RPA vs. AI: Which One Should You Choose?

If you are seeking to leverage the power of AI and Robotic Process Automation (RPA) for your business, it's crucial to partner with the best software development company. They can help you unlock the true potential of these technologies, enhancing productivity, customer satisfaction, employee happiness, and overall efficiency, leading your organization towards remarkable growth and success.

Before you reach out to an RPA Solution Companies 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.

In the realm of ecommerce software solution development, RPA emerges as a powerful automation technology capable of replicating human interactions with digital systems. By streamlining repetitive and time-consuming tasks, RPA empowers employees to focus on more strategic and value-added endeavors, while also enhancing customer satisfaction. 

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 process 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
• 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.

RPA vs AI – A Complete Comparison

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, 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 can not 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.

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.

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. 

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.