate information is crucial for customer satisfaction. By standardizing responses, AI agents help reduce the risk of human error and miscommunication, leading to a more reliable and trustworthy customer experience.

With AI agents, call centers can provide support around the clock. This 24/7 availability means customers can access assistance anytime, improving service levels and accommodating those needing help outside traditional business hours.

AI agents significantly lighten human agents' workloads, especially during peak hours. This alleviation of pressure reduces stress and helps prevent burnout, allowing agents to maintain their performance and well-being while supporting customers.

AI agents significantly enhance the personalization of customer interactions. By accessing and retaining information about customers, including their past inquiries and preferences, these agents can tailor responses and solutions to meet individual needs.

AI agents are best suited to handle certain types of tasks. Let’s go through some of them:

• Customer Support: AI agents can handle routine customer support tasks, such as answering frequently asked questions, providing product or service information, and guiding customers through common processes.
• Order Management: AI agents can assist customers with tracking orders, processing returns, or making adjustments to their purchases. 
• Technical Assistance: AI agents can troubleshoot steps or solutions for basic technical issues. They can walk customers through device setups, software installations, or other routine tasks, minimizing the need for human intervention in common technical problems.
• Appointment Scheduling: With AI agents, customers can effortlessly make appointment calls to restaurants and hotels. The AI agents quickly check availability and confirm reservations, streamlining the process without human intervention.
• Feedback Collection: When collecting feedback, AI agents can make outbound calls to gather customer opinions through automated surveys. This allows businesses to efficiently capture feedback at scale, ensuring more consistent data collection for service improvement.
• Payment Processing: Customers can easily make payments with the help of AI agents, who securely guide them through bill payments, updating payment methods, or resolving billing issues. 
• Emergency Responses: In urgent situations, AI agents can provide immediate assistance by delivering critical information or escalating the call to the appropriate personnel. 
• Multilingual Support: Customers who speak different languages can easily interact with AI agents, which provide support in multiple languages. This ensures a seamless experience for a wider range of users, breaking down language barriers and improving accessibility.

Human and AI agents in call centers aren't in competition; instead, they complement each other by providing mutual support. AI agents are best suited for handling routine tasks that would otherwise burden human agents. The table below compares various aspects of the roles performed by human and AI agents in call centers.

From the table, we can see that AI agents are well-suited for tasks like automation, they are available 24/7 and can be scaled to handle large call volumes. In contrast, human agents excel at managing complex tasks that require critical thinking, empathy, and adaptability in decision-making.

A modern call center must thrive with a combination of human and AI agents. Relying only on one could limit the operation's overall effectiveness.

Many companies are already leveraging AI agents and reaping the benefits of this advanced technology. Let’s explore a few examples.

AGIA, an insurance broker and administrator, partnered with Sharpen to improve its contact center operations through AI agents. Sharpen, leveraging Deepgram's Voice AI solutions, helped AGIA achieve significant results. By incorporating AI agents, AGIA reduced its Average Handle Time by 12% and cut Average Hold Time by 23%, leading to annual savings of over $87,000.

Faced with a 5.4% decline in successful calls, a leading lender for multifamily and property loans partnered with Revenue.io to utilize AI agents for call analysis and performance improvement. By leveraging Deepgram’s ASR technology to train and customize a speech model based on audio from their platform, Revenue.io analyzed past calls to identify performance gaps. 

They discovered successful calls prioritized early discovery, while less effective ones jumped to product details too soon. Following a two-week pilot with real-time AI guidance, the team achieved a 43% increase in successful calls, transforming their overall approach.

Love's Travel Stops successfully integrated AI to handle routine calls, enabling their human agents to focus on complex issues. Partnering with Replicant, Love's improved efficiency by managing unpredictable call volumes and reduced agent attrition through AI automation. 

Over 180,000 calls have been handled by AI, cutting wait times and enhancing customer satisfaction. Additionally, the conversational AI system offers seamless, natural interactions, freeing up agents while delivering faster resolutions, and saving time and costs across their contact centers.

