Call Center Automation: AI Tools, Key Benefits + How To

Artificial intelligence (AI) and call center automation are rapidly reshaping the industry, with Gartner predicting that over 80% of enterprises will use AI in their businesses by 2026—up from 5% in 2023.

These contact center automation solutions can speed up workflows by performing a wide range of manual tasks that don’t require human intervention (like summarizing calls, entering data, or evaluating interactions), freeing up agents to tackle more pressing customer queries.

Call center automation tools are here to stay, but are they making a real business impact? How do these technologies work, and are they right for your business needs? Are they replacing human agents, or enabling greater agent efficiency and job satisfaction?

In this article, we’ll show you exactly how AI-powered automation is impacting the customer service industry, the tech behind these, and how you can make the most out of generative AI in your call center.

9 emerging technologies in call center automation

90% of customer service leaders are reporting higher customer expectations and, thanks to the current AI boom, they’re turning to call center automation to meet these growing demands. What was once a slow, manual environment is being transformed via:

Conversational AI chatbots

Intelligent, AI-powered chatbots and virtual agents are now capable of handling complex issues using natural language processing (NLP). These bots can:

• Resolve routine inquiries
• Collect customer information
• Escalate to live agents when needed

Better yet, they’re available 24/7 and can scale instantly during peak periods—without compromising accurate responses.

AI-powered interactive voice response (IVR)

Modern IVR systems use speech recognition and machine learning to understand spoken language and route calls to the most suitable agent. Instead of facing frustrating menus, customers explain their needs and are directed accordingly, reducing wait times and improving first call resolution rates (FCR).

Predictive call routing

Predicting call routing uses customer data and machine learning to match callers with a suitable agent based on factors like previous interactions, the caller’s issue, and agent performance, in order to deliver:

• Personalized interactions

• Accurate answers

• Shorter wait times

Real-time assistance for agents

AI tools can offer in-the-moment coaching during live interactions, giving contact center agents real-time assistance via prompts, compliance reminders, and suggested answers based on customer intent and sentiment. This helps reduce training time and boosts consistency across your customer support.

Workforce engagement management (WEM)

WEM tools go beyond traditional scheduling by integrating performance analytics, training opportunities, and employee feedback into a single platform. With WEM, businesses can:

• Optimize staffing levels

• Reduce agent attrition

• Increase employee engagement

Voice biometrics

With voice biometrics, you can use automatic speech recognition to authenticate customers based on their unique vocal patterns, eliminating the need for passwords or security questions for a faster identity verification process. This helps deliver exceptional customer experiences while reducing the risk of fraud.

Customer sentiment analysis

Sentiment analysis tools analyze vocal tone, vocabulary, and pace to assess customer emotions in real time. Then, you can use this data to gain insights into your customer support and:

• Identify churn risks

• Detect and intervene before calls escalate

• Prioritize follow-ups more efficiently

AI-powered call center quality assurance

Traditional QA relies on manual sampling, which can only capture 1 to 3% of total conversation volume. With AI-powered QA, you can capture and evaluate 100% of interactions (voice, chat, email, etc.) to address issues, track compliance, and measure agent performance.

Omnichannel workflow orchestration

Automation tools can now coordinate customer interactions across all of your channels, from phone calls to social media. This helps preserve customer context as they move between communication channels, resulting in faster resolutions and fewer repeat questions.

What are the benefits of call center automation? 8 business outcomes

Call center automation solutions help your business solve common challenges in day-to-day operations. With generative AI call center solutions in place, you can automate time-consuming tasks, improve service quality, and manage growing demands without adding headcount.

Here are some of the biggest benefits of contact center automation today:

• Faster workflows: Intelligent automation streamlines repetitive tasks like call routing, data entry, and after-call work (ACW). This helps agents move through interactions faster and more efficiently, so they can focus on solving customer problems instead of doing paperwork.
• Reduced average handle time (AHT): Using real-time prompts, intelligent routing, and pre-filled customer data, call center automation cuts time per call. And, with shorter calls, agents are available more often, leading to better service levels and more resolutions. In fact, conversational AI is expected to handle 10% of all interactions by 2026.
• Improved customer satisfaction and first call resolution rates: When AI assists agents or handles inquiries independently, customers get faster, more accurate responses. This means fewer call transfers and a higher FCR rate—a must-have for 8 out of 10 customers.
• Easy scaling without adding headcount: As volumes increase, call center automation software can handle these added interactions via better self-service options. 77% of customers feel wait times are too long—so give them an option to skip the queue.
• Lower operational costs: Automating high-frequency tasks lowers your total cost per interaction. Plus, it reduces error rates and improves resource allocation, supporting increased operational efficiency across the board.
• Standardized policies and procedures: Call center automation enforces consistency by guiding agents through approved scripts and workflows. With that, agents are at a lower risk of noncompliance and deliver exceptional customer experiences each time.
• Fewer manual errors: Automated data capture and validation processes help prevent the common mistakes that come with manual data entry, leading to cleaner records and greater overall accuracy.
• Better insights: With AI-powered automation, contact centers are better able to gather and analyze the data they collect. This is most relevant in call center QA, where you can evolve from a typical 1 to 3% sample size to as much as 100% coverage.

