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RPA will become Robotic Process AI-tomation?

RPA with AI Integration is Trending!

RPA Design, Development, and Operation, AI Trends

The integration of AI with RPA is becoming more important, to transform how RPA design, development, and operations are managed and where AI is set to impact each phase.

RPA Design

  • AI-Driven task and process discovery can analyze vast amounts of data to identify automation opportunities with greater accuracy and speed, and uncover patterns and inefficiencies that might be missed by human analysts.
  • Predictive modeling with AI in which processes are most likely to yield high ROI and suggest the best candidates for automation.
  • Automated design proposals with AI to generate initial automation designs, documentation of workflows, reducing the time and effort required from human designers.

RPA Development

  • Code generation through AI algorithms can write portions of the code needed for RPA bots, especially for standard and repetitive tasks, accelerating the development process and driving low-code / no-code in citizen development.
  • Intelligent debugging with AI will assist in identifying and fixing bugs more efficiently by learning from past errors and applying that knowledge to new development projects.
  • Adaptive learning in AI systems from data to improve the efficiency and effectiveness of RPA bots by continuously optimizing their performance.

RPA Operation:

  • Predictive maintenance through AI capabilities than more accurate predict when RPA bots are likely to encounter issues based on historical data, allowing for high preventive maintenance to minimizing downtime.
  • Real-Time optimization with AI can monitor bot performance and make adjustments on the fly to optimize resource allocation and process efficiency.
  • Dynamic Orchestration where AI will take over to manage the scheduling and workload of RPA bots, ensuring they operate at peak efficiency and adapt to changing conditions without human intervention.

Will AI Take Over RPA Design, Development, and Operation?

While AI will significantly enhance and transform RPA processes, the complete takeover is unlikely in the near term. Instead, the synergy between AI and human expertise will drive the evolution of RPA.

AI is about to revolutionize the design, development, and operation of RPA, making automation more efficient, adaptive, and intelligent. However, the best outcomes will be achieved through a collaborative approach, leveraging the strengths of both AI and human expertise. This partnership will unlock new levels of productivity and innovation, driving significant advancements in how businesses operate.

Human RPA developers and designers will collaborate with AI tools to create more sophisticated and efficient automation solutions. With AI handling routine and repetitive aspects of RPA, human experts can focus on higher-level strategic tasks, such as identifying new areas for automation and improving overall business processes. AI will facilitate continuous improvement by learning from data and feedback, enabling RPA systems to become more intelligent and effective over time.

Robotic Process Automation

  • Ideal for Rule-Based processes and perfect for tasks with clear, step-by-step workflows.
  • Manages tasks like logging into applications, connecting to system APIs, copying and pasting data, extracting structured content from documents, opening emails, and web scraping.
  • Works best with stable workflows that require minimal human intervention or has repeatedly similar tasks in processes.
  • Hyperautomation sets the integration of advanced automation tools like AI, machine learning, and task / process mining.

Artificial Intelligence

  • Expanding automation with AI and RPA together extend automation into new or optimized areas.
  • AI managing complex processes that traditionally required human intervention or exceptions.
  • Predictive analytics with AI identifying patterns and best practices.
  • Failure and bottleneck detection through AI algorithms in operations.
  • Natural Language Processing in chatbots and virtual assistants.
  • Image Recognition e.g. in document reading or quality control in manufacturing.
  • Large data source identification, qualification and information extraction in communication modules such as mail, chat, etc.

