What Is Artificial Intelligence (AI)?
Artificial Intelligence (AI) has been a hot topic for a while, but the buzz around the topic has substantially increased since the release of Chat GPT in November 2022. So, what exactly is AI? Artificial Intelligence, or AI for short, is essentially the brainchild of humanity's attempt to make machines perform tasks that typically require human intelligence.
AI simulates human intelligence processes by machines, especially computer systems. In other words, it's the development of computer systems that can perform tasks such as visual perception, speech recognition, decision-making, and language translation. AI systems can learn from data and experiences, improving performance over time without being explicitly programmed for every task.
AI can be categorized into two types: Narrow or Weak AI and General or Strong AI. Narrow AI is designed to perform a specific task, like voice assistants or recommendation systems. General AI can understand, learn, and apply knowledge across a wide range of tasks at a human level.
AI techniques include machine learning, where algorithms enable computers to learn from and make predictions or decisions based on data, and deep learning, a subset of machine learning that involves neural networks with interconnected layers to simulate human brain activity.
How Can AI Affect Call Centers?
We know what AI is, but what we all want to know is how it will affect our lives in the future. AI will affect people the most who have repetitive jobs, and the problems that agents deal with in a call center tend to be redundant, such as checking on the status of a claim or helping a customer with a payment issue.
Consider this scenario: a customer wants to change their flight ticket to a different time. The agent they speak to might attempt to upsell special additions, which could irritate the customer if the special additions are not the right fit—however, the perks of AI lie in its capacity to excel in such situations. By leveraging a customer's historical data, AI can make more accurate recommendations for additional services, enhancing the overall experience.
AI enables computers to recognize many human languages and process the words, and it then determines how to respond in the most Natural Language Understanding (NLU) possible. Conversational AI happens when a customer interacts with a company's touchpoints, such as online via social media or live chat and over the phone.
AI is also used for sentiment analysis to determine Csat, customer retention, and agent self-coaching. For example, sentiment analytics flags negative customer interactions so that call center supervisors can jump in on the call to help an agent resolve an inquiry or problem to ensure a positive CX. Moreover, sentiment analytics can be used to coach agents to improve their CX delivery.
Agent self-coaching has been one of the biggest call center advancements that have taken place due to AI. With mySQM™ Customer Service QA software, coaching opportunities are identified and displayed on the dashboard so that agents can self-coach to improve QA scores and CX. This has made improving FCR and increasing CX performance much easier.
AI is not a wholesale replacement of human labor. Instead, it is a great tool that can be used to supplement human labor. For example, companies are implementing AI-powered applications that offer real-time guidance to agents during calls. For customer service, this means that AI is reshaping the nature of jobs rather than entirely displacing human involvement.
Will AI Replace Call Center Agents?
To answer the question that all call center agents have been wondering: Will AI replace call center agents? The answer is no. Although there are many aspects of the job that contact center AI can take over, such as improving operational efficiency, optimizing customer service, and gathering customer data, it cannot replace the human touch that is so crucial to good customer service.
SQM Group's research shows that 73% of call center professionals somewhat or completely agree that Artificial Intelligence will improve call center interactions for customer satisfaction.
Call center Artificial Intelligence enhances agent productivity by equipping agents with tools for faster and more effective decision-making. It also frees up valuable time by minimizing repetitive tasks. This dynamic contributes to your company's ability to deliver an outstanding customer experience and ensures the seamless operation of contact center services.
How Long Will It Take AI Technology to Handle 50% Or Greater of Calls Currently Handled by Live Agents?
SQM Group's research shows that most call center industry professionals believe it will take under five years for call center AI software to handle the majority of calls that human agents currently handle. We are on the brink of major changes in the call center industry. The emergence of call center artificial intelligence (AI) will drastically transform all aspects of operations and customer interactions through automated and personalized service.
Call center technology has become very complex in recent years. It is not uncommon for a call center to have sophisticated software applications such as intelligent routing, artificial intelligence, customer relationship management, customer service QA, omnichannel technology, and beyond. According to SQM research, 94% of industry professionals believe their company must implement new call center technology solutions to significantly improve customer service.
What Are the Benefits of Using AI In a Call Center?
Using AI in your call center can lead to substantial cost savings, and it can optimize your resources by freeing up call center employees' time. Even using AI for simple tasks such as collecting customer information at the beginning of the call can save your contact center thousands of dollars over the course of a year.
