التقنية : الميتافيرس
- AR Version
- Pathway: AI Literacy Core
الإلمام المهني بالذكاء الاصطناعي للوكلاء الذاتيين ™
AI Literacy for Autonomous Agents (AILC-AA)™ Workshop | Pathway Mandatory
( Mandatory Foundational Track for AI AgenticVerse™ Pathways)
AILC-DP™ builds essential AI literacy for professionals, leaders, auditors, and compliance roles to responsibly oversee, govern, and approve AI-driven decisions across digital organizations.
- Last updated : January 3, 2026
- 4.721 students
About the Workshop
AI Literacy for Autonomous Agents™ (AILC-AA™) is the mandatory foundational AI literacy course for the AI AgenticVerse™ pathways.
It prepares professionals to understand how autonomous agents think, act, interact, and fail, and how autonomy fundamentally changes risk, responsibility, governance, and security.
The course introduces high-level agent architecture concepts (without code) and focuses on human-in-the-loop control, escalation, and accountability, ensuring learners are ready before entering advanced agentic roles such as AAD™, AABL™, AABP™, AASS™, and AAIP™.
The course is designed for those interested in the design, implementation and responsible use of artificial intelligence systems and products within their organization.
- – Professionals working with or overseeing autonomous AI agents
- – Agentic AI developers and architects (pre-technical readiness)
- – Business leaders deploying agent-based AI systems
- – AI governance, risk, and oversight professionals
- – AI security specialists and SOC leaders (agent awareness layer)
- – Industry practitioners adopting agentic AI solutions
- – Agentic AI Developer (AAD™)
- – Agentic AI Business Leader (AABL™)
- – Agentic AI Business Professional (AABP™)
- – Agentic AI Security Specialist (AASS™)
- – Agentic AI Industry Practitioner (AAIP™)
- – What autonomous AI agents are — and what they are not
- – How autonomy changes decision-making and system behavior
- – Where autonomous agents fail or behave unpredictably
- – How agents interact with tools, data, APIs, and environments
- – Why autonomy creates new accountability and governance gaps
- – How to recognize agent-related security and safety risks
- ✓ Avoid deploying or approving autonomous agents without understanding autonomy risks
- ✓ Gain confidence to question agent decisions and behaviors
- ✓ Reduce operational, safety, and reputational risks caused by agent misuse
- ✓ Understand where human override and escalation are mandatory
- ✓ Prepare safely for advanced AI AgenticVerse™ certifications
- – Autonomy Awareness: Understand how autonomous agents reason and act
- – Agent Risk Interpretation: Identify risks unique to autonomous behavior
- – Oversight & Control Judgment: Know when human intervention is required
- – Accountability Mapping: Understand responsibility in agent-driven actions
- – Agent Security Awareness: Recognize non-traditional threats from agentic systems
- ✓ Autonomous Agent Fundamentals: What autonomous agents are, how they operate, and how they differ from traditional AI systems.
- ✓ Autonomy & Decision Behavior: How agents plan, decide, and act independently — and where autonomy breaks down.
- ✓ Agent Architecture (Conceptual): High-level understanding of agent components, tools, memory, and orchestration (no code).
- ✓ Risk, Safety & Control: New risks introduced by autonomous behavior, including loss of control and unintended actions.
- ✓ Agentic AI Security Awareness: Understanding agent misuse, tool abuse, and autonomy-driven threat scenarios.
- ✓ Governance & Accountability for Agents: Human oversight, escalation, and responsibility in autonomous systems.
- ✓ Agentic AI Literacy: Understand autonomous agent behavior and limitations.
- ✓ Autonomy Risk Awareness: Identify risks introduced by agent independence and goal-seeking behavior.
- ✓ Oversight & Escalation Judgment: Know when agents must be supervised, paused, or overridden.
- ✓ Governance & Accountability Awareness: Recognize who is responsible when agents act autonomously.
- ✓ Agent Security Awareness: Maintain non-technical awareness of threats unique to autonomous agents.