The Medicare Club, a healthcare startup that assists seniors with Medicare enrollment, implemented Grace AI Voice Agent from Gridspace to enhance their outbound calling efforts. This AI solution, designed with a clear voice for elderly customers, enables efficient engagement with potential clients while standardizing inquiries. 

The results were notable, achieving a 23% conversion rate and handling 78% calls in under two minutes. This partnership allows the Medicare Club to improve customer satisfaction and scale effectively as its business grows.

T-Mobile has teamed up with OpenAI to create IntentCX, an AI-driven platform set to debut in 2025. It is designed to enhance customer service through real-time intent and sentiment analysis. 

Leveraging T-Mobile's data and OpenAI’s AI expertise, IntentCX aims to resolve issues autonomously, offering personalized solutions and proactive support.

Building a voice-enabled AI agent requires multiple components to work together seamlessly. These include a large language model (LLM) for understanding and reasoning, Automatic Speech Recognition (ASR) to transcribe voice input, Speech Synthesis to generate realistic audio responses, and the underlying technology that supports real-time client communication. 

Recognizing these challenges, Deepgram developed an all-in-one solution called the Voice Agent API, which streamlines these elements into a single platform.

The Voice Agent API is built upon our advanced models, including Nova-2, which is recognized as the industry’s fastest and most accurate ASR model, and Aura, our cutting-edge speech synthesis model.

Additionally, there is flexibility in utilizing proprietary models, such as OpenAI’s GPT-4, or choosing open-source alternatives like Llama 3. This allows for selecting the most suitable solution tailored to specific needs.

The Voice Agent API offers numerous applications with significant potential in the call center industry. It enables companies to integrate AI agents into their existing call center systems.

The Voice Agent API streamlines the development of voice AI agents, allowing developers to concentrate on their core applications while we handle the complexities of voice integration and agent functionality. This enables organizations to enhance their offerings without managing voice technology.

The call and contact center industry stands to gain immensely from AI, particularly AI-powered agents. These agents allow call centers to handle unlimited calls, especially during peak times, effectively reducing customer wait times to zero. 

The benefits extend beyond customers; human agents also gain support from AI in managing routine tasks, enabling them to focus on more complex issues that require empathy and critical thinking. This synergy enhances overall efficiency and service quality in the industry, which is huge, especially for an industry known for its subpar customer service.

Despite the sophistication of the current technology, there’s still much to learn about human interaction with AI. As more companies adopt these solutions, we will identify pain points and gain insights to drive further improvements, ultimately shaping a more effective system that meets evolving customer needs.

At Deepgram, we offer a range of solutions for contact centers. Explore our contact center solution page to see how our partners successfully implement AI agents to enhance their operations.

Traditional call centers face issues that impact customer experience, including long wait times, frustrated customers, employee burnout, inconsistent service quality, repetitive information requests, limited hours, and difficulty handling sudden call volume increases.

AI agents can handle a high volume of calls, reducing customer wait times and improving overall satisfaction. They can automate routine tasks, freeing up human agents to focus on more complex issues. AI agents also provide consistent responses, 24/7 availability, and can help collect customer feedback and process payments.

AI agents in call centers excel at task automation, providing round-the-clock availability. They are easy to scale for high call volumes and handle straightforward tasks efficiently and consistently. In contrast, human agents bring empathy, intuition, and adaptability, making them more suited for complex interactions and sensitive customer needs. 

A Voice AI agent is an agent enhanced by voice technologies, such as speech-to-text and text-to-speech models. These agents can understand spoken language and generate speech responses, enabling natural and interactive communication with users.

Yes, AI agents can seamlessly integrate into existing call center systems. Partners of Deepgram, such as Sharpen, Replicant, and Revenue.io, offer solutions that facilitate this integration. Additionally, our Voice Agent API allows for the creation of custom solutions tailored to the specific needs of an existing call center.