Matthew Urwin | Nov 16, 2023

Intelligent automation (IA) streamlines business operations that would have otherwise required manual tasks performed by humans by combining artificial intelligence, robotic process automation, business process management and other automated technologies. Also referred to as hyperautomation, IA goes beyond basic automation, incorporating advanced approaches like cognitive computing and data mining to enable smarter, more adaptable decisions.

Intelligent Automation Definition

Intelligent automation (IA) brings artificial intelligence to standard automation, meaning it can handle complicated tasks that require decision-making and foresight. Companies use the technology to streamline business operations that normally have to be done manually by humans, such as detecting fraud in bank transactions or answering customer service questions.

Across numerous industries, companies that choose to automate their repetitive tasks through IA stand to see plenty of benefits, including increased efficiency, cost savings and an improved customer experience. And their human employees can have more time to focus on the more strategic and creative aspects of their jobs.

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How Does Intelligent Automation Work?

By combining artificial intelligence, robotic process automation and business process management, intelligent automation can speed up business processes while reducing production costs. 

  • AI: As machines gain data through training and user interactions, AI technologies give them the ability to learn from this data and make adjustments to enhance processes over time.  
  • RPM: Robotic process automation employs software robots to complete repetitive tasks, like organizing files and transporting physical objects.
  • BPM: Business process management is the practice of analyzing end-to-end business processes and determining opportunities to maximize outcomes.


Benefits of Intelligent Automation

No matter how it is used, intelligent automation can benefit a company in all kinds of ways.

Enhances Productivity

First and foremost IA can help enhance the productivity of human workers. By automating repetitive tasks, IA frees up employees to focus on jobs that require more creativity and problem-solving skills.  

“It’s allowing people to focus on what matters most,” said Peter Cousins, CTO of intelligent automation company WorkFusion. “There are quality of service capabilities that are really brought to bear by having a workforce that isn’t focusing on the routine stuff, and focusing on the more difficult things.”


Reduces Costs

Intelligent automation can also reduce a company’s operational costs — if not by cutting back the need for paid human workers then certainly by optimizing resource allocation, thus reducing unnecessary spending. In fact, a 2020 report published by Deloitte and Blue Prism found that IA cuts business process costs by between 25 to 40 percent on average.


Improves Efficiency and Accuracy

By definition, automation can perform tasks faster and with more efficiency than a human ever could. It can analyze large volumes of data, uncover trends from those analyses and produce actionable insights in no time at all. And it can easily be scaled up or down to meet changing demand without major resource investments.

“It doesn’t get tired or bored, it doesn’t quit for a better job,” Cousins said, meaning IA isn’t as likely to make the same kind of errors an overworked human employee might make. And the quality of its outputs is consistent.

Maintaining consistent work may sound simple, “but if you think about super complex processes — especially those that exist in highly regulated industries — the ability to adhere to standards is critically important,” said Adam Glaser, senior vice president of product management at process automation company Appian. “The ability to audit that process so that you know that it’s being done consistently is important.”


Boosts Customer Experience and Employee Satisfaction

Ultimately, when tasks are being done efficiently, quickly and accurately, everyone is happy. Customers have a more positive experience because they have access to a higher quality product, or can get answers to their questions faster (or even immediately). And employees have more time to focus on the more rewarding aspects of their jobs instead of “soul-crushing, boring work that nobody wants to do,” as Cousins put it. 

While the word “automation” is often associated with fears that human jobs will be replaced by computers, Glaser said job loss is not an inevitable consequence of intelligent automation. Rather, it is to “amplify the effectiveness” of a company’s team, he explained, by providing them with a sort of digital coworker with which they can “collaborate and coexist.”

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Automation Intelligence Use Cases

Many companies are tapping into intelligent automation’s potential. And like regular automation, IA can be used in just about any industry.

