How to Maximize the Value of RPA with Intelligent Process Automation
Within today’s business climate, artificial intelligence (AI), big data, machine learning, and predictive analytics continue to expand the possibilities for transforming the way work gets done. One of the more recent and most exciting applications of AI and machine learning is its introduction to robotic process automation (RPA), automation technology that uses software robots to manipulate and communicate with business systems, streamlining IT and businesses processes.
Augmenting automation with intelligence will intensify in the coming years. A recent Forrester1 study predicted ‘more than 40 percent of enterprises will create state-of-the-art digital workers by combining AI with robotic process automation’ over the next several years. Applying intelligence to RPA will also lead to greater cost savings for organizations. Gartner2 predicts that by 2024, companies that leverage automation and intelligence will reduce operational costs by nearly 30 percent. The benefits of combining AI and RPA make strategic business sense.
Because of the advancement that intelligence is bringing to RPA, organizations will begin to enhance their automation capabilities, and maintain control of critical information with more speed and accuracy. But delivering on the promise of this digital transformation requires the ability to harness both structured and unstructured data. In this blog, we will examine the different types of data within organizations today, and uncover how combining AI and machine learning with the power of RPA delivers intelligent process automation to solve the biggest document processing challenges in business.
Not All Data Is Created the Same
Within organizations today, there are two types of data—structured and unstructured data—and they are not created equal. Structured data is the data you are typically used to working with. It’s organized, clearly defined, quantitative, and searchable. Think Excel spreadsheets. According to Forbes3, structured data is easy to search, analyze, and group together, but it ‘accounts for less than 20 percent of all data’ within organizations today. Traditional RPA excels at processing structured data.
Unstructured data, on the other hand, is typically qualitative. It’s often difficult to interpret and analyze because it has no pre-defined structure. According to CIO Magazine4, ‘unstructured digital data is finally seeing its day in the sun,’ and includes things like emails, photos, audio files, social media posts, blogs, video, and other qualitative data. Similar to the estimate from Forbes, CIO further indicates that unstructured data ‘accounts for between 80 to 90 percent or more of the overall digital data universe.’ This means that a large majority of the data in your organization is not in a format that traditional data analysis tools can interpret or easily manage.
But with the introduction of AI and machine learning that can help extract meaning from unstructured data, the bulk of data within businesses can now be leveraged for greater insights and usability. And more importantly, when applied in context of robotic process automation, organizations can now apply intelligence to document processing for use in streamlining manual processes and eliminating costly steps like document classification, manual data entry, and document analysis.
Machine Learning and AI Unleashes the Power of RPA
The key to unleashing the true power of RPA is through unassisted machine learning that can harness both structured and unstructured data. The best in intelligent document processing calls upon unassisted machine learning algorithms that enable automatic self-learning for previously unseen documents because the system learns which document information to capture—getting smarter and more accurate over time.
Combining this with a robust classification and categorization engine that leverages artificial intelligence ensures rapid document processing across critical functions like mortgage processing, invoice processing, and sales order processing, enabling you to avoid manual data entry into systems, decreasing errors, and easily managing document volume.
Taking RPA to the Next Level with Automate Intelligent Capture
Automate Intelligent Capture leverages intelligent document processing to enhance the power of our RPA solution HelpSystems Automate through machine learning capabilities. Easily capture both structured and unstructured data to further extend the benefits of automation across your business. This is possible because Automate Intelligent Capture automatically learns data fields on forms by using custom machine learning algorithms without endless hours of building templates.
By capturing forms as they arrive in your organization from a scanner, email or monitored folder, documents are automatically sorted based on patterns, appearances, and text into specific document classes for extraction. Out of the box, organizations see 70 percent document processing without human touch automation, and within weeks of machine learning, automation is at more than 95 percent field level accuracy. Combined with HelpSystems Automate, our intelligent document processing solution can reduce manual data entry between 60 to 90 percent in your business. Enhancing the value of your RPA solution is possible by leveraging the best in AI and machine learning. It just takes the right solution to get you there.
1Goetz, M., Le Clair, C., Purcell, B., et al. Predictions 2019: Artificial Intelligence. Forrester.
2McHugh, B. Gartner’s IT Automation Predictions for 2020. Gartner.
3Marr, B. What’s The Difference Between Structured, Semi-Structured and Unstructured Data? Forbes.
4Davis, D. AI Unleashes the Power of Unstructured Data. CIO Magazine.
Let us show you what’s possible with the power of intelligent document processing and RPA. Request your own demo today to see Automate Intelligent Capture in action.