How Call Center Automation Empowers Agents & Enhances CX

Efficiency is a top priority for call centers around the world. From high call volumes —the average call center receives 4,400 calls per month — to dizzyingly high customer expectations, call centers and the agents that work in them are under mounting pressure to move fast in order to reduce wait times, lower operating costs, and keep customers satisfied. This means that agents can hardly afford to waste valuable time on manual (and sometimes menial) tasks such as call routing and after-call work; however, these tasks are still essential to call center operations.

Fortunately, there’s a solution to these pain points: call center automation.

What Is Call Center Automation? 

At a high level, automation refers to the use of technology to complete tasks that would otherwise be manually performed by a human. In call centers, automation can take many different forms, with chatbots or virtual agents being the most common.  

Call Center Automation: 8 Use Cases 

Although automation has been something of a hot-button issue across various industries, with some detractors arguing that automation will replace workers, automation actually has the power to create jobs.

“The impact of AI on the customer service function cannot be overstated. Not only do we expect organizations to replace 20-30% of their agents with generative AI, but also anticipate it creating new jobs to implement such capabilities.” – Gartner

In fact, many call centers have had great success using automation to complement their existing workforce and make agents more productive by enabling them to focus on higher-value tasks. Check out these examples of how call center automation technology can help enhance efficiency and productivity:

Data Capture 

Given the vast volumes of data each customer service interaction has the potential to generate, extracting raw data from conversations for analysis purposes can be difficult — if not impossible — to do in real time. Call centers can simplify data capture using automated data collection platforms, which have the power to: 

• Extract massive quantities of raw data from various sources (call recordings, emails, customer relationship management systems, and so on) 
• Transform that data so it’s clean and ready for analysis 
• Load clean data into a secure database for future use 

This process is known as the ETL pipeline and can help call centers save time while gaining access to valuable, data-driven insights. 

Forecasting  

Call centers sometimes experience unexpected flurries of activity, which are challenging to plan for from a staffing and scheduling perspective. By automating forecasting, call center managers can review historical call data and identify patterns within that data. For example, a call center may receive increased call volumes around roughly the same time each year, suggesting that there’s a seasonality to this activity. 

Armed with this information, call center managers can better forecast demand and make more informed staffing and scheduling decisions, adding headcount to their teams as needed and ensuring that they have enough agents on hand at any given point in time to handle incoming calls. 

Reporting 

Call center managers can set up automated reporting for key performance indicators (KPIs) and other critical metrics to better gauge the operational health and performance of their call center. This form of call center automation enables managers to identify areas in need of improvement and determine what support they need to provide to their agents to meet key objectives. 

After-call Work 

As its name implies, after-call work (ACW) refers to any tasks a call center agent needs to complete following a customer interaction. This may include data entry, updating colleagues, and scheduling follow-up activities. ACW can take considerable time to complete — time that is factored into a call center’s average handling time — and prevent agents from focusing on higher-value activities.  

By automating these tasks using robotic process automation — which we’ll cover later in this article — agents can eliminate tedious, manual tasks and focus on what’s really important: providing exceptional service to customers. 

See how Hitachi Solutions Call Wrap Up can help with After Call Work

Customer Feedback 

Customer feedback is the lifeblood of any call center, enabling managers and agents alike to gauge agent performance and develop an understanding of which customer service tactics are effective (and which ones aren’t). Using call center automation technology, managers can streamline the feedback solicitation process by automatically sending out a request for customers to share their thoughts or fill out a survey shortly after a call center interaction. 

Quality Assurance 

When used in conjunction with machine learning and voice analytics, call center automation can be a powerful tool for quality assurance. Call center managers can automatically apply machine learning algorithms to call recordings. These algorithms will analyze each recording and score them based on previously defined variables — for example, the particular phrasing the agent used or the customer’s tone of voice. The higher the score, the more successful the call. 

Call scoring has long been an effective means of quality assurance and performance monitoring for call centers; however, given the substantial volume of calls centers typically receive, it’s impossible for managers to listen back to and analyze every recording. Automating the process not only enhances call scoring efficiency by eliminating the need for human intervention, it also helps managers surface valuable data about customer opinions and personas, recognize pre-churn signals, solicit customer feedback, and more. 

Lead Generation 

Call center automation can be a powerful tool for both inbound and outbound lead generation. On the inbound side of the equation, call centers can utilize interactive voice response (IVR) technology to collect customers’ details and provide them with a series of prompts for the purpose of their call. This enables call center managers to automatically capture information about callers and their motivations, and agents to better serve customers.  

