Your Guide to Intelligent Automation in Customer Service


Humans can do a lot of things. 

Humans in customer service, for instance, can answer phones and alleviate people’s concerns, process orders, and provide product information. 

While humans can do all that and more, should they? Given the increasingly competitive business environment and large volume of work, would it not be smarter to find a quicker, cheaper, and just as effective solution for customer concerns? 

That is where intelligent automation in customer service comes in. 

Intelligent automation (IA) combines artificial intelligence and robotic process automation (RPA) to automate processes, scale decision-making, and enhance productivity. By harnessing artificial intelligence, automation in customer service can take over tasks that were traditionally performed by humans, like answering questions and resolving issues.

This article will offer a run-down of the functioning and benefits of intelligent automation in customer experience, illustrating how IA can build an exceptional customer experience and improve customer satisfaction. 

What is intelligent automation?

Intelligent automation is a powerful technology that integrates artificial intelligence (AI) with robotic process automation (RPA) to automate repetitive tasks, enhance decision-making, and improve workflow efficiency through AI-driven insights and automation. On its own, RPA involves automating rules-based tasks such as data entry and sending automated emails.

Despite reducing employee workload and increasing productivity, RPA has limitations, particularly in managing unstructured data and creative decision-making.

Fortunately, intelligent automation can help.  

Employing multiple AI technologies, artificial intelligence enables machines to learn from data, identify patterns and trends, and make complex decisions. AI technologies common in intelligent automation include:

  1. Machine Learning (ML): Machine Learning is a process that uses data and algorithms to allow machines to learn as humans do, allowing them to make decisions and predictions without being explicitly programmed to do so. In customer service, ML algorithms can be used to analyze customer sentiments, categorize customers, and offer personalized recommendations.

  2. Natural Language Processing (NLP): NLP lets machines to interpret, understand, and generate human language. In the context of intelligent automation in customer service, NLP equips machines to “understand” customer questions, detect sentiment, and provide relevant responses to queries.

  3. Generative AI: From text and audio clips to images and videos, generative AI creates content that is original and realistic. The value of Generative AI to intelligent automation in customer service is challenging to quantify as this technology boasts a wide range of applications. GenAI can automatically generate personalized, human-sounding responses to customer queries, create targeted content for advertising campaigns, develop voice assistants that can hold more natural conversations with clients, and more.

  4. Computer vision: Computer vision helps machines interpret visual data such as images and videos, performing functions like image recognition, facial recognition, and scene understanding.

    In customer service, computer vision lets intelligent bots interact with different systems (especially legacy systems). For example, an intelligent bot may pull a customer’s data from a legacy software to better address their query. Computer vision also helps bots interpret visual data, including pictures provided by the customer (which is important for, say, claims processing). 

  5. Optical character recognition (OCR): Optical character recognition (OCR) is an AI-based technology that allows computers to extract information from images, documents, and other data sources and convert it into an editable or searchable format. OCR is useful in extracting information from customer documents, customer feedback forms, invoices, etc. 

By combining RPA and these AI technologies, intelligent automation empowers customer service teams to not only automate routine tasks but also provide personalized and effective support, leading to a more satisfying customer experience.

How does intelligent automation work in customer service?

Intelligent automation goes beyond traditional automation tools to automate customer support so that it does not remain limited to predefined rules to execute repetitive tasks like routing calls and processing payments. Customer service automation that leverages artificial intelligence with RPA can interpret contextual information, make data-driven decisions, generate predictions, continuously learn from new data, and adapt to changing circumstances. 

Intelligent automation is applicable to both attended and unattended automation of customer service tools. 

In attended automation, RPA bots work alongside humans to make their lives easier. Automated customer service tools can help customer service agents by suggesting appropriate responses to customer inquiries, deriving relevant insights using customer data, and offering real-time recommendations. For instance, an IA-integrated chatbot may analyze client or transaction history to suggest troubleshooting steps to customer service agents.

In unattended automation, software works independently of human intervention, often performing back-end tasks required to build a helpful customer experience. Tasks carried out autonomously by IA systems include invoice processing, customer record management, and personalized email generation. For example, intelligent bots can categorize customer support tickets by urgency and complexity, prioritize tickets with high profitability potential, and draft personalized replies to each of them.

Thanks to its applicability to both attended and unattended automation, intelligent automation has widespread usage in customer service. 

Uses Cases and Examples of Intelligent Automation in Customer Service

1. Live customer support

Intelligent automation assists customer support agents in the provision of effective live support in multiple ways. Intelligent chatbots can use NLP to accurately understand inquiries and sentiment analysis to recognize emotions, while intelligent RPA bots can extract data from knowledge bases to answer queries and suggest tailored responses to support agents. AI tools can also analyze customer data in real-time and provide the service agent with important insights to help them make decisions. 

2. Automated data processing

In automated data processing, AI-powered bots extract and manipulate information collected by bots to enable businesses to gain actionable insights and optimize service delivery. Through its data processing abilities, intelligent automation predicts customer needs, creates tailored solutions, and provides more proactive customer service experiences. 

