Generative AI for Managers and Leaders

Course Category : Risk Management

A leadership-focused programme enabling managers to understand Generative AI, assess its opportunities and risks, and lead its strategic and responsible adoption across organisational functions.
Duration: 5 Days
Level: Intermediate to Advanced

Introduction

Generative AI is reshaping managerial work by expanding the capacity to analyse information, generate content, support decisions, and redesign workflows. For managers and leaders, the central challenge is no longer simply understanding the technology, but determining where it creates measurable value, how its risks should be governed, and what controls are required for responsible organisational adoption.
This course provides an integrated management framework covering Generative AI and large language models, enterprise use cases, effective interaction techniques, value assessment, governance, risk management, and the development of a structured roadmap for organisation-wide AI adoption..

Targeted Audience

Executives and decision-makers
General managers and functional directors
Middle management leaders
Digital transformation and innovation leaders
Strategy and business development managers
Operations and organisational excellence managers
HR, finance, and corporate services managers
Professionals responsible for AI and organisational transformation initiatives

Targeted Skills

Managerial and strategic understanding of Generative AI
Enterprise use-case and value assessment
Effective prompting for generative systems
Evaluation of AI-generated outputs and reliability
AI governance, risk, and accountability management
AI initiative prioritisation
Leadership of AI adoption and organisational change
Development of AI-enabled transformation roadmaps

Expected Outcomes

Explain the fundamentals of Generative AI and large language models from a managerial perspective.
Identify high-value use cases across organisational functions and processes.
Structure effective prompts for management-oriented AI tasks.
Evaluate the quality, limitations, and reliability of generative outputs.
Assess privacy, security, bias, intellectual property, and accountability considerations.
Prioritise AI initiatives according to value, risk, and organisational readiness.
Lead organisational change associated with AI adoption.
Develop an initial roadmap for responsible Generative AI adoption.

Training Topics Index

Generative AI fundamentals and its position within the broader AI landscape
Large language models and the generation of information and content
Capabilities, limitations, and inaccurate or fabricated outputs
Transition from conventional automation to AI-augmented work
Leadership responsibilities in directing enterprise AI value

Generative AI applications across management, strategy, and operations
Research, summarisation, reporting, and management communications
Use cases across HR, finance, marketing, and customer service
Assessing use cases according to value, feasibility, and risk
Prioritising opportunities and developing an AI initiative portfolio

Prompt engineering principles for managers and leaders
Defining context, objectives, constraints, and output formats
Improving prompts through iteration, decomposition, and contextualisation
Evaluating accuracy, relevance, consistency, and information reliability
Human oversight and appropriate boundaries for AI-supported decisions

Enterprise governance frameworks for Generative AI
Privacy, confidentiality, data security, and generative systems
Bias, transparency, accountability, and human oversight
Intellectual property considerations for AI-generated content
Acceptable-use policies, risk management, and compliance

Assessing organisational and leadership readiness for AI adoption
Defining roles, responsibilities, operating models, and governance
Managing change and developing AI-related organisational capabilities
Measuring value, performance indicators, and expected return
Building a phased roadmap for adoption, scaling, and continuous improvement

Course Features

Updated and Interactive Content
Hypothetical Examples and Case Studies
Pre- and Post-assessments to Measure Impact
Verified Certificate with a QR Verification Code

Generative AI for Managers and Leaders