On the outbound side, artificially intelligent chatbots can cold-call prospects and ask a series of qualifying questions to gauge whether they’d be a good fit for the company’s products and services. Once a prospect has undergone this initial automated qualification, a company’s marketing team can begin the lead nurture process in earnest, before handing qualified prospects over to the sales team. 
  

Call Recording Archiving 

Call recordings are an invaluable asset to call centers and serve a wide variety of purposes, from agent training to regulatory and legislative compliance. Archiving those records, however, can be a tedious process — which makes it an ideal candidate for automation. Many modern archiving solutions leverage automation to capture call recordings in real-time and move them into secure archives for future use. Some solutions are even able to automatically transcribe calls as they happen, creating a written record for call center managers and agents to review at a later date. 

Call Center Automation Trends & Technologies 

There is a diverse array of call center automation technology — some of it well-established and some of it still emerging — available to call and contact centers today. Some of these technologies and call center automation trends include: 

Robotic Process Automation (RPA) with Advanced AI Integration

A form of business process automation, RPA refers to the use of artificial intelligence (AI), machine learning, and other advanced technologies to complete tasks traditionally performed by humans. Compared to other forms of automation, which are often used to automate repetitive, rule-based tasks, RPA is highly sophisticated and can replicate human actions and speech with stunning accuracy.

Microsoft has been pushing the boundaries of RPA by infusing AI-driven capabilities into automation, making it more stable, intelligent, and accessible:

• Generative AI Actions – Microsoft’s latest AI-driven automation enhancements include Generative AI-powered actions that allow users to describe processes in natural language, and the system translates those descriptions into automated workflows. This simplifies automation design, reducing the need for complex scripting and making automation more accessible to non-technical users.
• Self-Healing Selectors – Traditional RPA solutions often struggle when UI elements change due to application updates. Microsoft has introduced self-healing selectors that automatically adjust when UI elements are missing or modified, ensuring automation continues to function without manual intervention. This drastically reduces maintenance efforts and improves automation stability.
• AI Recorder – The AI Recorder allows users to automate workflows simply by talking through the process. Instead of manually defining steps, users can verbally describe the process, and AI will generate an automation flow by interpreting the commands, mouse movements, and screen interactions. This significantly reduces the time required to develop robust automations.

To that end, RPA lends itself to a wider variety of use cases than most other forms of automation, including:

• Customer self-service – Automating routine inquiries to free up agents for high-value interactions.
• Streamlining order and transaction summaries – Automating data extraction, validation, and processing.
• Workflow integration – Connecting different systems and automating cross-platform processes for greater efficiency.

By combining RPA with AI-driven enhancements, call centers can achieve more resilient, adaptable, and intelligent automation, significantly reducing manual intervention while improving operational efficiency.

Take the Next Step with RPA with our Automation & RPA Envisioning Workshop!

Autonomous Agents

Unlike standard chatbots that respond to predefined queries, autonomous agents can independently perform complex tasks.

While conversational chatbots have been a staple in call centers for years, Microsoft’s Copilot Studio is taking automation to the next level with autonomous agents—AI-driven entities that can proactively manage tasks, make decisions, and continuously learn from interactions. Unlike traditional bots, which operate based on predefined scripts and respond to direct user queries, autonomous agents have the ability to self-initiate actions, handle multi-step processes, and function independently without requiring constant human oversight.

Key Differences Between Autonomous Agents and Conversational Bots

Feature	Conversational Bots	Autonomous Agents
Interaction Model	Follows scripted interactions, responding to direct user input.	Can proactively initiate interactions, recognize patterns, and predict next steps.
Task Complexity	Handles basic FAQs and simple transactions.	Manages end-to-end workflows, escalates cases, and integrates with multiple systems.
Adaptability	Limited ability to adjust responses dynamically.	Learns from interactions, refines workflows, and improves over time.
Decision Making	Requires human intervention for complex issues.	Uses AI-driven logic to assess situations and take appropriate actions.

Chatbots 

Perhaps the most common example of call center automation, chatbots use AI, machine learning, and natural language processing (NLP) to recognize and interpret human speech. Call centers can use chatbots to handle simple requests, such as changing a password or providing a balance on an account, and answer basic questions using pre-programmed answers. When used in conjunction with intelligent call routing — more on that shortly — chatbots can also escalate more complex and/or high-priority inquiries to the appropriate live agent. Some solutions also offer the ability to store a copy of the chat transcription for viewing at a later time. 

