Intelligent Automation: Pairing RPA and AI to Advance Your Organization
- AI/ML, RPA
In today’s dynamic and competitive business landscape, the need for automation is growing exponentially. A study by Deloitte found that 86% of organizations are currently investing in automation, with 79% identifying automation as a strategic priority.
Intelligent automation (IA), which combines two key technologies: Robotic Process Automation (RPA) and Artificial Intelligence (AI), stands out as a proven solution to address this growing need.
The “robot” in RPA refers to a software bot rather than a physical robot. These bots automate repetitive and time-consuming tasks based on predefined rules. For example, an RPA bot can copy and paste data, move files, fill out forms, scrape browsers, and extract information from documents. They complete rule-based work that humans would otherwise need to do manually.
AI, on the other hand, involves machines mimicking human intelligence to perform repetitive, time-consuming and complex work.
Together, RPA and AI create solutions that automate end-to-end processes using intelligence. This means that, rather than dealing with binary decision points, the processes are completed while dealing with multiple variables and arriving at multiple outcomes. Simply put, Intelligence Automation has proven to deliver demonstrable levels of efficiency and productivity.
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How and Where AI Addresses the Shortcomings of RPA
An increasing number of organizations leverage RPA to automate repetitive, rules-based tasks. However, Robotic Process Automation faces inherent limitations that hinder its ability to address a wider range of business challenges. Some of the more important ones are:
- Missing cognizitive capabilities: Natively, RPA excels in tasks with well-defined rules and procedures, but its ability to make intelligent decisions based on context and changing circumstances is severely limited. This deficiency impedes RPA’s ability to handle complex processes that require judgment, adaptability, and the ability to learn from experience.
- Scalability: RPA often requires the constant need for tuning and the potential need to add bots and servers
- Human exception handling: RPA still requires human intervention for handling exceptions. Exceptions are unexpected events or occurrences that fall outside the pre-defined rules and parameters of an automated process. These exceptions can disrupt the smooth flow of automation and require human intervention to analyze, resolve, and update the process accordingly.
- Unstructured data: Traditional RPA relies heavily on structured data, meaning it struggles to process unstructured information such as emails, images, videos, and natural language. This limitation restricts RPA’s applicability to a narrower set of processes and prevents it from tapping into the vast amount of unstructured data that exists in most organizations.
- Process complexity: While traditional RPA has transformed task automation, it faces inherent limitations in handling complex processes. Complex processes often involve intricate workflows, dynamic data inputs, and frequent changes, which makes them challenging for RPA to manage effectively.
Artificial intelligence (AI) plays a pivotal role in addressing the limitations of traditional RPA. By incorporating AI capabilities such as Machine Learning (ML), Natural Language Processing (NLP), and cognitive reasoning, Intelligent Automation (IA) extends the reach and effectiveness of automation far beyond what RPA alone can achieve.
AI-driven Intelligent Automation applications can analyze and interpret unstructured data, enabling them to extract insights, make predictions, and generate actionable recommendations. This capability is critical for tasks that involve processing emails, analyzing customer feedback, or extracting information from images and videos. Moreover, AI’s ability to learn, adapt, and make predictions empowers IA to handle complex processes that require human-like intelligence. This includes tasks like fraud detection, risk assessment, customer service resolution, and predictive maintenance.
Proven Benefits of Intelligent Automation
Productivity Enhancement and Cost Savings
Intelligent Automation plays a crucial role in streamlining processes and automating repetitive tasks, freeing up employees from mundane, time-consuming activities and allowing them to focus on high-value, strategic initiatives. This shift in focus leads to significant productivity gains, reduced operational costs, and improved resource allocation.
Studies show that Intelligent Automation delivers average cost reductions of over 58% by eliminating the need for manual labor, expanding teams, and reducing errors. This cost-saving potential is particularly attractive to organizations seeking to optimize their operations and maximize profitability.
Enhanced Accuracy and Data Integrity
RPA and AI, the core components of IA, work in tandem to eliminate human error, a prevalent source of inaccuracies and inconsistencies in business processes. By automating data entry and verification tasks, Intelligent Automation ensures data integrity and accuracy, fostering informed decision-making and risk mitigation.
This increased accuracy is particularly beneficial in critical areas such as financial transactions, regulatory compliance, and customer data management. Robust data integrity ensures the reliability of information and protects organizations from potential errors and penalties.
Improved User Experience and Relationship Management
Intelligent Automation transforms customer service by providing faster, more personalized interactions. AI-powered chatbots and virtual agents can handle routine customer inquiries, resolve issues promptly, and provide tailored recommendations. This enhanced customer service experience leads to increased satisfaction, loyalty, and customer advocacy.
Seamless communication and collaboration across departments are also facilitated through the use of Intelligent Automation, which breaks down silos and fosters a unified approach to customer engagement. By providing a holistic view of customer interactions, Intelligent Automation enables organizations to tailor their offerings and strategies to meet individual customer needs.
Streamlined Operations and Reduced Cycle Times
Intelligent Automation seamlessly integrates with existing systems and workflows, automating processes across departments and eliminating manual data entry errors. This streamlines workflows, reduces cycle times, and improves overall operational efficiency, leading to significant cost savings and improved customer satisfaction.
Organizations also adapt to changing market demands and customer needs with greater agility through the adoption of IA. By analyzing real-time data and identifying patterns, Intelligent Automation can make proactive adjustments to processes, ensuring business agility and resilience.
Conclusion
Intelligent Automation has emerged as a transformative force in today’s business landscape, delivering wide-ranging benefits. By combining the power of RPA with Artificial Intelligence, IA empowers organizations to streamline operations, enhance customer experiences, reduce costs, and demonstrably improve productivity. We will see exponential growth as more and more companies identify use cases where Intelligent Automation can deliver these critical benefits.
If you have questions about Intelligent Automation, or if you would like to determine how and where this technology can specifically benefit your organization, reach out to us. We invite you to a free consultation with one of our automation experts. Click below to schedule an appointment.
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