Customer Service

Tools like AI-powered chatbots can be used to handle common customer inquiries 24/7. Similarly, virtual assistants can guide customers through troubleshooting processes and account inquiries either through text or over the phone using conversational AI. Intelligent automation can also be used to analyze customer data to find patterns and trends, enabling more personalized customer experiences like product recommendations or personalized messaging.


Recruiting and Onboarding

In recruiting, IA software can easily sift through thousands of resumes, enabling companies to connect with eligible candidates faster. Thanks to natural language processing, it can analyze candidates’ applications and determine their qualifications, narrowing down the list of people human employees can then schedule for an interview. IA tools can also be used to guide new hires through their onboarding process, helping them complete paperwork and receive training.


HR Analytics 

Intelligent automation also has the ability to streamline time-off request processes, payroll and benefits administration and even workforce planning, providing HR teams with the employee data analyses they need to forecast workers’ needs, including hiring, training and talent retention strategies. And in the event an employee leaves a company, IA can analyze and summarize data collected in exit interviews.


Demand Projection 

IA can be used to analyze a company’s historical data and related market trends to better forecast demand for specific products, reducing overstock or understock situations. And automation tools can help manage the procurement of raw materials based on those production needs.


Predictive Maintenance Analytics 

IoT sensors can also be used to collect data from equipment to monitor its output and working condition in real time, using predictive analytics to figure out when maintenance is needed, as well as algorithms to monitor their energy consumption and optimize their usage. All of this helps reduce costs and ensure productivity. 


Regulatory Compliance  

The finance industry is a fairly complicated one, involving various calculations, transactions and communications between financial institutions and their customers. Intelligent automation can help companies within the space streamline these data-intensive operations, all while meeting the stringent and constantly shifting regulatory requirements that tend to slow things down.


Fraud Detection 

IA software can be used to detect and prevent fraud, analyzing transaction data in real time to flag suspicious activities and take the necessary steps to protect both companies and their customers. It can also be used to assess creditworthiness and calculate risk profiles for loan or insurance applicants, as well as streamline the approval process with automated document verification.


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Robotic Process Automation vs. Intelligent Automation

Intelligent automation and robotic process automation both automate business tasks that would have otherwise been handled by humans, but there are some key differences. 

Robotic process automation can perform only simple, repetitive tasks — like copying and pasting, or clicking buttons using software bots that follow pre-defined rules and instructions. You can think of it as a robot on a factory assembly line.

Intelligent automation combines RPA with AI and machine learning to handle more complex tasks that require decision-making and predictions. It takes those simple, rules-based tasks and brings a level of “inference” to them, said Reid Robinson, lead AI product manager at workflow automation company Zapier. You can think of intelligent automation as a sophisticated worker who not only performs repetitive tasks, but can also adapt and make decisions when needed.

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Artificial Intelligence vs. Intelligent Automation

Like robotic process automation, artificial intelligence is a key component of intelligent automation — IA cannot exist without AI. 

“It’s a technique that plugs in at different steps,” Cousins said. “Extracting data from documents or making automated decisions or classifying information to determine what to do next, all of those things are AI. And intelligent automation is what brings it all together.”

And as the capabilities of artificial intelligence grow more sophisticated, so too do the capabilities of intelligent automation. AI systems have never been better at processing and generating natural language, and they can easily extract information from unstructured data sources like emails or even video and audio files — all of which can enhance the abilities of intelligent automation.


Frequently Asked Questions

What is an example of intelligent automation?

Email marketing is one example of intelligent automation. Companies can use customers’ data to send them personalized messages, which have been automatically triggered by specific behaviors or dates, such as birthdays or anniversaries. 

How does robotic process automation differ from intelligent automation?

Robotic process automation is meant for more simple, repetitive tasks — requiring bots that follow narrow, pre-defined instructions, and are incapable of adapting to new environments or making decisions. Intelligent automation can handle more complex tasks that require inference, predictions and decision-making abilities — all of which is made possible by combining robotic process automation, artificial intelligence and other related technologies.

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