Conversational AI 

Conversational AI refers to the use of machine learning and NLP to make chatbots and virtual agents more sophisticated, so that they can more convincingly replicate human speech. Chatbots programmed using conversational AI are better able to understand conversational context, recognize multiple intents, and even process voice commands from users in multiple languages.  

Much like other AI-driven forms of automation, conversational AI is a helpful tool for enhancing live agent productivity because it broadens the scope of requests a call center can respond to without the need for human intervention.    

Intelligent Call Routing (ICR) 

Also known as skills-based routing or smart routing, intelligent call routing refers to the use of automation to identify the live agent best suited to handle a particular customer. With intelligent call routing, an IVR system presents callers with a menu of available options. Based on a caller’s selection, the ICR system automatically connects them with a live agent with the necessary skills to process their request or answer their questions.  

ICR is a powerful call center automation technology that enhances call center responsiveness and accuracy, all while saving customers valuable time. It also improves first-call resolution because it connects callers with the agents most qualified to help them and has the ability to reduce call queues over time.  

Agent Assistance 

A leading call center automation is the use of RPA to enhance agent performance. The way it works is simple: A virtual agent powered by RPA monitors a live agent’s calls, delivering recommendations in real time to enhance that live agent’s performance, checking other factors that might negatively impact call quality (such as spotty internet connection and workplace disruptions), and providing the agent with ACW support.  

Although conversations about automation often center around whether it will replace human workers, this is an excellent example of how companies can use call center automation to support and empower their human workers.   

Predictive Dialing 

For call centers, every second counts — including the seconds spent manually dialing phone numbers for outbound calls. Predictive dialers enhance operational efficiency in call centers by using automation to call telephone numbers from a preprogrammed list and only routing calls to a live agent when a contact picks up. 

Sentiment Analysis 

Call center operations are an exercise of continuous improvement, with agents and managers alike constantly soliciting feedback from the customers they serve in the hopes of improving their performance. Although customer satisfaction surveys can be an effective means of receiving feedback, customers are often reluctant to participate in them, citing everything from a lack of trust or empathy to not having enough time to fill them out.  

With that in mind, many call centers are turning to sentiment analysis as an alternative means of receiving feedback. Sentiment analysis refers to the use of NLP, text analysis, computational linguistics, and biometrics to identify the underlying sentiment of a piece of text. In call centers, sentiment analysis can be applied to call recordings in order to gauge both the caller and the agent’s emotional tones. Based on this analysis, call center managers can more accurately evaluate agents’ performance and gauge the efficacy of different techniques — all the way down to tone and turns of phrase — and adjust call center scripts and agent training accordingly.  

Voice Biometrics 

Call centers have become a popular target for scammers in recent years — call center fraud increased by 40% in 2020 alone — with account takeovers being the most common attack vector. Agent authentication has proven ineffective at preventing fraud, as agents can be susceptible to social engineering. In order to solve for this problem, a growing number of call centers have invested in voice biometrics to authenticate customers’ identities before providing them account access. 

Voice biometrics, also known as speaker recognition or voice authentication, refers to the use of uniquely identifying biological characteristics and vocal patterns to confirm a customer’s identity. With voice biometrics, a call center uses a voice recognition system to capture a speech sample from a customer. The system then sends that sample to a biometric engine, which saves the sample and turns it into a template — known as a voiceprint — for future recognition. The next time that customer calls in, they’ll be prompted to another speech sample, which the biometrics engine will compare against that caller’s voiceprint in order to verify their identity. 

Since voice biometrics is entirely automated, it is not vulnerable to social engineering, and since all voiceprints are automatically stored in a secure archive, fraudsters are not able to access and replicate them.  

Call Center Automation: An Illustrative Example 

Meet Sam.  

Sam recently bought a software solution from ABC Enterprise but is having issues logging back into her account after forgetting her password. She places a call to ABC Enterprise’s customer service line and is presented with an IVR menu with a list of options, including a forgotten password option. Sam selects this option and is automatically connected to a conversational AI-powered chatbot through ABC Enterprise’s ICR system. The chatbot uses voice biometrics to authenticate Sam’s identity before assisting her, so that her login information is kept safe.  

Once the chatbot has helped Sam get back into her account, it asks her whether she requires any additional assistance. Sam remembers that she ran into another issue with a particular software feature, and so choose to stay on the line. The chatbot asks her a few qualifying questions to collect additional details about the problem she is experiencing. Based on this information, the chatbot recognizes that the issue at hand is too complicated for it to solve, and so uses ICR to connect Sam to a live agent, named Connor.  