Successful RPA / AI Implementation

  • Discovery to understand RPA needs and AI vision, discussing specific processes or broader business goals.
  • Utilizing AI to analyze initial client data and generate insights for a more focused discussion.
  • Analyzing workflows to identify automation opportunities and ensure legal compliance.
  • Implementing AI for advanced process mining and data analysis.
  • Pointee for visualizing process maps, bot performance, and compliance.
  • Choosing a key process for a Proof of Concept (PoC) based on potential ROI and business value.
  • Using AI to predict ROI and impact of automating different processes.
  • Selecting the best RPA tools (e.g., UiPath, Blue Prism, Automation Anywhere) and set up the automation environment.
  • Developing RPA bots tailored to your specific processes, possibly using reusable plugins or pre-existing bots.
  • Integrating AI to create adaptive bots that handle exceptions and learn from new data.
  • Testing the bots in a pre-production environment to ensure they meet your requirements.
  • Applying AI-driven testing tools to simulate various scenarios and ensure robust performance.
  • Pointee to facilitate information from logs, reports, simulation and track testing metrics.
  • Deploying the bots into your production environment, completing your first RPA implementation.
  • Implementing AI monitoring tools for smooth deployment and immediate issue detection.
  • Continuing automating additional processes from the backlog based on their ROI potential.
  • Using AI to reassess and prioritize processes for maximum ROI.
  • Deciding whether to maintain the bots with ongoing support or train your team for in-house management.
  • Deploying AI for predictive maintenance and automatic updates.
  • Pointee to provide insights for CoE training modules and knowledge transfer sessions in RPA.

Pointee Enhancing Your RPA Journey

Real-Time Monitoring

  • Enhanced Monitoring in a user-friendly view of all automations across platforms.
  • AI-Powered Insights and real-time insights into bot performance using AI.
  • Resource utilization and better understanding of resource assignment and resource overload and underperformance.
  • Seamless and easy integration without installing on virtual machines.

Rapid Resolution

  • Faster incident resolution to achieve up to 90% quicker workaround and better resolution.
  • Incident alerts quickly pinpoint issues, reducing Mean Time to Repair and meeting Key Performance Indicators.
  • Root Cause Analysis can swiftly determine the root cause of bot failures and bottlenecks.
  • Process speed improvement experience up to 60% faster execution.

Dynamic Orchestration

  • Reassign digital workforce power and optimize bot assignments, runtime and performance.
  • Efficient bot scheduling to reduce manual scheduling tasks by up to 90%.
  • SLA compliance to ensure 100% Service Level Agreement (SLA) compliance and availability.
  • Vendor-Agnostic with no vendor locks or system-specific endpoints.
  • Resource optimization to maximize resource utility and optimize infrastructure and operational costs.

Automated Reporting

  • Customizable reports can generate fully automated information for reports, dashboards or internal like billing, pay per use, pay per SLA etc.
  • Stakeholder insights to provide relevant information to key people, or units, or clients at the right time.
  • ROI measurement and improve the automation program’s ROI.

Easy Integration

  • Effortless integration can quickly monitor the robots and gather critical or beneficial data.
  • Automation teams empowering the Center of Excellence to innovate beyond have RPA operational tasks and routines.
  • For business stakeholders to unlock RPA insights and advocate automation benefits.
  • For leadership to maximize automation ROI and upscale the automation program.

RPA Mining and Design Examples

In this phase, Pointee works closely with the CoE to identify optimal processes suitable for automation, analyze existing automation and workflows, assess feasibility, and help CoE to design effective RPA solutions.

  • Dynamic Orchestration streamline and optimize your digital workforce, reducing manual tasks in bot scheduling by up to 90%.
  • SLA Compliance to achieve 100% Service Level Agreement (SLA) compliance through reliable process automation.
  • Cost Optimization can maximize resource utility and optimize infrastructure costs, ensuring efficient resource allocation.

RPA Development and Implementation Examples

During this stage, Pointee executes RPA projects based on the design, helping to build, test, and deploy bots to automate specific tasks and to measure performance and availability.

  • Predictive Analytics can rapidly resolve incidents and optimize bot performance, decreasing incident resolution time by up to 90% and identifying root causes of bot failures.
  • Proactive Alerts to receive incident warnings, alerts and predictions related to your Key Performance Indicators (KPIs).
  • Real-Time Monitoring to experience up to a 60% improvement in process speed through efficient automation.

Run and Operate RPA Examples

Once RPA bots are live, Pointee ensures smooth operations, monitoring, and maintenance in the CoE, and can operate on several RPA platforms including Blue Prism, UiPath, Automation Anywhere, or MS Power Automate.

  • Automated Reporting to gain data visibility for strategic decision-making. Measure ROI, customize reports, and deliver timely information to stakeholders.
  • Real-Time Monitoring can access an all-in-one view of your automations. AI-powered insights help you understand bot performance, resource utilization, and management.
  • Predictive Maintenance helps identify potential issues before they escalate, allowing the CoE to address them proactively and prevent downtime.