RPA Paired With AI Opens Up A New World Of Automation

In the quest for automation's promised return on investment, the fusion of Robotic Process Automation (RPA) with Artificial Intelligence (AI) has ushered in an era of hyperautomation. This dynamic integration, often referred to as the union of multiple automation capabilities, is redefining the landscape of business processes.

The challenges encountered with pre-AI RPA were intricately tied to the intricacy and variability inherent in seemingly straightforward tasks. Take, for instance, the desire to deploy a bot for analyzing invoices and directing them to the appropriate contacts within an organization. What might appear simple on the surface becomes a complex undertaking as standardizing every invoice becomes a prerequisite, or programming the bot to navigate through myriad document variations becomes a costly necessity.

The introduction of AI introduces a layer of intelligence that transcends the limitations of standalone RPA. While RPA operates within the realm of structured and objective tasks, AI extends the scope to encompass nuanced, subjective, or unstructured data. Through the amalgamation of RPA and AI, businesses can automate a broader spectrum of their processes, unlocking capabilities such as:

1) Accurate Document Processing:

AI trains models to precisely read and sort diverse documents, eliminating the need for manual bot programming for varying formats.

Real-world example: Collaboration between Centric Consulting and UiPath enabled World Wide Technology to automate the management of purchase orders across various formats and languages.

2) Interpreting Free-Form Text:

AI-powered bots can comprehend unstructured data like emails and chats, streamlining the sorting process.

Application: Use of AI to read and categorize customer emails, freeing up employees for more strategic tasks.

3) Image Analysis:

AI-infused RPA tools can scrutinize images, identifying discrepancies or errors.

Instance: A food and beverage client of UiPath utilized AI automation to inspect design drafts, ensuring accuracy and efficiency.

4) Complex Reporting Automation:

AI-enabled RPA eliminates labor-intensive backend work involved in producing complex reports.

Case Study: A global oil and gas company streamlined the processing of production operation reports, saving time and enhancing decision-making.

5) Classifying Complex Information:

Custom machine learning models enhance RPA capabilities in tasks like loan assessment, automating a significant portion of manual work.

Example: An Australian mutual bank modernized its loan application process by automating the classification of living expenses.

As the examples above showcase, hyperautomation's potential is vast and impactful. The convergence of RPA and AI has propelled the growth of the RPA software market, reaching $2.8 billion in 2022 with a remarkable 22.1% growth rate (Gartner). This synergy presents an opportune moment for businesses to reevaluate and embrace automation, with readily available out-of-the-box options and tunable AI models for customization.

In conclusion, companies that seize the opportunity to automate processes through hyperautomation will not only capture efficiency gains but also elevate the working experience for their teams, setting the stage for sustained success in an increasingly automated business landscape.