AI and RPA Services – The Perfect Blend or a Disjointed Tech-Capability

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RPA and AI have emerged as the two best technology solutions for enterprises in the wake of digital transformation. Both AI and RPA services are the means and medium to help businesses achieve incompatible goals – increasing customer engagement and enhancing employee morale. However, one common factor connects the two – their shared objectives of reducing operational costs and accelerating profit.

However, most RPA service providers will agree that robotic process automation can reach its full value with the help of artificial intelligence and machine learning capabilities.

Artificial Intelligence Certification is essential because it helps to understand how it enables software to better understand human abilities like thinking, reasoning, planning, communication, and sensing and businesses can use RPA to develop code sequences that can perform boring or repetitive tasks without the need for human supervision.

It takes two to tango; AI and RPA services, when deployed together in sync, can benefit organizations in a million different ways. Let’s take a closer look.

Robotic Process Automation: Augmenting Processes with Automation

Companies avail the RPA as a service to automate repeatable business processes. With the use of software robots, RPA tools identify processes fit for automation by silently working in the background of the user’s system without disrupting the general workflow.

Then, the bots are deployed to carry out the same tasks without human intervention. RPA robots perform the same task the same way every time, following the predefined codes. They are incapable of improvisation or finding better ways to get their tasks done by deviating from the programmed codes. However, these robots are more than capable of handling processes independently, such as –

  • Logging into applications
  • Connecting to systems’ APIs
  • Copying and pasting of data from one place to another
  • Extracting data from documents and processing them
  • Documenting data and storing them in a single cloud repository
  • Opening and scanning emails and attachments
  • Capturing data from the web, and
  • Other redundant tasks
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RPA robots can be termed virtual assistants who shoulder the responsibility of catering to repetitive tasks that are less complex but consume the employees’ valuable time. They meet the roles as instructed with the utmost efficiency and speed.

Benefits of Using RPA Services

The top RPA service providers offer the following services that benefit enterprises in different ways, a few of which are described below –

Accelerated Speed of Task Delivery

The RPA tools and bots can complete tasks faster than humans, thereby improving process efficiency and negating bottlenecks.

Documenting and Compliance

RPA services are deemed the best bet for tracking, recording, and documenting data in a single cloud-based repository, creating audit trails, and upholding regulatory rules with precision.

Accuracy and Reliability

These software robots minimize human errors and their costs, thereby creating reliable, efficient, and accurate outcomes.

Boosted Employee Morale

Employees are relieved of redundant tasks and find enough bandwidth to focus on the more value-added roles that require expertise and knowledge.

Artificial Intelligence: Augmenting RPA Services with AI Capabilities

Artificial Intelligence has become a household name recently, courtesy of advancements made in technology. AI has questioned the legacy methods of conducting businesses and proved equally beneficial in science and medicine. Therefore, if you want to explore and be industry ready in AI, you should definitely check out this Artificial Intelligence Certification.

When machines simulate human intelligence in near closeness, it is called machine intelligence or Artificial Intelligence. It broadly covers the following human actions, like learning, reasoning, and self-correction. AI applications can acquire information from contextual rules, use contexts and rules to reach conclusions, and learn and improve from successes and failures.

The AI applications acquire data using image and speech recognition capabilities, machine vision, chatbots, natural language generation, and human emotions and sentiments analysis.

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Unlike RPA services, AI can easily handle more complex tasks and make cognitive decisions based on data sets and predictive analytics. In short, AI can go beyond simply executing to ultimate thinking.

Benefits of Using Artificial Intelligence

AI has proved to be efficient in catering to the following roles –

  • Understanding documents
  • Visualizing images, videos, and other visual aspects
  • Comprehending human language and emotions
  • Handling and extracting data from bulk structured or unstructured documents

Its contribution to businesses is quite similar to that of RPA services. A few of which are described below –

  • Reducing human errors and making processes more efficient
  • AI tools work relentlessly 24 hours round the clock for seven days a week
  • AI caters to redundant tasks with speed and precision
  • AI technology is capable of making decisions independently and improving the existing processes
  • It is reputed for making quick decisions and executing roles even faster than an average human
  • AI is mostly deployed in high-risk areas

AI and RPA Services – The Perfect Blend or a Disjointed Tech-Capability

As per statistics, the global RPA market is expected to reach $30.85 billion by 2030, wherein the AI market is forecasted to touch the $1,811.8 billion mark by the end of the same year.

However, this is not the only difference between the two. There are others. Let’s elucidate –

Approach

Robotic Process Automation services imitate basic human actions. Artificial Intelligence simulates human intelligence.

Processing and Input

On the one hand, RPA tools are rule-based, programmed, and deployed by humans; AI is created by humans but driven by analytics on the other.

Drive

RPA services are process-driven, but AI is only data-driven.

Contribution

RPA software enhances human capabilities with process automation. AI enhances automation itself.

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Method

RPA services are trained to follow a rule-based approach, while AI follows intelligent algorithms and statistical inputs.

Output

RPA automates repetitive tasks predefined. AI uses predictive analytics, ML, voice recognition, and other capabilities to accelerate processes by finding the best approaches which are not predefined.

AI + RPA Services: Garnering End-to-End Process Automation

To realize the objective of end-to-end process automation, both AI and RPA services are needed to drive operational excellence through increased process efficiencies. These technologies can work in perfect sync to ensure that companies’ goals are achieved at scale with speed and precision – much needed in the fast-paced and volatile digital space.

For example, RPA services find their application in the Insurance Industry, where certain redundant processes do not need a human hand to function. Such as collecting, collating, and documenting customer information on a centralized cloud-based repository. When AI capabilities are thrown in the same mix, Insurance companies can aptly predict claim frauds using ML and UiPath AI Fabric but based on the same customer data collected, documented, and processed by RPA tools.

In order to create a fully autonomous business process, RPA services should follow AI capabilities.

When to Deploy RPA Services Vs. When to Roll Out AI

This might sound unclear, but it need not be. Businesses can start their journey toward automation by incorporating RPA services in areas that are ideal candidates for automation. Then, they can roll out AI capabilities when workflows become complex for RPA to handle independently.

RPA is basically cleaning up underlying processes to provide an integrated framework to roll out AI into your existing digital system. In the absence of the underlying framework, AI implementation might have to follow the legacy approach of weaving into the core process.

Hence, both these technologies are independent but can co-exist simultaneously, thereby fostering game-changing improvements to existing processes and helping businesses reach their larger goals faster.