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Бизнес и менеджмент/Менеджмент/Управление изменениями

Change Management for Generative AI

Lead successful generative AI adoption with practical change management strategies.

Все уровни • 19 Лекции • Пожизненный доступ
Dr. Amar Massoud

Проверенный мастер-инструктор

Change Management for Generative AI
ТРЕЙЛЕР
Meet your instructor: Dr. Amar Massoud

19 ms

5.0 / 5.0
Глобальный рейтинг
1
Активные студенты
Американский английский
Субтитры на 99 языках
1 ч 47 мин
Общий контент

Чему вы научитесь

Assess an organization’s readiness for generative AI adoption.
Identify cultural, operational, and workforce barriers to AI integration.
Define a clear vision aligned with organizational goals.
Develop a structured change management plan for AI initiatives.

Содержание курса

10 разделов • 19 лекций • 01:47:45 общая длина

Introduction

05:57

Our Use Case: InnovAI Solutions Inc.

04:38

Step 1: Assessing Organizational Readiness for Generative AI – Part 1

07:29

Step 1: Assessing Organizational Readiness for Generative AI – Part 2

05:03

Step 2: Setting a Clear Vision for AI Integration – Part 1

06:35

Step 2: Setting a Clear Vision for AI Integration – Part 2

04:41
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Требования

No previous generative AI or change management experience is required.

A basic understanding of workplace operations is helpful.

An interest in organizational transformation and AI adoption.

A willingness to apply the course framework to practical business scenarios.

Целевая аудитория

Business leaders planning to introduce generative AI into their organizations.

Managers responsible for organizational change or digital transformation.

HR and learning professionals preparing employees for AI-driven roles.

Project and programme managers leading AI implementation initiatives.

Об этом курсе

Generative AI can transform how organizations operate, make decisions, serve customers, and create value. However, successful adoption requires more than introducing new technology. Organizations must prepare their people, processes, leadership, and culture for significant change.

This course provides a practical, step-by-step framework for managing organizational change during generative AI adoption. Using InnovAI Solutions Inc. as a continuing business case, learners will explore how organizations can assess readiness, define a clear AI vision, create a structured change management plan, and communicate effectively with employees and stakeholders.

The course begins by examining organizational readiness for generative AI. Learners will identify existing capabilities, cultural barriers, skills gaps, stakeholder concerns, and operational risks that may influence AI adoption. They will then learn how to develop a clear vision for AI integration that supports organizational objectives and provides employees with a shared understanding of the transformation.

Learners will explore how to create a practical change management plan covering leadership support, stakeholder engagement, employee participation, training, timelines, responsibilities, and risk management. The course also explains how communication strategies can reduce uncertainty, address resistance, and build trust throughout the AI implementation process.

Special attention is given to building a culture of adaptability and continuous learning. Learners will understand how organizations can prepare employees for changing responsibilities, promote experimentation, develop AI-related skills, and encourage collaboration between technical and non-technical teams.

The course also covers methods for measuring and sustaining AI-driven change. Learners will examine performance indicators, employee feedback, adoption levels, business outcomes, and continuous improvement processes. Ethical considerations and governance are addressed to help organizations manage transparency, accountability, data protection, bias, and responsible AI use.

Finally, practical case studies demonstrate how change management principles can be applied to real organizational challenges. By the end of the course, learners will have a structured roadmap for guiding generative AI adoption while maintaining employee engagement, responsible governance, and long-term organizational resilience.

Карьерные возможности и целевые профессии

Освойте практические навыки для работы и претендуйте на востребованные международные должности

Программа для карьеры
Профессии, на которые вы можете претендовать

AI Solutions Engineer

Data Science Consultant

Machine Learning Practitioner

AI Workflow & Automation Specialist

Ориентировочная годовая зарплата
$105,000 – $165,000 / yr
Спрос на мировом рынке

Fastest Growing Worldwide (#1)

Ключевые практические навыки
Model Fine-Tuning & Evaluation
Data Pipelines & Vector Analysis
Applied Generative AI Architecture
Predictive Analytics & Deployment
* Оценки основаны на глобальных отчетах о компенсациях в технологической отрасли.
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Dr. Amar Massoud
5.0 Рейтинг
5 Студенты
Посмотреть профиль
Dr. Amar Massoud
Главный инструктор
PhD in computer science and IT manager with 36 years technical experience in various fields including IT Security, IT Governance, IT Service Management , Software Development, Project Management, Business Analysis and Software Architecture. I hold 80+ IT certifications such as : ITIL 4 Master, ITIL 3 Expert ISO 27001 Auditor, ComptIA Security+, GSEC, CEH, ECSA, CISM, CISSP, CISA PGMP, MSP PMP, PMI-ACP, Prince2 Practitioner, Praxis, Scrum Master COBIT 2019 Implementor, COBIT 5 Assessor/Implementer TOGAF certified Lean Specialist, VSM Specialist PMI RMP, ISO 31000 Risk Manager, ISO 22301 Lead Auditor PMI-PBA, CBAP Lean Six Sigma Black Belt, ISO 9001 Implementer Azure Administrator, Azure DevOps Expert, AWS Practitioner And many more....

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