Intelligent automation (IA) benefits, components, and examples

Olivia is a customer service agent at a bustling, understaffed customer service department. She primarily responds to written support requests, like emails and chats, and can handle 30 to 50 messages per shift. However, her capacity often fluctuates based on the complexity of the tasks.

To free up her time, bots quickly answer customer questions or acknowledge receipt of the query and when customers can expect a reply. This keeps her workload manageable, stress levels low, improves the customer experience, and helps her stick to her schedule.

That’s the power of intelligent automation.

In this article, we will discuss the definition of intelligent automation, key components, and details about how you can leverage IA for customer service within your organization.

• What is intelligent automation (IA)?
• Why is intelligent automation important?
• 5 components of intelligent automation
• How can AI automation help employees work more efficiently?
• Examples of AI automation customer service use cases
• Discover the true potential of AI and automation in customer service

What is intelligent automation (IA)?

Intelligent automation (IA) describes the intersection of artificial intelligence (AI) and cognitive technologies such as business process management (BPM), robotic process automation (RPA), and optical character recognition (OCR).

Sometimes called “cognitive automation” or “hyperautomation,” IA allows businesses to automate repetitive tasks and processes. In customer service, intelligent automation helps agents provide faster support in addition to stand-alone options like chatbots.

What is the difference between AI and intelligent automation (IA)?

To put it simply, artificial intelligence is a tool for efficient problem-solving, while intelligent automation combines several tools and technologies (including AI) to automate tasks, workflows, and processes. Since the technology is constantly combining and evolving, there are some blurred lines between the definitions of artificial intelligence, intelligent automation, and other methods of business process management (BPM). Here are the basics:

• Artificial intelligence is a machine’s ability to perform cognitive functions typically associated with human minds, according to McKinsey.
• Intelligent automation uses automation technologies like AI, business process management (BPM) and robotic process automation (RPM) to simplify organizational processes, streamline and scale decision-making, and improve operational efficiency, according to IBM.

Why is intelligent automation important?

Intelligent automation benefits businesses by streamlining manual, routine tasks. It increases operational efficiency, reduces human error, and can lower business costs.

Here are a few benefits of intelligent automation and why they should matter to business leaders:

• Increases efficiency by reducing repetitive work
• Helps teams accomplish more with fewer resources to keep operational costs low
• Controls operational costs by alleviating the need to add more support agents to the payroll
• Improves the customer experience by enabling agents to resolve customer issues faster

5 components of intelligent automation

Intelligent automation uses several technologies to achieve necessary functionalities, but the five basic components of intelligent automation include artificial intelligence, robotic process automation, business process management, automation tools, and data.

So, let’s demystify these components and how they make intelligent automation possible.

1. Artificial intelligence

Artificial intelligence (AI) is essentially the brains of the operation. AI often powers intelligent customer service tools that assist with sentiment analysis, personalization, and problem-solving to streamline support interactions.

AI refers to the ability of computers and software to assist with, and sometimes perform, cognitive tasks humans are traditionally responsible for. For example, making decisions, understanding context, and personalizing responses. Using data, AI continuously learns, making it a powerful tool for problem-solving.

AI makes intelligent automation possible using these techniques:

• Machine learning (ML): A type of AI that utilizes algorithms to learn from the data it acquires.
• Optical character recognition (OCR): Sometimes known as “text recognition,” OPR can identify text and repurpose data from documents, images, and PDFs.
• Natural language processing (NLP): A machine’s ability to recognize, understand, and output spoken and written human language.

Together, these techniques and algorithms help the software “think,” better comprehend customer requests, and enhance support.

2. Robotic process automation

Robotic process automation (RPA) is the task handler and rule follower. It’s also a key component of chatbots but primarily uses pre-defined business rules to influence bot outputs instead of learning from interactions and delivering humanistic replies.

RPA allows bots to execute repetitive, back-office tasks and processes like data entry and extraction, filling out forms, processing orders, moving files, and more.

For example, RPA bots can follow predefined rules to automate tasks and workflows. However, they’re unable to make decisions or think for themselves. So, to achieve intelligent automation, you must use robotic process automation with AI.

3. Business process management

Business process management (BPM) is the operations specialist of the intelligent automation group. For instance, let’s say you want to create an IA function to optimize change management—or how your business will use tools to manage and adapt to change. BPM can influence implementation planning, help capture data, and streamline creation of your change roadmap.

BPM is a discipline that relies on various software and processes to manage a business’s operations, including modeling, analysis, optimization, and automation.