Connor receives a notification about an incoming call before Sam is connected, which gives him time to pull up Sam’s customer profile and review relevant details about her account, including her reason for reaching out. This enables Connor to greet Sam by name as soon as she’s connected and immediately begin discussing the issue at hand, rather than have her restate the problem. Connor also has a virtual assistant on his computer, which provides real-time recommendations on how to solve Sam’s issue based on similar examples. Connor is able to successfully resolve the issue on the first pass and checks to see whether Sam has any additional questions before ending the call.  
 
Once the call is complete, ABC Enterprise’s RPA system completes all ACW on Connor’s behalf — including data entry and sending out a follow-up email asking for customer feedback — so he can move on to his next call. The recording from Sam’s call is automatically entered into ABC Enterprise’s archiving system for future use. A few days later, Connor’s manager pulls up the call recording, applies sentiment analysis to it, and identifies a few areas where Connor may benefit from additional coaching. The manager then lands time on Connor’s schedule to offer feedback and set him up for future success.  

How Your Call Center Can Benefit from Automation 

Call centers that invest in automation enjoy a long list of benefits, including (but not limited to): 

• More Productive & Engaged Agents: With fewer distractions, manual tasks to complete, and less pressure to handle low-level inquiries, agents are empowered to put their talents to good use. This not only increases productivity but also makes agents feel more valued and engaged with their work, which can enhance call center performance and reduce the risk of employee turnover. 

• More Empathetic Service: Automation has the power to significantly reduce agents’ stress levels, both by taking tedious and time-consuming work off their plates and by providing them with real-time recommendations on how to improve their performance. The less stressed agents are, the more relaxed and focused they’ll be during customer calls, which translates to more empathetic service. 

• Personalized Customer Experiences: Call center automation is an incredibly powerful tool for data collection and analysis, particularly when it comes to customer data. With access to direct insights about customer preferences, service history, products owned, and more, agents can tailor their service to the individual, allowing for a more personalized — and positive — customer experience. 

• Increased Customer Satisfaction: In addition to receiving empathetic, highly personalized service, automation also increases the likelihood that a customer’s issue will be resolved, or their question answered on the first call. This saves customers valuable time — and, more importantly, spares them any potential frustration — which can help call centers improve their customer satisfaction scores and reduce churn.  

• More Efficient Service: Speaking of valuing customers’ time, chatbots and other related forms of call center automation technology provide customers with self-service options that allow for greater efficiency — a smart move, given that 62% of customers said that they would rather talk to a chatbot than a human agent if it meant not having to wait for service. 

• Enhanced Operational Efficiency: Customers aren’t the only ones who benefit from the efficiency gains call center automation has to offer. By automating manual tasks, improving agent productivity and performance, generating more accurate demand forecasts, and accessing scalable technology, call centers have the opportunity to enhance operational efficiency across the board.  

• Lower Operating Costs: Greater operational efficiency also translates to lower operating costs. By supplementing their human workforce with virtual agents, call center managers can drastically reduce the average cost per call and automate low-level requests, thereby enabling agents to focus on higher priority — and higher value — inquiries.  
  
  Having access to more accurate forecasts also enables call center managers to make more informed decisions about staffing; rather than dedicate substantial resources to staffing and risk over-hiring, they can right-size their teams according to demand.  

• Stay Competitive: Perhaps the simplest, yet effective argument in favor of implementing call center automation is that your competitors are likely already doing it. According to one study, 95% of call center leaders have either already adopted automation, are currently implementing automation, or plan to use automation within the next year. In order to keep pace with those companies — let alone get a leg up — it’s imperative that companies invest in automation for their call centers. 

Automate Your Call Center with Hitachi Solutions & Microsoft 

From agent enablement capabilities to automated reporting, Microsoft Dynamics 365 Customer Service is your one-stop shop for call center automation — and Hitachi Solutions is the perfect partner to implement it.

We have extensive experience with the entire Microsoft ecosystem, including Dynamics 365, Azure, the Power Platform, and Microsoft 365 Copilot, as well as a wealth of proven technical expertise. We’ve also been recognized by Microsoft as a top partner for intelligent automation, customer service and more, so you can rest assured that your call center is in good hands.

Contact us today to learn more about how we can help digitally transform your call center and turn it from a cost center into a profit center.

---