- ✓ Responsible AI and autonomous system principles
- ✓ AI safety and autonomy governance concepts
- ✓ Emerging global guidance on agentic AI risks
- ✓ Human-in-the-loop and human-on-the-loop frameworks
- ✓ AI risk management best practices (conceptual alignment)
- ✓ Optional & Recommended: Pass the Certificate : AI Literacy Core – AILC™
- ✓ General AI literacy or professional exposure to AI systems
- ✓ Experience in technology, business, governance, or security roles
- ✓ No coding or agent development experience required
- – Course Students Study Notes – Online version Only
- – AI-security literacy reference guides
- – Certificate of completion upon passing assessment
Service Guide
1. Implementation Manual
- Step-by-step instructions on how to implement the ISO/IEC 42001 standard.
- Detailed processes, templates, and best practices.
1. Printed Materials
- – Physical copies of guides, templates, and notes.
2. Digital Resources
- – Downloadable PDFs and editable documents.
- – Online access to tools and software platforms.
3. Workshops and Webinars
- – Interactive workshops for hands-on practice.
- – Live and recorded webinars for remote learning.
4. Certification Exam Preparation
- – Practice exams and sample questions.
- – Study guides focused on certification requirements.
Practices
Practices for the ISO/IEC 42001 Course
English
1. Interactive Workshops:
Hands-on sessions where participants work on real-world scenarios.
Group activities to encourage collaboration and knowledge sharing.
Practical exercises to apply concepts learned.
2. Case Study Analysis:
In-depth examination of successful ISO/IEC 42001 implementations.
Discussion of challenges faced and solutions applied.
Lessons learned and best practices.
3. Risk Assessment Exercises:
Identifying and evaluating AI-related risks.
Developing risk mitigation strategies.
Using provided templates and tools for risk management.
4. Compliance Audits:
Conducting mock internal audits.
Reviewing compliance checklists and documentation.
Identifying areas for improvement and developing action plans.
5. Role-Playing Scenarios:
Simulating real-world situations to practice decision-making.
Role-playing different stakeholders to understand various perspectives.
Problem-solving tasks to reinforce learning.
6. Policy and Procedure Development:
Creating AI management policies using provided templates.
Developing standard operating procedures for AI tasks.
Customizing documents to fit organizational needs.
7. Ethical and Legal Considerations Workshops:
Discussing ethical implications and legal requirements of AI.
Analyzing case studies on ethical dilemmas.
Developing strategies for ethical AI management.
8. Software Tools Training:
Hands-on training with AI management software or platforms.
Demonstrating how to use tools effectively.
Practice sessions to build proficiency.
9. Q&A Sessions and One-on-One Consultations:
Scheduled sessions for participants to ask questions.
Opportunities for individual consultations with instructors.
Addressing specific concerns and providing tailored advice.
10. Certification Exam Preparation:
Practice exams and sample questions.
Study guides focused on certification requirements.
Tips and strategies for successful exam performance.
Arabic
1. ورش العمل التفاعلية:
جلسات عملية حيث يعمل المشاركون على سيناريوهات واقعية.
أنشطة جماعية لتعزيز التعاون وتبادل المعرفة.
تمارين عملية لتطبيق المفاهيم المكتسبة.
2. تحليل دراسات الحالة:
فحص متعمق لتنفيذات ناجحة لمعيار ISO/IEC 42001.
مناقشة التحديات التي واجهتها والحلول المطبقة.
الدروس المستفادة وأفضل الممارسات.
3. تمارين تقييم المخاطر:
تحديد وتقييم المخاطر المتعلقة بالذكاء الاصطناعي.
تطوير استراتيجيات التخفيف من المخاطر.
استخدام القوالب والأدوات المقدمة لإدارة المخاطر.
4. تدقيق الامتثال:
إجراء تدقيقات داخلية وهمية.
مراجعة قوائم التحقق ووثائق الامتثال.
تحديد مناطق التحسين وتطوير خطط العمل.
5. سيناريوهات لعب الأدوار:
محاكاة مواقف واقعية لممارسة اتخاذ القرارات.
لعب أدوار أصحاب المصلحة المختلفين لفهم وجهات النظر المختلفة.