How is AI used in call centers?

Robotic process automation (RPA)

RPA uses AI bots to complete repetitive, rules-based tasks that would otherwise take up valuable agent time. These bots can log customer data into your CRM, trigger account updates, verify information, and manage backend system workflows—all without human intervention.

And since they operate across different platforms, they can reduce delays and eliminate potential manual errors on a consistent basis. All of which gives your agents more time to focus on complex customer issues or the kind of work that needs human input.

Predictive analytics

Call center automation tools apply machine learning models to both historical and real-time data, so you can identify patterns to help anticipate future trends. This enables proactive analysis like:

• Forecasting conversation volumes

• Identifying customers at risk of churning

• Detecting shifts in customer sentiment

AI can also work in conjunction with your QA software to pinpoint agent behaviors that lead to higher first call resolution rates (FCR) and customer satisfaction (CSAT), so you can then try to replicate those behaviors across the customer service team. Or, on the other side of the coin, it can spot struggling agents and give coaches actionable data to help them improve.

Personalized customer experiences

71% of customers expect personalization and 60% are more likely to become repeat buyers after personalized interactions. Generative AI enables contact center automation tools to deliver these kind of tailored experiences on a greater scale by analyzing:

• Past interactions

• Behavioral cues

• Account history

With the ability to analyze all of this data instantly, AI call center solutions can then recommend tailored scripts, suggest relevant products for upselling and cross-selling, and even guide the conversation in real time.

This level of personalization helps customers feel understood from the very first touchpoint, leading to better engagement and brand loyalty. Call center automation can even anticipate needs and help you proactively reduce friction across the customer journey for better CX.

Workforce management (WFM)

AI-powered WFM tools take the guesswork out of scheduling and performance planning. They can generate optimized schedules that align with both customer needs and agent preferences by analyzing patterns in:

• Call volumes

• Agent availability

• Historical demand

They can also detect signs of agent fatigue and disengagement, giving you a chance to step in and make changes to avoid employee burnout or churn before they happen.

AI-enhanced reporting

Using call center automation, businesses can automatically collect and analyze data across every single customer interaction and channel. This helps you spot trends, anomalies, and performance gaps that may be missed in the manual reporting process.

AI-supported platforms also give you access to real-time dashboards that show QA scores, compliance issues, key performance indicators, and sentiment changes as they happen—all in one place. This gives you clear visibility and faster access to your most impactful metrics.

How call center automation empowers agents

Automation is not here to replace agents—it's a tool to make their jobs easier and less stressful while improving operational efficiency. These AI-powered systems work alongside your customer service team to eliminate friction, reduce manual workload, and create space for tackling bigger issues.

With the right tools in place, agents can focus more on delivering a great customer experience instead of system navigation and repetitive processes. Leveraging call center automation can:

• Make agents more efficient and less stressed. Automated workflows handle repetitive tasks like data entry, call routing, and form completion, giving agents more time to focus on resolving complex issues. That way, they feel less pressure during busy periods and are less likely to experience burnout.
• Offer real-time assistance and coaching. AI-driven tools offer live prompts, next-best-action suggestions, and reminders during calls. This allows agents to stay on track, follow procedures, and handle unfamiliar scenarios with greater confidence.
• Reduce after-call work (ACW). Contact center automation tools can summarize customer calls, log details into CRMs, and complete other ACW that eats up agent time. This shortens time between calls and boosts agent productivity without adding pressure.
• Support better emotional intelligence. When agents aren’t overwhelmed by context switching and multitasking, they have more time to focus on active listening and empathy. Automation frees up mental space, allowing for more human conversations.
• Provide sentiment analysis to guide interactions. Generative AI tools can detect customer tone and mood in real time via NLP, giving agents more insight into how the interaction is going. This allows them to adjust their tone, pace, or messaging to match the customer’s emotional state (or let supervisors know if there’s a possible escalation).
• Enable development with AI-powered QA. Automated QA tools provide consistent, objective feedback on every interaction. Agents get targeted coaching based on real conversations with customers, helping them learn faster and improve performance with actionable feedback and accurate data.

How to balance automation and human service: 5 tips

Call center automation can transform operations—but only when it’s used with care. To get the most out of AI (without losing the human touch), you need a strategy and mindset that keeps people at the center of the experience. Here’s how you can do it.

1. Remember that full automaton isn’t the goal

Automation is here to enhance, not replace, human service. While AI can handle routine tasks and mundane work, there’s no substitute for human empathy. Complex tasks and emotional interactions still require human input, so keep real people in the loop for empathy, nuance, and trust.

2. Establish hybrid AI + agent workflows

Use automation to support agents, not sideline them. Build workflows where generative AI handles the repetitive steps like information capture, data entry, or call summaries, while agents lead the customer conversation.

3. Focus on building customer trust

It’s not easy to build customer trust in the age of AI, so be open and transparent about your AI usage, and always make it easy for customers to reach a live agent. Trust grows when customers feel supported—not when they’re made to feel too unimportant to speak to a human.

