التقنية : الميتافيرس

الإلمام المهني بالذكاء الاصطناعي™

AI Literacy Core (AILC)™ Workshop | Optional

AI Literacy Core™ (AILC™) is the foundational program that builds AI readiness by explaining how AI works in context, where it fails, and what humans remain accountable for — across roles, sectors, and technologies.

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About the Workshop

AI Literacy Core™ is a foundational AI readiness workshop designed for executives, professionals, and decision-makers who must understand AI before approving, deploying, governing, or relying on it. The course introduces AI as a decision-impacting layer embedded within digital platforms, physical systems, and emerging technologies. It focuses on understanding, judgment, risk awareness, and responsibility, rather than tools, coding, or model development, and serves as the base layer for all advanced MetaServ AI pathways.

The course is designed for those interested in the design, implementation and responsible use of artificial intelligence systems and products within their organization.

– Executives and senior decision-makers responsible for AI initiatives
– Business and technology managers overseeing AI-enabled processes
– Digital transformation and innovation leaders
– Risk, compliance, audit, and governance professionals
– Consultants, advisors, and policy professionals
– University students and professionals seeking AI readiness

– Board Members & Executive Sponsors
– CIO / CTO / CDO Stakeholders
– Digital Transformation Managers
– Risk & Compliance Officers
– AI Program Owners (Non-Technical)
– Policy & Strategy Advisors
– Consultants and Analysts

– What AI is and is not, beyond hype and marketing claims
– How AI influences and amplifies human and organizational decisions
– Where AI fails, misleads, or introduces systemic risk
– How AI interacts with data, platforms, physical systems, and emerging technologies
– Why governance, accountability, and oversight cannot be automated
– How to assess AI readiness before specialization or execution

– Avoid AI adoption driven by hype rather than understanding
– Gain confidence to question AI outputs and assumptions
– Build a shared AI language across teams and stakeholders
– Reduce decision, compliance, and governance risks
– Prepare safely for advanced AI, security, defense, or agentic tracks

– AI Conceptual Literacy: Clear understanding of AI capabilities and limits
– Decision Oversight Skills: Ability to evaluate AI-assisted decisions
– Risk Awareness: Recognizing failure modes and misuse scenarios
– Governance Awareness: Understanding accountability and responsibility boundaries
– Ecosystem Thinking: Seeing AI as part of a larger technology landscape

– AI Fundamentals in Context: Intelligence, automation, and generative systems
– Decision Impact & Human Oversight: AI as a decision multiplier
– Data Awareness (Non-Technical): Bias, leakage, and context risks
– AI & Digital Transformation: Reality vs hype
– AI Across Emerging Technologies: Cloud, immersive systems, automation, platforms
– AI Risk & Responsibility: Misuse, failure, and accountability

– AI Literacy Competency: Understand AI behavior and limitations
– Decision Accountability Competency: Identify where humans remain responsible
– Risk Recognition Competency: Detect early warning signs of AI failure
– Governance Readiness Competency: Understand why AI governance exists
– Pathway Readiness Competency: Enter advanced AI tracks with the right mindset

– ISO/IEC AI governance and risk principles (awareness level)
– NIST AI Risk Management Framework (conceptual alignment)
– Global Responsible AI principles
– Industry best practices in AI governance and digital transformation

– Optional & Recommended: Pass the Certificate : AI Literacy for Defense & Security – AILC-DS™
– Pathway Mandatory : Attend and pass the Certificate : Pass the Certificate : AI Literacy for Defense & Security – AILC-DS™
– General digital literacy
– Basic familiarity with modern business or technology environments
– No AI, coding, or technical background required

– General digital literacy
– Basic familiarity with modern business or technology environments
– No AI, coding, or technical background

– Course Students Study Notes – Online version Only
– Structured learning – slides and reference summaries
– AI readiness conceptual frameworks
– AI decision-awareness checklists
– AI risk & misconception reference guides
– Certification 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.

- Overview

– Course Introduction
– Certificate Introduction & Exam Details.

Module 0 – Orientation & AI Literacy Foundations

Purpose: Establish the correct mental model before learning anything about AI.

Subtopics:

– What “AI Literacy” means vs AI skills vs AI engineering
– Why AI literacy must come before AI adoption
– Common reasons organizations fail with AI
– What AILC™ intentionally covers and excludes
– Position of AILC™ within MetaServ pathways
– AI literacy as a governance and decision prerequisite

Module 1 – Understanding Intelligence: What AI Is (and Is Not)

Purpose: Remove misconceptions about “intelligence” and autonomy.