مهام حل المشكلات لتعزيز التعلم.
6. تطوير السياسات والإجراءات:
إنشاء سياسات إدارة الذكاء الاصطناعي باستخدام القوالب المقدمة.
تطوير إجراءات التشغيل القياسية لمهام الذكاء الاصطناعي.
تخصيص الوثائق لتناسب احتياجات المنظمة.
7. ورش العمل حول الاعتبارات الأخلاقية والقانونية:
مناقشة التداعيات الأخلاقية والمتطلبات القانونية للذكاء الاصطناعي.
تحليل دراسات الحالة حول المعضلات الأخلاقية.
تطوير استراتيجيات لإدارة الذكاء الاصطناعي بشكل أخلاقي.
8. تدريب على أدوات البرمجيات:
تدريب عملي على إدارة البرمجيات أو المنصات المستخدمة في الذكاء الاصطناعي.
عرض كيفية استخدام الأدوات بشكل فعال.
جلسات تدريب لبناء الكفاءة.
9. جلسات الأسئلة والأجوبة والمشاورات الفردية:
جلسات مجدولة لطرح الأسئلة من قبل المشاركين.
فرص للتشاور الفردي مع المدربين.
معالجة القضايا المحددة وتقديم نصائح مخصصة.
10. التحضير لامتحان الشهادة:
اختبارات تجريبية وأسئلة نموذجية.
أدلة دراسية تركز على متطلبات الشهادة.
نصائح واستراتيجيات لتحقيق أداء ناجح في الامتحان.
By incorporating these practices into the course, participants will gain practical experience and confidence in implementing the ISO/IEC 42001 standard, preparing them effectively for real-world application and certification.
- – Course Introduction
- – Certificate Introduction & Exam Details.
Purpose
To establish a clear understanding of what autonomous agents are and why they represent a new class of AI systems.
Topics & Sub-Topics
Definition of autonomous and agentic AI
Agents vs traditional AI systems
Levels of autonomy
Why autonomy changes responsibility
Purpose
To explain how agents plan, decide, and execute actions independently.
Topics & Sub-Topics
Goal-driven behavior
Planning, reasoning, and action loops
Agent memory and context
Decision confidence vs correctness
Purpose
To provide high-level visibility into how agentic systems are structured.
Topics & Sub-Topics
Agent components (LLMs, memory, tools)
Tool and API interaction
Orchestration concepts
Environment interaction
Purpose
To identify where autonomous agents fail or behave unpredictably.
Topics & Sub-Topics
Hallucination and goal misalignment
Unintended actions and runaway behaviors
Feedback loops and compounding errors
Safety boundaries and guardrails
Purpose
To introduce security risks unique to autonomous agents.
Topics & Sub-Topics
Agent misuse and abuse scenarios
Tool abuse and privilege escalation
Prompt injection in agent workflows
Supply-chain and integration risks
Purpose
To establish governance models and accountability for autonomous agents.
Topics & Sub-Topics
Human-in-the-loop vs human-on-the-loop
Escalation and override principles
Accountability for agent actions
Governance boundaries
Purpose
To understand real-world agent use cases and organizational impact.
Topics & Sub-Topics
Agentic workflows in business operations
Industry adoption patterns
Organizational readiness indicators
Risk vs value trade-offs
Purpose
To validate autonomous-agent literacy, judgment, and readiness.
Topics & Sub-Topics
Scenario-based autonomous agent cases
Autonomy risk identification
Governance and escalation judgment questions
Certification readiness for AgenticVerse™ pathways
Successful completion of AILC-AA™ enables entry into:
Agentic AI Developer (AAD™)
Agentic AI Business Leader (AABL™)
Agentic AI Business Professional (AABP™)
Agentic AI Security Specialist (AASS™)
Agentic AI Industry Practitioner (AAIP™)
AILC-AA™ ensures professionals understand autonomy, risk, and responsibility before trusting AI agents to act independently.
- – Agentic AI Literacy Map: A visual framework explaining how autonomous agents perceive, decide, act, and escalate—without diving into code.
