Robotic Process Automation (RPA) automates various manual tasks or actions. Robots (or Bots) help run actions or tasks with a greater efficiency than that of humans. RPA is process driven and automates repetitive, rule-based processes that require interaction with multiple, disparate IT systems.
RPA use-cases can be generic such as invoice processing, email segregation, HR processing etc. or industry focused catering to Financial Services, Insurance, Manufacturing etc.
Also, RPA is useful in scenarios where data is structured, templates are pre-defined and all process scenarios are known upfront.
AI is the ability of a machine or software program / application to exhibit human intelligence. AI is typically a combination of cognitive automation, machine learning (ML), reasoning, hypothesis generation and analysis, natural language processing and intentional algorithm mutation producing insights and analytics at or above human capability.
AI and ML are data driven hence useful in managing scenarios that are dynamic and dependent on data. Also, AI and ML have the capability to learn at run time from processes that are complex hence can go beyond pre-defined rules.
AI and ML are useful in scenarios where data is semi-structured or unstructured hence are highly dependent on data quality rather than pre-defined rules.
AI and ML are logical next steps for RPA in the digital stairways to Intelligent Automation (IA) that can be completed by capabilities such as Optical Character Recognition (OCR).
IA complemented by OCR could be the much needed catalyst for Digital Transformation across various industries and scenarios.
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