Design your automation tools to solve the easy problems quickly, and then guide customers to real support agents when the situation calls for it.

4. Ensure your AI is accurate (and unbiased)

It’s crucial that you review your AI tools regularly across all channels and customer segments to ensure:

• Accuracy

• Fairness

• Performance

An AI system that misroutes calls or makes assumptions based on flawed data or biases can hurt your service quality and your brand’s reputation. There should always be a human in the loop to ensure AI tools are up-to-date, monitored, and working as intended.

5. Use AI with intention

41% of organizations struggle to define and measure the impact of their AI initiatives—it’s crucial that you don’t automate or add AI tools without knowing your ‘why’.

Only add software where it solves a clear problem or improves a key workflow. Every automation decision must align with your service goals, enhance quality, and make life easier for customers and agents. And you need to back it up with actual metrics to show that it works, too.

9 call center automation best practices

1. Map the customer journey first: Before introducing automation, figure out key customer touchpoints and where they might experience friction. Understanding the journey helps you decide where automation adds value and where the human touch still plays a key role.
2. Choose the best software: Not all automation platforms offer the same capabilities. Use tools that align with your business goals, compliance requirements, agent needs, and QA standards.
3. Integrate with your contact center tech stack: Automation works best when it connects with the rest of the software your call center uses—like your CRM, QA, WFM, and communications platforms. Integration eliminates data silos, allowing relevant information to travel freely between systems.
4. Start small and then scale: Kicking off with smaller pilot projects gives your teams the time and space to figure out what works—and what doesn’t. Implementing call center automation in small teams (or to target specific use cases) allows you to test, adjust, and refine before rolling out to the entire company.
5. Localize for different regions: If your call center supports multiple markets, tailor your automation workflows, languages, and scripts to meet their expectations. Localization improves customer satisfaction and avoids confusion in global operations.
6. Deploy change management strategies: Introducing automation requires cultural and operational changes, so you should prepare for it in advance. Communicate early with your customer service team, get agents involved, and provide ongoing training for a smooth transition.
7. Continuously assess the impact of automation: Use data to evaluate the impact of call center automation on key performance indicators (KPIs) like AHT, FCR rate, CSAT, and more. Regular reviews help you spot gaps, optimize performance, and make informed decisions.
8. Balance automation with live support options: Your customers should always have the option to talk to a human if they want to. AI tools should never block customers from getting the help they need—only guide them to it.
9. Build in feedback loops: Get both internal and external input to understand what’s working (and what isn’t). Then, use that agent and customer feedback to refine workflows and improve your automation strategies over time.

7 contact center automation trends for the future

Call centers are entering a new phase where AI doesn’t just support operations—it shapes strategy, too. These contact center automation trends are already gaining traction and will continue to influence how you design, manage, and optimize your customer experience. In the future, you can expect:

• AI-first contact centers growing in popularity: Call centers are shifting towards AI-first strategies, where self-service and automation tools handle the majority of routine interactions before humans intervene. This model helps streamline service while reserving live agents for complex tasks or high-value conversations, and supporting higher interaction volumes.
• AI augmentation for supervisors: Supervisors will increasingly use AI-driven dashboards that highlight agent performance, customer sentiment, and quality issues in real time. They allow for faster coaching, more informed decisions, and better insight into contact center processes.
• Voice and video chatbots: As customers adopt more communication channels, voice (and even video) chatbots will become more common. These bots use NLP and generative AI to deliver support that feels more natural, personal, and intuitive.
• A bigger focus on human agent experience: With automation handling more mundane tasks, there’s growing attention on improving agent wellbeing (and making sure they’re not being replaced). Expect more tools focused on reducing stress, delivering better training, and building career paths to upskill agents.
• Hyper-personalized customer experiences: AI will deliver even more tailored interactions by analyzing real-time behavior, preferences, and sentiment. From customized greetings to context-aware routing, personalization is becoming standard.
• End-to-end automation with conversational AI + RPA: The combination of AI and RPA will create seamless workflows from customer inquiry to resolution—without any agent involvement, in some cases. This will streamline operations, but also put a bigger focus on making human interactions more personal.
• Ethical, explainable AI is critical: As AI takes on more decision-making, there’s a significant push for transparency and accountability. Tools that explain how outcomes are reached—especially in routing, sentiment scoring, or QA—will become essential for maintaining trust.

Ensure effective call center automation with AI-powered QA

AI isn’t going away, with new models and advanced technologies still coming out every few months. Automation brings a ton of benefits to your call center—a better customer experience, lower operational costs, more efficient workflows, and happier agents, to name just a few.

But if you aren’t careful with how you implement, or you don’t maintain the human element, it can easily backfire, alienating customers and tanking employee satisfaction. An effective QA system plays a key role in maintaining the balance between human agents and AI tools, so you can ensure a hybrid approach that works as intended.

With Scorebuddy, you get access to an AI-powered QA system that can support your call center automation process. try our interactive demo now and see for yourself.