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 RPA and AI can drive.
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.
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Before you reach out to an RPA development company you should know whether you need RPA, AI, or a mix of both.
But, First, 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.
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
• Extracting data and processing documents
• Managing emails and attachments
So, 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.
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 its 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
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Therefore, you need an RPA development company with experience of AI-based RPA development.