Question 1

Will AI eventually replace contact centre agents?

Accepted Answer

We don't think that replacing human agents is the endgame here. That's not our goal at least, as we continue to design our CCAI. For us, AI technology is a complementary piece of an efficient contact centre or call centre team. It can help with self-service customer interactions, but we’re a long way from removing live agents altogether—if that's possible at all. That’s because computer systems still can’t quite deliver the same levels of empathy, emotional intelligence, and initiative that a human can. In our view, the best way to make the most of the technology is to pair it with the human element, enhancing agent capabilities and empowering agents rather than replacing them—for example, that's why we designed RTA cards to provide handy tips for agents and help steer them through tough questions. While smart automated tools take care of repetitive and time-consuming tasks, contact centre agents are still the best people for providing excellent customer service, especially to high-value prospects and customers. The fact that AI is so useful for coaching and support is also beneficial for employee retention in the high-churn contact centre industry. By giving agents the tools they need and reducing customer frustration, you’re creating a less-stressful workspace where humans are happy to stay.

Question 2

Are chatbots enough to handle customer support for small businesses?

Accepted Answer

Chatbots definitely have their place. Acting as virtual agents, they can often provide answers to simple questions about opening times and returns policies, or help customers deal with tasks like paying a bill, getting info about an account, making an appointment, signing up to a newsletter, or scheduling a callback from a live agent. There are plenty of customers who like to start with this option instead of using the phone to contact a business, as they can keep the chat going while they multitask—and interacting with a bot can prove faster than speaking to a real person. Some people just don’t like to talk on the phone, and who are we to judge? However, chatbots aren't 100% perfect. Some types of queries may still be too complex for them to handle, and although the latest versions include a degree of machine learning, it will take a bit of time for them to get up to speed. This is where conversational AI comes in, since it can learn and improve on its own—think of it as a much smarter chatbot. Reach out to learn how we designed Dialpad's conversational AI to address chatbot's biggest weaknesses! (Even small businesses often need more than one point of contact for customer support. Because every customer is different, it's best if you can offer omnichannel support—that means phone, email, SMS/MMS or instant messaging, social media, and even video calls. Fun fact: Dialpad Support is used by both small businesses and enterprises because of its intuitiveness and cost-effectiveness.)

Question 3

How can AI help facilitate customer self-service?

Accepted Answer

Although there will always be times when a customer needs to speak directly to a human agent, self-service options are a great way to empower customers to solve issues themselves. They have the added bonus of freeing up agents to handle other inquiries and tasks, too. AI enables smarter self-service solutions, and ensures that customers are only directed to this option if it’s the most suitable for them. By using conversational AI and voice recognition in IVR menus, your system can determine the nature of the inquiry and provide a simple answer—for example, if a customer was calling to ask about store opening hours, an agent wouldn’t need to get involved. It can point them toward the FAQ section or knowledge base on your website, or give them the option to leave a voicemail if there’s a queue. AI can also give customers the choice of requesting an in-queue callback, where they leave their details and an agent is notified to call them later. Using AI’s analysis of data and automated reports, you can view how your customers are using self-service options and make adjustments to improve the experience. (It’s also a great way to build and continuously refine your self-service options. If your records show certain questions come up a lot, you can make sure there’s a written answer easily available, which will reduce the number of incoming calls you’re likely to get!)

Question 4

What are some other contact centre AI use cases?

Accepted Answer

Beyond automating routine tasks and enhancing agent productivity, AI can be applied to a variety of other use cases in contact centres.  One such use case is predictive analytics, which can forecast customer behavior and identify trends to proactively address issues before they escalate.  AI can also enhance customer self-service options through intelligent virtual assistants, which can handle a wide range of inquiries and transactions without human intervention. Another significant use case is sentiment analysis, which allows contact centres to gauge customer emotions during interactions, providing valuable insights that can help tailor responses and improve customer satisfaction.  AI can also optimize workforce management by predicting call volumes and scheduling agents accordingly to ensure optimal coverage.  Additionally, AI-driven quality assurance systems can automatically evaluate and score agent performance, providing consistent and objective feedback to help agents improve their skills.  These diverse applications of AI demonstrate its potential to transform contact center operations and elevate the overall customer experience.

Question 5

What is agentic AI and how will it enhance contact centre experiences?

Accepted Answer

Agentic AI refers to a new class of artificial intelligence that goes beyond traditional generative AI by autonomously acting on your behalf — not just generating responses or insights, but planning, reasoning, and executing multi-step tasks with minimal human intervention. Unlike basic automation or scripted chatbots, agentic AI understands context, makes decisions, learns over time, and interacts with systems to complete complex workflows end to end. In contact centres, this means AI that can proactively resolve issues such as booking appointments, tracking orders, updating records, or initiating follow-ups without requiring an agent to trigger each step manually. It represents a shift from AI that assists to AI that acts, helping to reduce routine work and enabling agents to focus on higher-value, customer-focused interactions. Common contact centre use cases for agentic AI include handling after-hours enquiries, triaging and intelligently routing incoming calls, scheduling and modifying appointments, and providing real-time order status updates. When situations require empathy or complex judgement, agentic AI can escalate interactions to a human agent with full context. These capabilities also allow organisations to scale contact centre operations more efficiently, supporting higher volumes and extended hours without relying on BPOs or additional domestic hiring.

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AI Agents to automate routine contact centre interactions

Real-time call transcriptions for faster coaching

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Track keywords to uncover trends across customer conversations

Protect customer relationships with real-time sentiment analysis

Increase QA efficiency with automated scorecards

[AI Live Coach Cards] really helped us build out the way we train CSRs, [as it] pulls up guidance for them right away as opposed to making them reach out to someone else.

Jude Tungul
Business Operations and Intelligence Manager at Westward360

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I love AI CSAT because people tend to respond to surveys if they're very happy or very mad. But if you're neutral, you don't respond. So the AI-driven customer satisfaction score gives us that texture that we miss when it's customer-generated.

Brooks McClary
Senior Director of Sales Performance at BNI

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