Here are 10 Benefits of using AI in a call center:
1. Reduces Repetitive Tasks
AI dramatically reduces the pressure on call center agents by helping offload simplistic tasks that can be automated such as collecting customer information, writing interaction summary notes, and helping with routine inquiries or common problems.
AI's consistent performance isn't affected by factors like fatigue, mood swings, or external influences. This ensures a consistently high level of service quality.
2. Enhances Agent Job Satisfaction
Agents will be handling less simplistic call inquiries and common problems, so therefore they will be focusing on more complex customer inquiries and problems. This increases employee job satisfaction and allows contact center employees to take on more diversified and valuable tasks.
3. Enhanced Personalization
With its comprehensive understanding of individual customer histories and preferences, AI can offer highly personalized recommendations and solutions, leading to more tailored customer experiences. This also increases the likelihood of successfully upselling products or services.
For example, AI could provide agents with real-time product recommendations tailored to each customer's preferences and previous purchases. This helps agents offer personalized assistance to customers looking for product suggestions.
4. Automatic Call Routing
AI can optimize interactive voice response (IVR) by using conversational AI-empowered chat to support customers with more straightforward problems and route the call to an agent for more complex issues. AI can understand the general reason for the customer's call and, from there, can transfer the call to the associated department. This helps reduce your call center's average wait time (AWT) and increase first call resolution (FCR).
5. Agent Self-Coaching
AI-driven agent self-coaching stands out as a significant progression within call centers. With mySQM™ Customer Service QA software, potential coaching moments are pinpointed and displayed on the dashboard. Most importantly, it utilizes the agent's intrinsic motivation — their internal drive for achieving good QA and Csat scores, personal growth, and job satisfaction.
6. 24/7 Availability and Global Support
AI can provide round-the-clock customer support, eliminating the limitations of human work hours. This availability would also cater to global customers in different time zones. For multilingual customers, AI could offer real-time language translation, enabling agents to communicate effectively with customers who speak other languages.
7. Efficient Multitasking
AI can handle multiple tasks simultaneously, such as managing various customer interactions or performing data analysis in the background while assisting agents.
For example, while assisting human agents with calls, AI could simultaneously analyze real-time data from various sources, such as customer browsing behavior on the website, purchase history, and inventory levels.
8. Data Analysis and Insights
AI can process and analyze vast amounts of customer data in real time, generating valuable insights to inform business decisions and strategies. Data analytics software helps call centers process and analyze vast amounts of customer data efficiently and effectively. Without it, the data can be overwhelming, and extracting business insights that could streamline operations can be much more challenging.
Call center analytics is crucial because it enables managers and supervisors to make informed choices based on accurate and reliable data insights. This data-driven approach allows call centers to optimize resource allocation, enhance CX, improve agent training, and streamline operations, ultimately leading to higher Csat and better overall performance.
SQM’s Quality Assurance (QA) software captures and reports internal data (e.g., ACD, QA) and external data (e.g., web, email, and phone surveys) for agent accountability, agent self-coaching, and recognition. Reports with actionable insights powered by AI are displayed to agents and managers in real-time to continuously improve customer service.
Request a mySQM™ Customer Service QA Demo Video
Learn about SQM's agent… Csat prediction model, which is based on standardized metrics, AI, and regression analysis to predict customer satisfaction derived from a QA evaluation. Our Csat prediction model provides a high statistical correlation, translating to a 95% success rate in predicting agent Csat in most cases.
9. Human-AI Collaboration
AI can collaborate with human agents, assisting them in complex scenarios, suggesting solutions, and providing real-time guidance. For example, AI could provide an agent with suggestions for helping a customer, allowing the agent to resolve the customer's call reason more efficiently.
AI can also help guide an agent through customer interactions by analyzing the customer's voice tone, language, and sentiment to provide agents with insights about the customer's emotional state and possible issues. This support could be delivered via a chat interface or a dashboard.
If the customer has straightforward queries like checking account balances or verifying shipping status, AI could quickly retrieve relevant data and respond instantly to the agent. This minimizes wait times and improves efficiency.
10. Adaptive Learning
AI continuously learns from interactions and improves, resulting in an ever-evolving understanding of customer needs and preferences. Over time, it would refine its recommendations and support based on the successes of previous interactions.