RPA automates the boring repetitive tasks, but AI powers through complex decision-making for businesses. Let’s find out which one you need for success.

1. RPA vs. AI: Which One Should You Choose?
RPA automates the boring repetitive tasks, but AI powers through complex decision-making for
businesses. Let’s find out which one you need for success.
Robotic Process Automation (RPA) and artificial intelligence (AI) have become buzz terms. You must
have already heard about the unforeseen productivity, customer satisfaction, employee satisfaction,
and efficiency AI & robotic process automation services can drive.
Before you reach out to an RPA Development Company you should know whether you need RPA, AI, or
a mix of both. In this blog, we will dismantle the key comparisons of RPA vs AI & show you how both
technologies are improving operational efficiency of today’s businesses.
What is RPA?
RPA is an automation technology that can interact with digital systems and mimic human interactions.
RPA can relieve human employees of mundane, time-consuming tasks and non-value-added work.
As per Grand View Research, the global RPA market will reach a whopping $25.56 billion by 2027, and
the AI market is expected to touch an epic $390.0 billion by 2025.
RPA development best practices can increase employee productivity and customer satisfaction in one
go. RPA can handle several tasks all by itself, such as –
 Connecting to system APIs
 Data entry
 Relocating and reallocating data

2.  Extracting data and processing documents
 Managing emails and attachments
What is AI?
With guidance from the right RPA development company, Artificial intelligence (AI) can be the brains
behind the muscle (RPA). AI is a broad term that defines several technologies, including RPA. Unlike RPA,
AI can “understand” and make cognitive decisions using predictive analytics on large data sets.
API typically goes beyond the typical execution tasks. Here’s what AI can do for you –
 Understanding documents
 Comprehending conversations
 Visualization of screens (remote desktop control)
 Assessing processes that need automation
 Processing language
 Sorting and “understanding” semi-structured and unstructured data
AI can build efficient machine learning (ML) models that can make business operations run without a
margin of error. In sharp contrast to the portrayal of AI in science fiction, AI and ML are here to help and
enhance human skill, not replace it.
AI and RPA: Which One Should You Choose?
When the question involves AI and RPA; it shouldn’t be an “either-or” situation. RPA should always be a
part of AI. That is the only way to automate your business processes in an intuitive and scalable way.
For example, RPA development best practices can categorize all diabetic and non-diabetic patients in a
hospital database all by itself. However, RPA alone can only assess “yes” or “no” type answers and base
the categorization on the same. It is incapable of assessing more complex diagnostic criteria, which may
define how severe a patient’s condition is or what kind of care they require at the moment.
AI-based RPA development can allow hospitals to further categorize their patients into low-risk,
medium-risk, and high-risk categories by assessing myriads of other test results. The presence of AI with
RPA can also provide direct prompts to patients when they need further testing to check for new
symptoms of the disease.
A combination of RPA and AI is a force to be reckoned with. The use of big data and predictive analytics
give AI the power to predict high-risk pregnancies and cancer prognoses and reduce time-to-treatment
per patient. That can reduce the workload of healthcare professionals.
The margin of error remains so low due to the meticulous nature of AI-powered analytics and the
presence of humongous volumes of data that the rates of timely diagnoses can increase significantly.
That makes it crucial to work with the best RPA developers team that can guide you through the
automation process.

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RPA vs AI – A Complete Comparison
Parameters Robotic Process Automation
(RPA)
Artificial Intelligence (AI)
Definition RPA is software robots that
uses intelligent automation to
perform repetitive tasks
AI is a technology that simulates human
intelligence to automate repetitive learning
through data
Working process RPA bots perform based on
defined rules
AI technology is based on ‘learning’ & ‘thinking’
Drive Process-driven Data-driven
Characteristics A rule-based technology with
no intelligence. Automates
repetitive tasks only.
It includes Machine Learning (ML) and Natural
Language Processing (NLP). It offers more than
just making a rule-based engine
Enhancements Enhances process automation Enhances automation
Approach Rule-based approach required Computational intelligence, intelligent
algorithms, statistical inputs required
Objectives The main objective is to
automate the mundane &
repetitive business processes
Aims to build a system with automated
decision-making
Complexity Easier & simpler to implement. A number of tasks are required to set up & run
Examples Data Transfers
Processing Payroll
System Setup
Call Centre Operations
eCommerce Processing Orders
Credit Card Applications
Compliance Reporting
Chatbots
Maps & Navigation
Facial Detection & Recognition
Search & Recommendation
Digital Assistants
AI Image Generators
Social Media Feeds
Key differences between RPA & AI
Robotic process automation & Artificial Intelligence both terms are used interchangeably, however,
they have extensive differences. RPA is efficient but it only automates predefined business workflows,

