Is Intelligent Automation an Alternative to RPA? Experts Weigh In


Robotic Process Automation (RPA) is good at mimicking human actions, but there are some functions that require thinking and that is where intelligent automation — a combination of Artificial Intelligence (AI) and software robots take center stage. We find out why intelligent automation is gaining acceptance and how it is primed to disrupt the IT landscape. 

The pandemic spurred a tremendous interest in Intelligent Automation (IA), a key enabler of innovations such as intelligent chatbots. By leveraging these technologies, organizations across the globe were able to provide faster services to customers and reorganize their operations for a distributed work model. During the pandemic, these technologies became integral to the resilience strategy of many organizations.  

According to research firm MarketsandMarkets,Opens a new window the global Intelligent Automation market is likely to grow from $10 billion in 2020 to $16.3 billion by 2025, with North America leading the market in terms of deployment. A recent report by Information Services Group found that 8 out of 10 organizations in the U.S. have experimented with or deployed intelligent business automation solutions to future-proof their businesses.  

“Intelligent automation was experiencing very strong growth prior to the pandemic. But the business disruptions, increase in remote work, and changes in customer behavior caused by the pandemic have made organizations even more aware of how intelligent automation can help them address these and similar challenges,” said Prince Kohli, CTO, Automation Anywhere. 

‘’As organizations scrambled to do more with less during the pandemic, they realized that intelligent automation could discover and eliminate tedious tasks for employees. These organizations will expand the use of intelligent automation across their enterprises, further growing this market,” added Kohli. 

How Intelligent Automation is Different From RPA

Intelligent automation is the marriage of Robotic Process Automation (RPA) with AI and related technologies such as computer vision, Natural Language Processing (NLP) and Machine Learning (ML). 

The primary objective of any automation is to reduce dependence on humans and automate repetitive tasks and processes with the help of software.  In RPA, organizations deploy software robots, also known as bots, to learn, mimic, and execute rules-based business processes.  

They can be programmed to process invoices, orders, registrations, payrolls, onboarding, customer queries; scrape data; make calculations; parse emails; connect to APIs and extract unstructured data.  

Though RPA has enabled organizations to achieve greater efficiency and reduce costs, it can only function within the ambit of pre-defined rules. It cannot understand the logic behind a task, nor can it comprehend patterns in data or understand the context in images, text or speech.  

On the other hand, intelligent automation combines RPA with a range of cognitive technologies such as natural language processing (NLP) and computer vision to mimic human intelligence and achieve greater efficiency. According to a Deloitte surveyOpens a new window , organizations combining the two saw a 9% increase in revenue on an average compared to a 3% increase for companies that did not. Also, 45% of organizations that are looking to scale automation combine RPA and AI at some stage.  

Using intelligent optical character recognition (OCR), natural language processing (NLP) and machine learning, Intelligent Automation solutions can automate predictions and decisions from structured and unstructured data.  

For instance, an organization that generates thousands of invoices daily from its vendors in multiple formats can use Intelligent automation in its invoice automation processing pipeline to recognize the different invoice types and fields and their role in the invoice structure and then decide where they go in the ERP system.  

Kohli points out, during the pandemic, organizations recognized that one type of intelligent automation, intelligent document processing (IDP), is critical to getting work done by a “work from anywhere” workforce. IDP digitizes and “understands” documents, allowing them to be part of automated workflows. 

“Moving forward, organizations will increasingly find they need IDP, powered by AI-driven RPA, to process structured and unstructured data autonomously if they want their remote workforce to work efficiently,” added Kohli.

Learn more: 5 Steps To Integrate AI Into the Fabric of Enterprise Marketing Automation

Where Intelligent Automation Is Making a Difference

Customer care: Traction for Intelligent Automation has been highest in customer-facing businesses such as banking and financial institutions and retail and consumer companies. Post covid many customers prefer to communicate online. Consumer-facing businesses can longer afford to sit back and handle customer queries with simple chatbots or human operators. The former restricts communication with its fixed responses and can be frustrating to use, while the latter cannot address multiple customers queries simultaneously. As a result, more companies choose AI-based chatbots and voice bots, which use NLP to carry out a free-flowing and unstructured conversation that resembles human-like interactions. In the long run, this will improve customer retention and engagement for the brand.  

