AI will take robotic process automation to the next level
Tags: ai
Published: 2020-12-07 14:20:47

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title: AI will take robotic process automation to the next level
published: true
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tags: AI
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<p>To someone who isn&rsquo;t familiar with their uses, Artificial Intelligence and Robotic Process automation might sound like two sci-fi concepts that can unite to create some sinister threat to humankind.&nbsp;</p>
<p>Fortunately, the reality is far less threatening, as these two technologies can work together to help us and help each other. Here is what AI will do to take RPA to the next level.&nbsp;</p>
<h2>Some RPA basics</h2>
<p>First of all, the robots mentioned in the <a href="https://www.investopedia.com/terms/r/robotic-process-automation-rpa.asp">RPA acronym</a> aren&rsquo;t physical robots. They are specialized computer programs that are used to standardize and automate repeatable business processes. As such, they do the same task the same way each time, as they cannot learn and improve themselves.&nbsp;</p>
<p>These robots are not meant to replace humans in any way. Instead, they are more like virtual assistants that can handle repetitive tasks that aren&rsquo;t complicated but consume valuable employee time. One clear advantage that robots have is that they don&rsquo;t get bored with continually doing the same thing. Besides, there is no room for error since they will handle their duties precisely as instructed and as efficiently as possible.&nbsp;</p>
<p>Typical tasks that RPA handles include auto-keying, screen/form integration, application or data integration, automated decisions, and rudimentary task management. It can reach to simple task sequencing and simple resource orchestration.&nbsp;</p>
<h2>What does AI do?</h2>
<p>Unlike Robotic Process Automation, AI is meant to emulate human intelligence in many ways. This includes learning by gathering information and applying contextual rules to use the gathered info and reasoning, where AI can use context and regulations to reach a conclusion.&nbsp;</p>
<p>Finally, it can learn from its successes and failures. This final ability is known as self-correction. These qualities make AI capable of doing many things that RPA cannot do on its own. Popular applications of AI include image recognition, <a href="https://aiinsurance.ai/resource/powering-insurance-automation-with-digital-workers/">digital assistants</a>, machine vision, speech recognition, chatbots, natural language generation, and sentiment analysis.</p>
<p>As you see, the main difference is that RPA uses structured inputs and logic, while AI uses unstructured inputs and develops its own logic.&nbsp;</p>
<h2>How the two technologies work together</h2>
![Alt Text](https://dev-to-uploads.s3.amazonaws.com/i/7gj2fsfiiai0s1m7has2.jpg)
<p>Even though they are so different, AI and RPA can team up to help each other and help us. Both are built mainly around improving workflow, minimizing human errors, and streamlining mundane or repetitive tasks.</p>
<p>While RPA automates the routine operations, AI has self-learning capabilities to boost process automation to the next level. Put them together, and you have two tools that perfectly complement one another.&nbsp;</p>
<p>AI empowers RPA with its cognitive capabilities, including machine learning and speech recognition. These cognitive technologies help in automating emotional or judgment-based processes, which is not possible with RPA alone. But that is not all.</p>
<p>When AI is integrated into Robotic Process Automation solutions, it brings the capability of gathering and sharing useful information with different systems and makes better decisions. Customized RPA solutions can utilize data fetched by AI and performs a complex task with ease. To sum it up, AI, together with cognitive technologies and ML (Machine Learning), empowers robotic process automation by introducing a human response in the workflow.</p>
<p>When put together, these two technologies can create something so new and powerful that some refer to this new process as CRPA (<a href="https://www.forbes.com/sites/forbestechcouncil/2019/08/19/the-rise-of-cognitive-robotic-process-automation/?sh=ed7e1bd2a7ff">Cognitive Robotic Process Automation</a>). This combination can also perform advanced tasks through refined software mechanisms and algorithms.</p>
<h2>Challenges in RPA and AI synergy</h2>
<p>Merging the two technologies has a gratifying outcome once you get to it. But, many kinks need to be sorted out before the combined solution is possible.&nbsp;</p>
<p>This process requires good coordination between two separate teams that handle RPA and AI, respectively, and proper planning and real-time communication between teams.&nbsp;</p>
<p>People who work on merging the two technologies should also keep an accurate record of actions, progress, problems, and milestones.&nbsp;</p>
<p>They also must manage the network to convey requirements and possible solutions effectively while paying more attention to every single detail and business aspects.</p>
<p>Finally, they need to apply a rigorous approach, which leaves no room for error because even the slightest mistake in the combination can damage the entire system.</p>
<p>When the two techs unite, it becomes easy to manage customer interactions and establish better customer relations through improved services. You can also utilize the RPA and AI combination in operating complex development cycles and explore new horizons for bringing intelligent automation to your workplace.</p>
<h2>Advantages of AI and RPA working together&nbsp;</h2>
![Alt Text](https://dev-to-uploads.s3.amazonaws.com/i/wbkbhsy1s2rgp6rfd395.jpg)
<p>Here are some of the benefits your business can gain by using intelligent automation:&nbsp;</p>
<ul>
<li>Improved productivity of your workforce.</li>
<li>Saving your workforce from tedious and repetitive tasks.</li>
<li>Eliminating human errors from the workplace and being sure to reach correct results.</li>
<li>Improving data management more effectively and saving costs.</li>
<li>Acquiring complete process transparency through a customized dashboard and customized reporting support.</li>
</ul>
<h2>What will the future bring?&nbsp;</h2>
<p>As AI advances to include activities such as judgment, particularly in context, RPA can make informed decisions based on leveraging the combination of AI and analytics. Deductions can be made after integrated information sources and knowledge worlds are run through advanced algorithms to take smarter action that considers multiple contexts.</p>
<p>Tasks that are knowledge-intensive will also need the help of the combination of AI and RPA. AI will be able to sort through <a href="https://www.datamation.com/big-data/structured-vs-unstructured-data.html">unstructured data</a> that will also likely include image, voice, and video and use them to gain knowledge which will help the bots.</p>
<p>While AI can learn to think and project by employing predictive analytics, RPA would be able to intercept exceptions and match these patterns or events to expected or unexpected opportunities, as well as threats. This puts organizations in a position to think through and respond to emergent behaviors and markets.</p>
<h2>Conclusion&nbsp;</h2>
<p>Adding AI to existing RPA platforms means adding the capacity to understand speech, better mimic human behavior, work with less structured data sets, and more. Therefore, going from RPA to intelligent automation adds a level of cognitive thinking to your machine processes.&nbsp;</p>
<p>Machine learning helps robots develop the critical thinking skills needed to handle more complex tasks. All of this enables AI to become an even better human partner by taking on repetitive and manual tasks while allowing humans to take on more rewarding activities. </p>