Subtopics:

– Automation vs Machine Learning vs Generative AI
– Why AI appears intelligent but lacks understanding
– Pattern recognition vs reasoning
– What AI cannot understand: intent, values, context
– The illusion of autonomy and agency
– Why AI is not a human replacement

Module 2 – AI as a Decision Multiplier

Purpose: Shift thinking from “AI tools” to “AI-influenced decisions”.

Subtopics:

– AI as decision support vs decision delegation
– How AI accelerates, amplifies, or distorts decisions
– Human-in-the-Loop as a spectrum, not a switch
– Decision confidence vs decision correctness
– When AI decisions require escalation
– Decisions that should never be fully automated

Module 3 – AI & Data Foundations (Literacy Level)

Purpose: Understand data risks without technical depth.

Subtopics:

– Why data quality matters more than algorithms
– Training data vs operational data
– Data bias and representativeness
– Context loss and data drift
– Why “accurate” AI can still be wrong
– Data ownership and responsibility awareness

Module 4 – AI & Digital Transformation Reality Check

Purpose: Separate real transformation from AI hype.

Subtopics:

– Digitization vs Digitalization vs – Digital Transformation
– AI-Driven Transformation vs tool deployment
– Why AI fails without process redesign
– Organizational readiness vs technical readiness
– Culture, incentives, and decision ownership
– Warning signs of superficial AI adoption

Module 5 – AI in the Emerging Technology Ecosystem

Purpose: Understand AI in context, not isolation.
5.1 Immersive & Spatial Technologies
- – AI in Metaverse, Digital Twins, XR
- – Simulation vs prediction vs intelligence
- – Risks of AI-driven virtual-physical systems
- – Trust and realism challenges
5.2 Decentralized Technologies (Blockchain & Web3)
- – Core differences between AI and blockchain
- – Why AI ≠ trust and blockchain ≠ intelligence
- – Valid integration use cases
- – Common misconceptions and marketing myths
5.3 Cloud, IoT, Robots, Drones & Physical Systems
- – AI as orchestration and control layer
- – Autonomy vs automation in physical systems
- – Safety and escalation risks
- – Limits of AI in real-world environments
5.4 FinTech, RegTech & Platform Systems
– AI in regulated decision environments
– Explainability and auditability challenges
– AI risk in compliance and oversight
– Why “black-box” AI is a governance issue

Module 6 – AI Risk, Misuse & Failure Modes

Purpose: Teach how AI fails before it fails.

Subtopics:

– Hallucinations and confidence errors
– Automation bias and human over-trust
– Misuse vs abuse vs unintended harm
– Scaling risk with AI deployment
– Systemic failure patterns
– Early warning signs of AI breakdown

Module 7 – Responsible AI & Governance Awareness

Purpose: Reinforce human accountability.

Subtopics:

– Why responsibility cannot be delegated to AI
– Accountability, explainability, and oversight
– Governance as enablement, not restriction
– Leadership responsibilities in AI systems
– Why policies alone are insufficient
– Human decision ownership in AI environments

Module 8 – AI Readiness Review & Pathway Alignment

Purpose: Prepare learners for the correct next step.

Subtopics:

– What “AI readiness” actually means
– Self-assessment of readiness level
– Matching readiness to MetaServ pathways:
- – AILC-DP™
- – AILC-CD™
- – AILC-AA™
- – AILC-DS™
– Risks of early specialization
– Literacy as a long-term capability

Module 9 – Final Assessment & Certification Evaluation

Purpose: Validate understanding, not execution.

Subtopics:

– Scenario-based AI decision cases
– Conceptual MCQs focused on judgment
– Risk identification and escalation questions
– Governance and responsibility evaluation
– Certification readiness confirmation

– AILC™ does not teach how to use AI
– AILC™ teaches how not to misuse, misjudge, or over-trust AI

– AI Readiness Self-Assessment Checklist
– AI Decision Responsibility Map
– AI Misconceptions & Red-Flags Guide
– AI Ecosystem Awareness Framework
– AI Risk Awareness Reference Sheet

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:

Read the details here

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.

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First Name

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Upload Profile Image

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Verse-related Technologies

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Ideas & Recommendations

Suggest for us good Profiles like yours to join us:

Other Inputs & Details

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LEVEL

Executive

Duration

5 Days

Modules

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.

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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.

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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.

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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.