Text Analytics Leads the Way
Forrester: Look to Four Use Case Categories to Push RPA and AI Convergence
From reducing human effort in invoice processing to text analytics that sort unstructured data, RPA’s rapid growth has wildly exceeded expectations as more and more companies are realizing its profound benefits. But why? As new artificial intelligence (AI) building blocks emerge, companies can expect to gain greater value from automation solutions. Artificial intelligence won’t replace RPA, but RPA tools that use AI will replace legacy RPA tools. IT professionals must understand the role that RPA and AI will play together and prioritize RPA use cases based on their AI potential.
Forrester’s ‘Look to Four Use Case Categories to Push RPA and AI Convergence’ report outlines several important takeaways around the convergence of RPA and AI, including:
- RPA progress has centered on simple, high-volume tasks
- Each RPA and analytics combination uses RPA in a different way, affecting platform choices
- Text analytics is the brightest near-term area, as unstructured data requires special handling
A good example of RPA and AI Convergence can be found in products such as EPAM’s InfoNgen – EPAM’s InfoNgen has been recognized by Forrester in this report as a representative option for text analytics. Using natural language processing (NLP), topical classification, tagging and annotation, InfoNgen has improved automation rates and process accuracy across various RPA use case.
Download a copy of the report on Forrester.com to learn more.
To learn more about why InfoNgen was listed as one of Top Eight Providers That Matter Most in The Forrester Wave™: AI-Based Text Analytics Platforms, Q2 2018 and receives the highest possible score in seven criteria download a complimentary copy of this report.
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