Table of Contents
- Market Categories and Deployment Types
- Key Criteria Comparison
- GigaOm Radar
- Vendor Insights
- Analysts’ Take
- About Ben Stanford
Robotic process automation (RPA) solutions are used mostly for UI and surface-level automation and support both unattended and attended automation use cases. RPA solutions provide integration scripts to enable UI-level integration with legacy applications or systems that do not expose an API. While there are tools available to generate REST APIs against legacy back ends, RPA solutions are preferred because of their less-technical approach to automation and faster time to automation.
As enterprises adopted RPA solutions to automate specific tasks and processes, requirements arose for other capabilities, such as intelligent document processing (IDP), API-led integration, and task mining, to automate end-to-end processes. This evolution simply indicates an increased capability of these solutions (along with adjacent products) to support a greater degree of automation for an entire end-to-end process.
Bot stores offering prebuilt components and RPA bots for automating a specific task are now a key requirement for enterprises that have scaled beyond the first couple of dozen RPA bots. API-led integration tools are used when application and data integration can be achieved via APIs. Beyond legacy optical character recognition (OCR) tools, RPA solutions integrate with IDP solutions to enable document ingestion and processing. In other words, they convert semi-structured and unstructured data in documents to a structured format. Task mining empowers organizations to understand how tasks are performed by monitoring user interactions with their workstations. Autogeneration of process design documents (PDDs) for automation opportunities identified via task mining helps RPA developers expand their understanding of end-to-end processes.
While RPA solutions have commoditized to some extent, the overall intelligent automation platform (IAP) market is growing fast, with several new technical developments. RPA vendors have quickly added new tools and capabilities (mostly via acquisitions and partnerships) to address the requirements of intelligent automation use cases. With RPA scalability and bot resiliency being a recurring question, a few RPA vendors have put in efforts to address these issues. We see that lines of demarcation between integration and process automation approaches are blurring, with the traditional friction between deep integration—API-led integration and dedicated application connectors provided by integration platform as a service (iPaaS)—and surface-level automation lessening over the last few years.
There is a greater propensity for RPA solutions to call dedicated AI/ML APIs (as in computer vision APIs) to meet specific requirements of a use case. Another interesting observation is a greater number of RPA implementations have scaled to hundreds and thousands of RPA bots, indicating that RPA, when applied to the correct use cases and governed properly, can deliver positive outcomes. Issues arise when RPA initiative leaders spend too little time on analysis and optimization; they often think of RPA as a hammer and then see most of their business processes as nails to hit. Needless to say, automation of an inefficient business process with RPA will deliver only minimal gains.
This GigaOm Radar report highlights key RPA solution vendors and equips IT decision-makers with the information needed to select the best fit for their business and use case requirements. In the corresponding GigaOm report “Key Criteria for Evaluating RPA Solutions,” we describe in more detail the key features and metrics that are used to evaluate vendors in this market.
How to Read this Report
This GigaOm report is one of a series of documents that helps IT organizations assess competing solutions in the context of well-defined features and criteria. For a fuller understanding, consider reviewing the following reports:
Key Criteria report: A detailed market sector analysis that assesses the impact that key product features and criteria have on top-line solution characteristics—such as scalability, performance, and TCO—that drive purchase decisions.
GigaOm Radar report: A forward-looking analysis that plots the relative value and progression of vendor solutions along multiple axes based on strategy and execution. The Radar report includes a breakdown of each vendor’s offering in the sector.