The “Rise of Robotic Process Automation (RPA) and Cognitive Automation” report has been added to ResearchAndMarkets.com’s offering.
This research service provides an overview of current and emerging RPA trends, applications, and challenges.
Digitalization is gradually replacing paper-based tasks with digital processes. Standardized and monotonous processes are prime candidates for automation through robotic process automation (RPA), which deploys software bots replicating and automating procedures across applications and environments. RPA automates repetitive, labor-intensive, and time-consuming tasks, minimizing or eliminating human involvement to drive faster and more efficient processes.
RPA has demonstrated its advantages in simple, non-decision-making processes. Industries are now considering cognitive automation, or cognitive RPA, to automate more complex functions. With technologies such as artificial intelligence and natural language processing, cognitive RPA can become a crucial component in an organization’s digitalization strategy.
While technological advancements in RPA systems have spurred the development of knowledge-based automation, true cognitive RPA is still nascent. Almost all major RPA deployments have no actual decision-making capabilities.
The study also covers the following:
- RPA and cognitive automation/RPA
- Challenges in RPA implementation
- Trends in RPA
- Significance of RPA in the insurance industry
- Notable companies delivering RPA solutions
- Growth opportunities for RPA vendors
Key Topics Covered:
1. Strategic Imperatives
1.1 Why Is It Increasingly Difficult to Grow? The Strategic Imperative: Factors Creating Pressure on Growth
1.2 The Strategic Imperative
1.3 The Impact of the Top Three Strategic Imperatives on Robotic Process Automation (RPA)
1.4 Growth Opportunities Fuel the Growth Pipeline Engine
2. Research Scope and Methodology
2.1 Research Scope
2.2 Research Methodology
2.3 Research Process and Methodology
3. From RPA to Cognitive Automation
3.1 RPA Automates Standardized and Repetitive Processes with Minimal Decision-Making
3.2 RPA Can Use AI to Develop Basic Decision-Making Capabilities and Automate Complex Tasks
3.3 Cognitive Automation Can Be Built on Top of Intelligent Business Applications
4. RPA Challenges and Potential Solutions
4.1 Successful RPA Projects Need Strong Collaborations between IT and Functional Teams
4.2 Organizations Risk Inducing Additional Complexities in the Environment by Undertaking Heavily “Sandboxed” Pilot Projects
4.3 Organizations Are Motivated to Reduce Costs and Automate Repetitive Tasks
5. Trends in RPA
5.1 RPA Deployment Will Continue to Grow
5.2 Emerging Challenges to RPA Deployment Scalability
5.3 Rise of Build-Your-Own-Bot and No-Code Development Concepts
5.4 Companies Prefer Cloud RPA Deployments and See the Potential of AI in Automation
5.5 Urgent Need to Update Applications and Upskill Employees
6. RPA in Insurance
6.1 Insurance Providers Can Explore RPA to Meet Personalization and Quick Execution Demands
6.2 RPA Can Automate or Accelerate Insurance Processes at Every Stage Depending on the Task Complexity
6.3 RPA Cannot Handle Complex Customer Queries or Assess Losses to Insured Properties
6.4 Insurance and the Larger BFSI Industry Are Key Adopters of RPA Technologies
7. Companies to Watch
7.1 Blue Prism, UK
7.1.1 Intelligent Automation Platform
7.2 Kryon, Israel
7.2.1 Full-Cycle Automation Suite
7.3 NICE, Israel
7.3.1 Robotic Process Automation
7.4 Automation Anywhere, US
7.4.1 Automation 360
7.5 UiPath, US
7.5.1 Enterprise RPA Platform
8. Growth Opportunity Universe
8.1 Growth Opportunity 1: Industry-specific RPA Product Offerings for Unique Customer Needs
8.2 Growth Opportunity 2: AI-based Decision-making Capabilities to Augment Cognitive RPA
8.3 Growth Opportunity 3: No-code RPA and Citizen Developers to Boost RPA Adoption
9. Key Recommendations
9.1 Recommendations for RPA Adopters
10. Key Contacts
Companies Mentioned
- Automation Anywhere
- Blue Prism
- Kryon
- NICE
- UiPath
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