The primary job of business process automation is to identify and eradicate inefficiencies by reassigning tasks that are time-intensive or prone to human error to AI automation.

4. Automation tools

Automation tools such as apps and integrations act as helpers. They automate workflows and processes, and enhance existing functionalities.

These integrations and automation tools often serve a specific purpose, like:

• Enabling communications between platforms

• Streamlining data sharing

• Identifying support congestion

• Automating general tasks

• Assisting with replies

By adding apps and integrations, businesses can customize intelligent automation from end-to-end to effectively serve customers and departments with unique needs.

5. Data

Finally, data is the key piece of the intelligent automation ecosystem. IA uses raw data to train its systems and set up intelligent workflows. Over time, IA can also continue learning and improving using data from interactions.

IA uses data to train itself and generate relevant responses to prompts it receives. Data also plays a key role in machine learning, ensuring the IA learns from each support interaction and user feedback.

Robotic process automation also uses data to follow predefined rules and compliance standards.

Business process management uses data to detect inefficiencies and enact changes that improve existing processes.

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How can AI automation help employees work more efficiently?

Many employees are hesitant to embrace AI for fear of job displacement. There is some merit to this concern, as a report from Gitnux predicts that AI will replace 85 million jobs by 2025. But the study also estimates that AI will create approximately 97 million new jobs.

AI isn’t a replacement for human talent, and businesses should use it as a support aid to enhance productivity.

For customer service, businesses can lead with an automation-first strategy to help human agents deliver better support. Here are some ways AI helps customer service teams:

• Saves agents time by taking over complex and repetitive tasks

• Identifies opportunities for streamlining operations

• Analyzes large amounts of data and delivers key insights

• Organizes support requests to keep agents on track

• Monitors regulatory guidelines to ensure compliance

Applications of AI automation and IA

Businesses can leverage intelligent automation to streamline their processes for various industries, from customer service and sales to marketing and operations. IA can help keep costs low by removing inefficiency from the equation and freeing up time for other high-priority tasks. See some examples of these applications below.

Make suggestions

Businesses can use automation to provide predictive suggestions that can speed up processes and improve productivity. Teams can use IA to:

• Draft emails and press releases

• Create internal process docs

• Brainstorm ideas

• Help edit text for basic grammar and syntax rules

Customer support teams can use intelligent automation to help write and send personalized replies to customers at scale. AI can save agents time on the basics so they can invest more time into things like personalization, this could include:

• AI-suggested macros and help center articles for agents to choose from while assisting a customer

• Auto-filled response options using a few contextual words from an agent

These automations benefit existing agents but are also useful to new hires, who may be slower to resolve tickets as they learn details about your business, its offerings, and performance expectations.

Automate workflows

Workflow automation helps team members handle smaller, repetitive responsibilities with ease. This also increases productivity by tackling time-consuming sales, support, IT, and marketing tasks.

Administrators can set up event-based (triggers) or time-based (automations) business rules so the AI will automatically address a task when the need arises without human intervention.

Gather data and insights

AI-driven tools like chatbots can aid in data collection, assess unstructured or historical data, and rapidly generate insights.

A few other ways businesses can use intelligent automation data include:

• Generating predictive analytics to aid in decision-making

• Gathering key context from customers before escalating tickets

• Detecting anomalies

• Prioritizing tickets and communications with high profitability potential

• Identifying how customer intent relates to purchasing behaviors

• Sharing personalized recommendations

Drive sales and conversions

Much like gathering data and insights, IA can help businesses drive more sales by providing strategy recommendations and optimizing existing sales processes.

Some ways IA can help create or identify upsell and cross-sell opportunities are through:

• Lead scoring

• A/B testing suggestions

• Real-time product recommendations

• Industry and market trend predictions

• Customer intent and sentiment analysis

Support customers

Aside from serving as a worthwhile resource for internal use, intelligent automation can also be a valuable tool for customer self-service.

For example, chatbots can provide conversational support for most minor issues and many customers like using them because of the added layer of convenience.

AI automation can improve customer service convenience by:

• Sending help center articles to customers or employees

• Answering frequently asked questions around the clock

• Routing customers to the best agent or department to resolve their issue

Invest in intelligent process automation

Discover the true potential of AI and automation for customer service by incorporating intelligent process automation into your workflows.

When you equip your support teams with AI-powered tools like chatbots, virtual assistants, and agent workspaces that enhance productivity, you empower them to take customer service to the next level—and maybe even capitalize on sales opportunities.

Learn more about Zendesk AI for customer service to take customer care to the next level and exceed customer expectations.