- – Human-in-the-Loop & Override Checklist: A practical checklist to identify where human control, approval, or shutdown must exist in agentic systems.
- – Agent Autonomy Boundary Matrix: A decision tool defining what agents can, should, and must not do across business, security, and operational contexts.
- – Agent Accountability & Responsibility Map: Clarifies ownership across designers, operators, leaders, and organizations when agents act autonomously.
- – Agent Failure & Misbehavior Awareness Guide: A structured overview of common agent failure modes, hallucinations, goal drift, and unintended actions.
- – Agentic Risk Awareness Canvas: A lightweight canvas to identify risk exposure introduced by autonomous agents (ethical, operational, reputational).
- – AI Agent Trust & Decision Confidence Scale: Helps participants assess when agent outputs can be trusted, challenged, or escalated.
- – Agentic Governance Awareness Brief: High-level governance principles for deploying autonomous agents responsibly—aligned with future advanced tracks.
Certificate/accreditation and examination
1. The importance of certification:
- Journalists and content creators who work in various media outlets and want to keep up with technological developments.
2. The Exam:
- Journalists and content creators who work in various media outlets and want to keep up with technological developments.
3. Certificate and accreditation:
Attendance Testimonials
1. مقدمة عن التقنيات الحديثة في الإعلام:
- تعريف بالذكاء الاصطناعي والميتافيرس.
- أهمية تطبيقاتهم في مجالات الصحافة والإعلام والثقافة.
Q&A
1. مقدمة عن التقنيات الحديثة في الإعلام:
- تعريف بالذكاء الاصطناعي والميتافيرس.
- أهمية تطبيقاتهم في مجالات الصحافة والإعلام والثقافة.
Evaluate to Obtain a Certificate of Attendance
التقييم انتهى ، نراكم في محاضرات أخرى
Ramy AlDamati
General Informations
- – Delivery Languages : Arabic or English.
- – Material Languages : Arabic or English.
- – Delivery Format: Inperson , or Self-teaching video lectures.
- – Access from any device and from anywhere.
- – Internationally recognized certificate of attendance.
- – CPE/CPD credits.
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Plan Your Next Steps
These next steps provide Customers with a clear pathway to certification, practical tools for success, and continued professional development.
Join Classroom
Attend live, interactive sessions either online or Recorded inperson for a collaborative learning experience. Sessions led by industry experts, offering opportunities for networking, hands-on exercises, and real-time discussions to deepen their understanding of AI governance and oversight.
Take the Exam
Attendees who complete the program exam successfully will earn the prestigious certification. This globally recognized credential validates their expertise in AI governance, strategic oversight, and implementation. Achieving this certification demonstrates a professional's ability to lead AI initiatives ethically and effectively, and alignment with organizational objectives.
Study Materials
Receive comprehensive study materials and Body of Knowledge (BoK)— a curated repository of essential concepts, frameworks, and tools in AI governance, strategy, and deployment. Resources are designed to reinforce learning and provide ongoing support throughout their professional journey.
ISO 42001 Services
To implement an AIMS, you will need a solid understanding of ISO/IEC 42001's requirements. We have training to provide the required knowledge. Once the system is in place, we can offer a gap assessment. After the successful completion of an audit, we will issue your certificate, confirming the effective implementation of the standard's requirements. An audit against ISO/IEC 42001 from us will help your organization to stand out from the crowd by supporting you to develop and improve performance.
AI Literacy Preparedness Tooling™
The DASO Toolkit equips Professionals with practical resources to oversee AI initiatives. It includes templates for governance policies, risk assessment frameworks, compliance checklists, and tools for managing AI projects and teams. This toolkit ensures Professionals are prepared to apply their skills immediately within their organizations.
AI Literacy Knowledge Resources
Knowledge Guides are a series of detailed, expert-authored documents that delve into specialized topics such as AI risk management, ethical AI practices, and regulatory compliance. These guides serve as valuable references, helping professionals stay informed and make informed decisions as they oversee AI initiatives.
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Meet our Instructors
Ramy AlDamati
ServME ACADEMY
Noor Zahran
Nidal Talib
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