Robotic Process Automation (RPA) and Artificial Intelligence (AI) have garnered a lot of hype lately driving never-before-seen productivity across businesses!
The global RPA market is showing an interesting growth and is poised to reach US$10.7 billion by 2027, and its bigger cousin the AI market is forecast to reach a monumental US$390.9 billion by 2025. However, despite the many conversations these promising disruptive technologies have sparked recently, there is still a lot of confusion that looms over the crucial differentiating factors, USPs, and how both these technologies increasingly to work in an amazing tandem.
Modern tech-powered enterprises integrate both simple processes and those rich in complex decision making, needing a set of complementary technologies to handle the full range of their workflows. RPA and AI combine to form a winning team, Robotic Process Automation systems have a clear, step-by-step flow, while Artificial Intelligence powers to augment and improve human-inspired machine decision making a complex mix-a-mix. Together they transform the future of organisational profitability and stakeholder commitment.
RPA is the core automation technology, also touted as the backbone to the automated interaction with digital systems. Praised to relieve humans of repetitive, time-consuming, and non-value-added work, RPA works best when it is deployed to handle rule-based processes where workflows have a pre-determined set of workflows and time schedules.
RPA is deployed in Enterprises for-
• Excel Automation
• Extracting and processing structured content
• E-Mail management
• Web-data scraping
RPA is often credited to be the stepping stone of Digital Transformation (DX) —the number one strategic technology trend for 2020 according to Gartner Top 10 Strategic Technology Trends for 2020 report—RPA paves the way for future tools technologies like AI, machine learning, and process mining.
No thumb rule determines when enterprises should jump into the Intelligent Automation bandwagon. A well-constructed approach is to start an enterprise automation journey by first tackling those rule-based processes that are deemed too complex for RPA alone, like customer onboarding in banking to insurance claims processing to finance & accounting automation.
Here is an AI RPA Takeaway-
• Workflows which are too complex like legal contract scrapping, loan defaults, and inventory forecasts.
• Highly variable processes that may have a different structure formation like resume matching, and language translation.
• Unstructured data extraction from images, videos, and texts like invoice extraction, and converting speech to text.
Summing up, Intelligent Automation is the future, an immensely powerful technology that not only gives enterprises their own Robotic Center of Excellence (CoE) but formulates a roadmap for quick wins that is beyond completion that enterprises can later scale with Hyper Automation.
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