4. while Artificial Intelligence simulates human intelligence. Below factors will help you understand how
RPA is different from AI technology.
1. Functionality: In terms of Functionality, Artificial Intelligence is more functional than Robotic process
automation. This is because AI is used for different purposes such as natural language processing,
predictive analytics, image recognition, etc. On the other hand, RPA functions are limited to performing
& automating predefined tasks.
2. Implementation time: A longer time frame is required for AI implementation as it needs a complex
development process. On the other hand, implementing Robotic Process Automation is relatively faster
as the development time is less. However, AI technology is more accurate than robotic process
automation, as AI uses a large amount of data to make a decision.
3. Cost: In terms of software & hardware, Robotic Process Automation requires very less
investment. On the other hand, you have to pay more if you would like to implement Artificial
intelligence in your project. So, no doubt, as compared to Artificial Intelligence, RPA technology is a
more affordable option.
4. Security: RPA & AI both technologies are both secure enough & they rely on mathematical
algorithms. However, AI technology is more secure than RPA as it uses large amounts of data. However,
as a business owner, if you’re in search of comprehensive security solutions, you can use RPA & AI
together to get powerful security benefits.
5. Risks: AI technology is comparatively new & it has high growth potential. However, AI has some risks
such as unforeseen errors, biased result possibilities, etc. Whereas, robotic process automation is less
risky than AI as it cannot manage highly complex tasks. Moreover, RPA doesn’t have a good range of
capabilities.
6. Flexibility: In terms of flexibility, AI always wins. This is because once the software is configured, RPA
performs a specific task in the same way. On the other hand, Artificial Intelligence is highly flexible than
RPA as it can automate a number of tasks and complex processes with ease. AI is the best option for
performing tasks that need a high level of decision-making & judgment.
7. Scalability: RPA is designed to simplify specific and predefined tasks. This means this technology is
only ideal for a business having a predictable & stable process. AI, on the other hand, is designed to
efficiently automate complex processes that need human-like intelligence. So, in terms of scalability,
Artificial Intelligence is more highly scalable than RPA.
8. Maintenance: AI needs more maintenance support than Robotic Process Automation systems. AI-
enabled systems constantly learn & evolve, so they need regular updates to perform well. On the other
hand, regular updates are not required for RPA systems as they’re designed to automate specific tasks
only.
9. Deployment process: Deploying AI-enabled systems in a business is a very complex & daunting
process. Unlike RPA, which needs basic skills in data & business processes only, AI system deployment
requires a high level of skill sets & deeper knowledge. This is because AI-powered systems are trained on
huge data sets to make decisions & learn patterns. The entire training process is time-consuming &
complex. That’s why the deployment process of AI is more difficult than RPA.

5. Which Business Processes Demand RPA and AI?
Suppose you have already selected a bunch of business processes for automation. However, some of
these processes are too complex for RPA since they demand cognitive thinking in addition to execution.
That’s where you need to introduce AI.
For example –
 You want to automate workflows, but you have no way to predict their outcome accurately.
These may include processes involving loan defaults, property evaluation, and inventory
forecasts.
 You need automation for highly variable processes that do not depend upon “yes” or “no”
questions. For example – purchase decisions, resume matching, and language translation.
 Your company needs to automate the processing of high-volume unstructured data from
various sources. These may include invoice processing, invoice extraction, speech-to-text
translation, and email routing.
The Pros of Choosing Both AI and RPA
At the risk of sounding reductive, we can call RPA an advanced version of flowchart-friendly process
automation. It lacks the understanding or cognitive abilities of AI necessary to comb through large
volumes of data and look for patterns.
On the other hand, AI alone may lack the infrastructure and support to scale up with your enterprise.
In the real world, several sectors are already using AI and RPA together. Some of the most popular AI-
supported RPA processes may include –
 Pricing optimization in the retail sector
 Readmission prediction in healthcare (hospitals and nursing homes)
 Detection of fraud in financial services
Therefore, you need an RPA development company with experience in AI-based RPA development.
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business workflows.
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Final Words
The RPA & AI both technologies are emerging & transforming today’s business landscape rapidly. They
provide massive opportunities that help you streamline complex workflows and automate repetitive
tasks within the organization.

6. However, choosing RPA or AI-enabled solutions completely depends on your business needs. To make
the right decision, consult with a technology partner who will help you thoroughly assess your project
requirements & find the exact solution for effective business growth.
FAQ’s
Which is better: RPA or AI?
RPA & AI both are powerful technologies used for streamlining business process automation. However,
in terms of scalability, flexibility, and functionality, AI technology is better than robotic process
automation.
Is RPA more complex than AI?
No, RPA is not more complex than AI as it can only automate specific repetitive & predefined tasks every
time. As compared to AI, robotic process automation can be implemented easily and it also requires a
basic knowledge of business processes.