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Critical Capabilities for Robotic Process Automation

Key Findings 

  • Of the reference customers surveyed for this research, 94% indicated that task automation involving the integration of different applications was the most important use case for them. Also, 30% indicated that citizen development was an important use case. 
  • Robotic process automation (RPA) software vendors have enhanced their core RPA offerings by either acquiring or building capabilities such as process mining/process discovery, optical character recognition (OCR), intelligent document processing (IDP) and integration with an intelligent business process management suite (iBPMS). 
  • RPA vendors are evolving their licensing and delivery models. Several now provide subscription-based pricing. Many include PaaS and SaaS offerings and about one-third of customers surveyed by Gartner indicated that they deploy RPA in some form of cloud scenario (hybrid, PaaS or SaaS). 
  • Customers demand security, availability, support, monitoring and change management as key features of an RPA product to ensure they achieve resilient and scalable RPA. 


To effectively assess RPA tools and techniques, application leaders responsible for application architecture, development, integration and platforms should do the following: 

  • Shortlist RPA products for your organization by assessing the needs of both citizen developers and their technical counterparts as they collaboratively build complex automations. 
  • Evaluate the complementary capabilities of RPA suites that have broad functionality, such as process discovery, process mining, broader process automation and machine learning (ML). 
  • Subscribe to different cloud models offered by RPA platforms to accelerate adoption and optimize scalability. 
  • Assess RPA products’ administration, reporting and security features by ensuring your team compares the capabilities of vendors’ orchestrator/control panel dashboards. 

Strategic Planning Assumptions 

By 2022, 80% of RPA-centric automation implementations will derive their value from complementary technologies such as AI/ML, intelligent document processing, process discovery and integrated chatbots to deliver hyperautomation. 

By 2023, 50% of new RPA scripts will be dynamically generated via AI-driven development tools. 

What You Need to Know 

Application leaders should acquire RPA solutions to combine user interface (UI) interactions and APIs that automate processes, and integrate and perform data transcription work between applications. 

Gartner has identified the following four common use cases for RPA: 

  • Task automation via integration — Extracting data from one application and making it available in another where no back-end integration or API is available. 
  • Enabling citizen developers — Empowering citizen developers to build automation scripts using low-code intuitive interfaces, guided navigations and easy generation of workflow design. 
  • Administration and process life cycle management — Reinforces governance of automation across all use cases including segregation of duties, data access and security controls, as well as administration of the environment. 
  • Augmenting knowledge workers — Enhancing the ability of knowledge workers to get work done, typically saving them effort by extracting needed information to better serve customers. 

Gartner has identified eight critical capabilities that address these use cases, and scored the vendors on support for them. For each capability, we identified a set of supporting elements of functionality; for each of those, we developed a specific scoring spectrum or method. Although we provide four use cases for consideration, organizations can adjust the capabilities for a custom analysis. 

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