For instance, a telecommunications company gathers data from multiple touchpoints including call logs, website interactions, and social media mentions. When a customer calls the helpline, intelligent automation-integrated bots can analyze this data to suggest relevant troubleshooting steps. 

3. Anomaly detection

Intelligent automation systems can leverage data from customer interactions and history to detect unusual behavior or patterns in customer behavior such as abnormal website activity or purchases, this allows potential issues to be addressed early on. 

Say, for example, that IA bots detect a surge in failed login attempts on an e-commerce platform. The system can alert the customer support team, who can then intervene to enhance security measures and safeguard customer accounts before a cyber attack compromises customer data. 

4. Self-service portals

With increasing digitalization in commerce, consumers are quickly adapting to more convenient solutions, with up to 70% of customers now expecting a self-service option on websites.  By integrating intelligent automation into self-service portals – which use AI to provide relevant information and solve customer’s problems – businesses facilitate customers to find solutions on their own, without having to rely on customer support teams.

6 benefits of using intelligent automation for customer service

The benefits of intelligent automation are not limited to the international operations of a business but extend to benefits for customers as well. Benefits of automated customer service include:

1. Personalized experiences

By analyzing data and extrapolating relevant insights, intelligent automation provides personalized experiences to customers. According to one study, 80% of customers are more likely to buy from brands that offer personalized experiences, building trust and long-term customer relationships.  

2. Reduced customer service response times

Customers expect speedy, efficient service from businesses. While around 50% of customers expect companies to respond in under 4 hours, the average customer service response time is over 3 times as much

By facilitating customer support teams in performing their jobs and providing AI-driven self-service options, intelligent automation reduces customer service response times.

3. Improved accuracy

AI-powered bots minimize human errors and can easily identify anomalies and errors, ensuring consistency and accuracy in responses to customer requests. 

4. Lowered operational costs

Around half of all contact centers struggle to hire enough agents, while 54% grapple with high operational costs. Intelligent automation can help solve both these problems by not just automating repetitive tasks but also allowing machines to perform complex tasks and make decisions that previously required human intervention. This reduces the need to engage customer service professionals and minimizes associated costs. 

5. Continuous improvement

Intelligent automation leverages AI technology like ML and NLP to continuously learn from experience and adapt, thereby enhancing service accuracy and quality over time. 

6. Higher job satisfaction

AI-powered bots assist customer support teams to quickly and effectively solve customer issues, leading to happier customers, and consequently happier employees. Intelligent automation also takes over both tedious, rules-based tasks and more complex customer problems to reduce employee workload and allow human employees to work on more strategic and rewarding tasks.

Pitfalls to avoid when automating customer service

Amidst the excitement of the game-changing capabilities of intelligent automation in customer service, it is crucial to remember that there are certain pitfalls to look out for when automating customer service. These include:

Lack of human connection

One quintessential difference between humans and machines is that humans have emotions and machines don’t. As a result, humans can empathize with others, which, in customer service, translates to understanding clients’ emotions, connecting with their troubles, and helping to resolve them. However, fully automating customer service removes the element of human connection, which 57% of customers still prefer over automated support.

To address this challenge, companies should offer the option to switch to a human agent at any point. 

Excessive and unnecessary automation

Excessive reliance on intelligent automation can decrease human oversight over customer service, which may have a range of implications. For instance, over-automation may create rigid processes that do not adapt to customer needs, automated tools may have trouble understanding customer concerns, and the perception of being too impersonal may damage a company’s reputation.

Therefore, companies must perform a robust analysis of situations in which intelligent automation would add value and automate only when the benefits outweigh the costs. 

Patchy implementation

Patchy implementation, such as automating only one communication channel or platform or having isolated automation strategies for different departments, can lead to inconsistent customer interactions and disjointed communication. 

It is important, then, for companies to develop a careful automation strategy for consistent and widespread automation at the same level across platforms and departments to ensure cohesive and effective implementation of customer service automation tools.

Not considering customer opinions

Customer support is meant to make your customers’ lives easier, so any automation technologies your company adopts should do the same. Not considering customer opinion – like 42% of businesses – deprives you of notable information that can help you adopt automation tools to resolve customer concerns and provide the right customer service. 

In this case, administering surveys to customers and analyzing their interactions with new technology may be useful in making key decisions based on customer feedback to deliver exceptional customer experiences.

Summary: Intelligent automation in customer service

In an increasingly competitive business environment where customers have high expectations from businesses, intelligent automation presents a powerful convergence of artificial intelligence with robotic process automation. Through automating routine tasks and facilitating informed decision-making, intelligent automation improves customer engagement and enhances the customer journey. 

However, in adopting this valuable technology, it is crucial to consider and judiciously address certain pitfalls so you can improve the customer experience for your clients without jeopardizing the human connection.   


Kash Sadiq

Director Marketing at Mercurial Minds. With broad experience covering several areas including, new product development, user experience design, product and project management. Has worked in broadcast television production and programming, advertising, sales, live audio reinforcement, audio studio engineering, artist management and telecom-media convergence.
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