Technical Considerations for Solution Design - AI Powered Automation

1. Technical Considerations for
Solution Design –
AI Powered Automation
04-September-2023

2. Thank You Team !
NikhileshSathyavarapu PradeepChinnala
AssociateManager,Sutherland SeniorRPAConsultant–WonderBotz,
UiPathMVP

3. Powered by Supported by

4. Key Speaker
UiPath AI ambassador APAC
4 X UiPath MVP
RPA Lead (APAC)/ Practice Lead for Document Understanding and
AI
Boundaryless Group
Lahiru
Fernando

5. Agenda
• What is AI powered automation?
• Major aspects to consider for AI powered automation?
• Technical considerations
• What is intelligent automation/ hyper automation/ how
automation solution architect needs to be ready
• What are the design techniques for Ai powered automation
solution

6. 6
What is AI Powered Automation

7. What is AI Powered Automation
• AI Powered Automation is about integrating of AI technologies with
traditional automation processes, aiming to enhance decision-
making, optimize operations, and improve efficiency.
• It introduces cognitive capabilities to mimic human-like reasoning
and understanding.

8. Why AI in Automation
• AI is the perfect complement to RPA, together providing more
accurate and efficient automation.
• RPA – automating repetitive rule-based activities
• AI – Introduces intelligent tools to simplify processes
• RPA + AI = Brings Intelligent Automation to automate complex
processes
Increase
productivity
Reduce
Costs
Improved
Accuracy
Improved
Customer
Experience

9. Why AI in Automation
• AI is no longer optional in RPA
• Evolution: AI is the driving force behind enabling RPA to handle
complex, unstructured data and dynamic scenarios
• Complexity: The data organizations work with today are often
unstructured. AI equips RPA with the ability to analyze, understand,
and extract insights from this data
• Decision-Making: AI enables automation to understand context,
learn, and respond intelligently to changing conditions.

10. AI Technologies
Machine Learning
Natural Language Processing
Computer Vision
Decision-
Making
Predictions
Pattern
Recognition
NLP NLG
Sentiment
Analysis
Entity
Recognition
Image
Recognition
Object
Detection
OCR/ ICR

11. AI in Automation
Robotic Process Automation
Document Processing
Computer Vision
Natural Language
Processing
Machine Learning

12. AI Components in UiPath
Document
Understanding
Image Analysis
Language
Analysis
Task Mining
Custom
Activities
Extraction
Models
Solution
Accelerators

13. AI Components in UiPath
Image Analysis
•Object Detection
•Image Moderation
Tabular Data Analysis
•Classification
•Regression
Language Processing
•Text Summarization
•Question Answering
•Text Translation
•Language Detection
•Text Classification
•Named Entity Recognition
•Sentiment Analysis
•Semantic Similarity
Document Processing
•Document Classification
•Content Extraction

14. 14
Points to Consider for AI Powered
Automation

15. Considerations for AI Powered Automation
Discover
Decide
Act
Optimize
Identify
Processes
Identify
Bottlenecks
Data Quality
Technology
Integrations
Process
Suitability
Prioritize
Processes
Technical
Approach
ROI
Process
Improvement
Building AI
Models
Technical
Integrations
Feedback
Loops
Transparency
Improve
Automations

16. Considerations for AI Powered Automation
Identify
Processes
Identify
Bottlenecks
Process
Suitability
Process
Improvement
ROI
Prioritize
Processes
Data Quality
Technical
Feasibility
Technology
Integrations
Technical
Approach
Feedback
Loops
Continuous
Improvement
Process
Technology

17. 17
Role of a Solution Architect in AI
Powered RPA Initiatives

18. How an RPA Solution Architect Can be Ready?
Ways to Upskill
Understand AI Fundamentals
Follow AI Trends
AI Integration
Collaborate with Data Scientists
Explore AI Ready Tools
Expand Process Analysis

19. Approach to Designing AI Powered Automation
Solutions
Identify areas where AI is required in automation
Identify the exact AI requirement and technical feasibility
Gather data for training/ fine-tuning models
Work with data scientists to cleanup the data and build a model
Plan for pilot implementation
Design the architecture for the automation solution
Introduce feedback loops in the design architecture for model fine-tuning
Plan evaluation and testing approach
Plan for monitoring and maintaining AI based RPA solutions

20. Q&A

21. Quiz

22. Academy
• Get crowdsourced support and share product feedback on UiPath Forum
• Check the product documentation
Forum
Community Events
• Connect with like-minded people and share best practices with the UiPath
Community
• Solve challenges in engaging hackathon competitions
• Join meetups and conferences
• Learn the skills of the future on UiPath Academy or through our Academic Alliance
• Earn globally recognized credentials with UiPath Certifications
Vibrant ecosystem of more than 2 million professionals and citizen developers learning,
getting support and succeeding together in their automation careers.

23. Thank You