Robotic process automation or RPA is the process of automating business operations through tools, software and technologies. It has the potential to yield nearly 80% reductions in processing costs and processing time. Simply put, RPA can reinvent the way you do business, enhance your customer satisfaction levels and employee’s work value. However, RPA is unable to automate the tasks that require the judgement and perceptual capabilities of humans. That is when the role of AI comes into play. 

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The combination of RPA and AI promises to take care of the redundant and boring tasks in your business. It lets you focus on the productivity of your business. It is because of AI that RPA is able to run applications just like the way a human would. So let’s check out how AI influences the efficiency of RPA in various industries. 

  1. Reading unstructured data 
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As per 2019 predictions from Forrester, RPA and AI tools are soon to become a strategic investment in the enterprise world. This is because AI makes it possible for RPA to read unstructured data without the need for human intervention. 

In case you are a newbie in this industry, let me explain the difference between structured and unstructured data first. 

Structured Data vs. Unstructured Data

Structured data consists of clearly defined data types. The pattern of these data types is readable by RPA software. 

Unstructured data consists of essentially everything else. The pattern of these data types is readable by humans but not by RPA software. It includes different formats such as audio, images, video and social media postings. 

The problem is unstructured information makes up to 80-90% of the information in an organisation. Thus, it is crucial to extract information from unstructured data for maximum business productivity. 

How does AI help? 

RPA can use AI, NLP and machine learning to extract a surprising amount of information from unstructured without the involvement of humans. Let’s see how. 

  • Old documents can be transformed into text files via OCR or optical character technology. 
  • Audio files can be read through speech recognition technology as is used in Apple’s Siri. 
  • Text files can also be examined with NLP to extract topics and keywords and to generate summaries. 
  • Images and videos can also be analysed with the help of computer vision software to understand its most important features. 

My verdict 

Most of the companies are sitting on approximately 100 or more terabytes of unstructured data. They can implement AI technologies in RPA to unleash the full potential of RPA software and extra valuable information from the unstructured data. 

  1. Making the most of IoT sensors 
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RPA plays a huge role in manufacturing and operations processes such as billing, invoicing, reporting, etc. In supply chain systems, it can be used for automated procurements and delivery schedule. Thus, the machine can re-order goods whenever the inventory runs low. It can schedule the delivery of products as soon as it is ready to ship. 

The problem is that RPA needs something or someone to tell it what to do. This technology is unable to make decisions on its own. Therefore, it needs AI to correlate data from various sources and make the right decision based on place, time and other valuable information. 

What is IoT? How does it fit into the picture with RPA and AI? 

IoT, the Internet of Things, enables the collection of data from the surrounding environment through automation or partial automation. Partial automation includes reading the barcodes and hand-held RFID. Complete automation in data collection includes the handling of wireless communication technologies such as BLE and GSM. 

Just like RPA, IoT is also unable to think on its own. It needs AI to learn from the data it collects, make logical interpretations and decide the following course of action exactly like humans. 

The combination of AI + IoT + RPA is usually used in the industry of supply chain and retail space. IoT sensors are integrated into the products. It identifies any error or hurdle that may delay the shipping or delivery of goods and lets the AI know about it. AI makes a decision based on this information and RPA implements it without human intervention. 

How do AI + RPA + IoT help in supply chain management systems? 

The combination of AI, RPA and IoT can provide transformative benefits for many businesses. The RPA software can compile the alerts sent by IoT into a central database and flag them for employee attention. Check out the benefits of implementing AI and IoT in RPA technology. 

  • IoT sensors can capture a substantial amount of data without external help. RPA can leverage this data to gain information about the internal dynamics of businesses.
  • IoT can respond to unforeseen situations, including bottlenecks within a supply chain. It also helps RPA execute the right action in response to unexpected business events. 
  • From better customer service to the proper management of products in the supply chain, RPA and IoT take care of all in a business. 

My verdict

IoT and AI help RPA manage huge volumes of data, operational optimisation and software robot autonomy. These technologies can lead to more streamlined business practises and operational efficiency over time. 

  1. Improving chatbot services 
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AI-based chatbots have already taken the real estate and customer service industry by storm. 60% of millennials use them on a regular basis to purchase goods. Experts even predict that 90% of interaction with customers in the bank will happen through chatbots by 2022. According to a Gartner CIO survey, chatbots are the most powerful AI tools being used in various enterprises. They can do wonders after integrating with RPA technologies. 

Enterprise chatbots have already solved a lot of issues encountered by organisations. The most common issues include late response to customer service queries, employee self-service and scalability. The chatbots are expected to function even better after its integration with RPA. Let’s see how. 

What is the result of integrating RPA with AI-based chatbots? 

AI-powered chatbots can understand how the clients ask questions and what answers they like better. Chatbots can have conversations with employees or customers to complete certain tasks or to send valuable information. To perform these actions, the bot needs to access information from different enterprise systems such as help desks, Business Intelligence, CRM, etc. 

The bot can access the required information only from the systems that have modern APIs. The chatbots may not be able to extra information if the system lacks modern APIs. That is when the role of RPA comes into play. 

When chatbots integrate with RPA, the former can not only handle front office tasks but also take care of back-office jobs, as well. The bot can access information from the systems even if they do not have modern APIs. This makes the bots capable of handling real-time and more complex requests and queries.

How does the integration of RPA with AI-based chatbots lead to business productivity? 

  • The combination of RPA and AI-based chatbots makes the most of the automation abilities of RPA and self-service features of a chatbot to meet the demands of customers at lower costs. 
  • The chatbots can take care of routine activities such as copying information, redundant paperwork, gathering customer data, etc. 
  • AI-based chatbots can analyse large volumes of information related to customer’s past queries and experiences to send them contextual and client-centric up-sell and cross-sell offers. 

My verdict 

All in all, the combination of RPA technology and AI-based chatbots can create intelligent conversational experiences for clients. It can reduce business expenses and enhance the productivity of enterprises. 

Wrapping Up, 

Both RPA and AI technologies are still evolving. These are the most powerful impacts of AI on RPA. With time, we can expect a lot of innovations in this field that will take the concept of automation to a whole new level. For now, all we can do is make the most of the existing AI-based RPA technologies and wait for better effective innovations in the future. 

Author Bio: 

Ema Lee works part-time as a Microsoft code visual studio editor and he also offers visual studio assignment help to students at MyAssignmenthelp.co.uk.