Security: During pandemic use of personal devices and non-IT-approved work applications grew significantly. This triggered a surge in malicious activities as it was a lot easier to inject malware on remote devices on home networks. According to reports, threat actors have intensified the use of automation to target systems and applications.  Cybersecurity firms, on their part, have also upped the use of Intelligent automation tools to automate threat detections and security logic to make faster, more reliable decisions on cyberthreats. 

“Smart automation adds immediate value and empowers users with the right tools to generate insight and context to make faster and more trustworthy decisions, seamlessly — all while anticipating what attackers might do next,”  Aparna Rayasam, senior vice president and general manager, Application Security, Akamai said in a statement.   

Networking: Intelligent automation is also being leveraged by communication services companies to manage networks more efficiently by implementing zero-touch operations. It has allowed them to identify hidden patterns and trends in networking data and optimize network operations and performance in real-time.  

“As the telco industry races to capture new value from 5G and Edge computing, many are transforming their networks to software-defined platforms that can deliver on this promise. Yet companies are identifying that limited automation and the lack of real- time visibility across networks have hindered their ability to deliver innovative services to customers fast enough,”  Andrew Coward, General Manager, Software Defined Networking, IBM,  said in a statement. 

Learn more: Automation and AI Are Key for Manufacturers’ Go-To-Market Strategy

Why Intelligent Automation Matters

Intelligent bots can use logic, make decisions, and self-learn, making them valuable for any organization, especially those that generate large volumes of data at both the front end and back end. 

Here are some of the key benefits of Intelligent Automation: 

Improves decision making: Intelligent automation can improve overall data-driven decision-making by reducing the risk of transactional errors caused by incorrect data inputs, incomplete processes or errors in rule application. 

Labour reorganization: By assigning certain analytical tasks to intelligent bots, organizations can further re-assign workers to higher-value tasks. 

Operational hygiene:  It can enhance business operational hygiene by scrubbing existing processes for any redundancies and conflicts using process discovery.

Modernization:   Intelligent automation can also modernize legacy ERP solutions by increasing efficiency, reducing errors and enabling real time decision-making. 

Reduce downtime: In specific sectors like manufacturing, it can also identify more appropriate maintenance routines and schedule installation and maintenance tasks in factories or warehouses. A proactive approach to maintenance can help businesses avoid costly downtime.   

Roadblocks to Intelligent Automation

Though intelligent automation has been growing, many companies are still holding back due to higher cost of implementation, lack of IT readiness and process fragmentation. 

In most organizations, processes are distributed across various software systems and teams, which further creates fragmented processes. Automating fragmented processes can be a costly affair as it involves deploying multiple bots for every process.   

According to a Deloitte survey, 36% of participating IT decision makers identified process fragmentation as the most significant barrier, while 17% found lack of IT readiness a major roadblock. Lack of vision, talent shortage are some of the other barriers to adoption.  

Another big barrier in the adoption of intelligent automation is the difficulties faced by organizations in scaling and updating on-premises intelligent automation solutions and on-premises solutions that had been lifted and shifted to the cloud. 

“While these organizations often experience some initial success with such solutions, they are not cloud-native and instead of being browser-based, require large legacy clients to be installed. This makes it much harder for them to scale to support more bots and users and also create more work for IT. In addition, because these solutions are not cloud-native and modularized, it is much harder for the providers of these solutions to add new services and innovations over time,” explains Kohli.

Learn more: Cloud to Enable 50% of Business Workloads by 2023: essidsolutions Ziff Davis Report


Intelligent Automation is the next logical step to RPA. By mimicking the cognitive abilities of humans, intelligent bots can achieve far greater business efficiency, customer satisfaction and much lower operational cost.  The road to adoption can be bumpy, but it is necessary for future growth.  

Do you think Intelligent Automation is the key to achieving greater business efficiency? Comment below or let us know on LinkedInOpens a new window , TwitterOpens a new window , or FacebookOpens a new window . We would love to hear from you!