🚀 Agentic Automation in Action 1/3 – From RPA to Agentic Automation (Arabic Session)

Automation is evolving fast — are you ready to step into the future?
This is the first session of the Agentic Automation in Action series (3 parts), delivered in Arabic and designed for the EMEA community.

What’s inside this webinar?

Quick refresher: What is RPA, and where it excels

UiPath’s AI journey: Specialized AI → Generative AI → Agentic AI

Introduction to agentic automation and its defining traits

Live demo of a simple agentic workflow

Real-world examples and open discussion

1. From RPA to
Agentic Automation
Agentic Automation in Action –Session 1

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Mohamed A. Shaker
Automation Consultant| UiPath MVP
BARQ Systems
linkedin.com/in/mo3bdlaa
Event speaker

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Content
1.Agentic Automation in Action Series
2.UiPath Cairo Community
3.Quick refresher: What is RPA?
4.The evolution of AI and Automation
5.Agentic AI: The hype into numbers
6.What is an AI Agent?
7.Robot vs Agent: unique combination of capabilities
8.UiPath Agentic Components
9.Live Demo

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The first Arabic virtual series to explore Agentic Automation. This series is provided as
a collaboration between Cairo and Dubai UiPath Communities.
Agentic Automation in Action – Arabic Series
Tuesday, Sep 23, 07:00 PM –08:00 PM Tuesday, Sep 30, 07:00 PM –08:00 PM Tuesday, Oct 07, 07:00 PM –08:00 PM
Agentic Automation in Action [1/3]: From RPA to Agentic Automation

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UiPath Community Cairo Chapter – the most recent launched chapter aiming
to support Arabic and EMEA community, to learn, engage, collaborate, and build
an environment of mutual innovation and forward looking.
UiPath Community – The first Arabic Chapter

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RPA stands for Robotic Process Automation, where Software robots
mimic human actions on computers.
Works best for repetitive, rule-based, structured tasks
Common use cases:
•Data entry & validation
•Report generation
•Invoice processing
•Copy-paste between systems
Key Benefit:
Saves time, reduces errors, increases efficiency.
Quick refresher: What is RPA?

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The evolution of AI and Automation
Phase 1: Rule-Based Automation
Basic automation using predefined workflows
and business rules. If-then logic for repetitive
tasks like filling forms and data entry.
Limitations: No adaptability, fails when
encountering exceptions.
Phase 2: AI-Powered Automation
AI-powered tools (ML, NLP, Computer Vision)
made automation smarter, handling variability in
tasks from document understanding to chatbots.
Limitations: Still dependent on human
intervention for complex decision-making.
Example: Specialized AI, Generative AI
Integrations.
Phase 3: Agentic AI, Rise of Autonomous Agents
AI agents that can think, learn, and act
independently with minimal human oversight.
How it works:
• Understands unstructured data & context.
• Makes decisions dynamically.
Example: Instead of a bot just processing invoices,
an AI agent analyzes trends, detects anomalies,
and negotiates with vendors.
Agentic Automation in Action [1/3]: From RPA to Agentic Automation

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Agentic AI: The hype into numbers
Source: Market.us: Agentic AI in Business Automation Market

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What is an AI Agent?
An AI Agent is an intelligent system that perceives its environment, makes decisions, and
takes actions to achieve specific goals — autonomously or with minimal human intervention.

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Robot vs Agent: unique combination of capabilities
RPA Robots Agentic Agents
Follow fixed rules & scripts Act autonomously with context-awareness
Structured data only (forms, spreadsheets)
Structured + unstructured data (emails, docs,
conversations)
must follow pre-set logic Dynamic (can choose best action based on context)
Breaks if process changes Learns & adapts to new situations
needs reprogramming for exceptions can act with minimal oversight
Agentic Automation in Action [1/3]: From RPA to Agentic Automation

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UiPath Agentic Components

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UiPath: Agent Builder

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UiPath: Agent Orchestration - Maestro
Enterprise workflows often involve a mix of deterministic and non-deterministic processes, with
large enterprises typically using over 175 systems. This complexity includes a combination of
legacy and modern applications, a fragmented technology stack, siloed data across disparate
systems, and coordination across multiple internal teams and external stakeholders.

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UiPath: AutoPilot

15. Live Demo
From theory to action: building a digital job-search assistant

16. Any Questions?
Don’t hesitate to reach me on LinkedIn or email: [email protected]