Automation is no more considered a fad. In fact, according to a report by Statista , the global market for robotic process automation is projected to reach $10.4 billion in 2023 as compared to only $2.9 in 2019. Proof enough that RPA implementation partners are effectively helping businesses boost their business.

As RPA becomes the new norm, there are new shapes and forms it takes, and new partners it chooses. This time around, we’re looking at the matrimony between RPA and Machine learning that is helping businesses across industries. While RPA has been of great help, users are now looking for an edge. And ML is what provides this edge.

RPA service providers are now leveraging machine learning and artificial intelligence, But how? To understand that, we must understand the difference between RPA and ML and how they function differently but in assonance with each other. Let’s learn.

How RPA Differs from ML?

The very names of both technologies are indicative enough. RPA, as the name suggests aims to automate repetitive tasks though a robot. So, tasks that are non-core, documentation based, repetitive but do not need much human discretion are automated by RPA consulting companies.

Machine learning, on the other hand, offers help through artificial intelligence. AI enables the machines as well as connected devices to learn user and behaviour and offer better insights to machines which further automate your processes in a much more dynamic way that RPA ever can.

How RPA implementation partners are Leveraging ML

The matrimony of both these technologies results in accomplishing tasks with high efficiency and accuracy. It helps gathering information, learning processes and user behaviours, and sharing this useful information with other related systems to make better decisions and automate processes.

The insightful information gathered by AI and machine learning companies can be utilized well by RPA for intelligent automation, a step ahead of robotic automation. It can perform complex tasks with great ease. This empowers RPA implementation partners to introduce the human aspect in the workflow.

Moving ahead to Intelligent Process Automation

IPA, i.e. Intelligent Process Automation or CRPA, i.e. Cognitive Robotic Process Automation is what the matrimony of ML and RPA produces. The AI/ML part gathers complex data from sources like text inputs, audio inputs, natural language processing. Then it analyzes it so that it can be converted into standard data that RPA can use. So, CRPA enables businesses to not just automate repetitive processes but also improve the productivity in a number of processes and that of overall operations.

The Challenge

The biggest challenge is when your RPA service providers and ML providers are not one and the same. In that case, a lot of time, effort and resources go in syncing both to your satisfaction. Slightest mistake on either party’s part can result in a grinding halt in the system.

A preferable situation is when your RPA implementation partners also provide you machine learning solutions. That not only reduces the planning and implementation time but also the odds for errors.

This convergence is one that looks towards the future with fecund potential, and if you are thinking of adopting RPA, it’s better adopted with technologies like ML and AI. In case you need any assistance in implementations or guidance in exploring RPA’s viability for your business, Synlogics can help. Get in touch with us.



Venkateshwarlu Kakkireni

Venkat is highly passionate about solving Business challenges using Technology. He has been instrumental in bootstrapping the company and is currently responsible for leading strategies and innovations to help customers enhance operations and improve efficiency. Among several key projects he was involved over the years, developing an award winning IoT solution which monitors Food Safety, both while in transit and in storage for Emerson Electric has been very close to his heart. Currently over 500+ businesses across the globe are using this solution to track real-time location, temperature and safety of perishable and high value shipments.