AI-DRIVEN DIGITAL TRANSFORMATION STRATEGY

Live-Online Training: N220,000
Classroom Training: N300,000
3 - 4 participants: 5% discount
5 or more participants: 10% discount

(Available also for Customised Training by Duration, Venue & Fee)

Program Description

This 4-day intensive course is designed for senior professionals and executives aiming to leverage AI to drive their organization's digital transformation. It provides a strategic framework for identifying AI opportunities, managing change, aligning AI initiatives with business goals, and implementing transformation projects effectively. Through case studies and practical exercises, participants will leave equipped with an actionable roadmap for leading AI-driven transformation.

Course Objectives:

●     Develop a strategic approach to integrating AI into organizational transformation initiatives.

●     Identify and prioritize AI opportunities across various business functions.

●     Learn change management techniques essential for successful AI adoption.

●     Review real-world case studies of AI-driven transformations to extract best practices.

●     Build a roadmap for implementing AI strategies aligned with business objectives.

Course Outline

Day 1: Understanding AI and its Role in Digital Transformation

Morning Session: Introduction to AI-Driven Digital Transformation

●     Course Overview and Objectives

○     Briefing on the course agenda, objectives, and expected outcomes.

○     Introduction to the concept of digital transformation and the pivotal role of AI.

●     AI Fundamentals for Business Leaders

○     A non-technical overview of AI, machine learning, and deep learning.

○     Review of key AI concepts relevant to strategic transformation (predictive analytics, NLP, computer vision).

○     Group discussion: AI trends and their potential impact on business strategy.

Afternoon Session: Identifying Strategic AI Opportunities

●     Identifying AI Use Cases Across Business Functions

○     Analyzing AI applications in marketing, sales, HR, finance, supply chain, and customer service.

○     Frameworks for evaluating the value and feasibility of AI opportunities.

○     Hands-on exercise: Identifying AI opportunities in participants' organizations.

●     Case Study: AI-Driven Transformation in Industry

○     Analyzing a successful case of AI implementation within an industry (e.g., retail, healthcare).

○     Group discussion on factors contributing to success and lessons learned.

Day 2: Building an AI Strategy Aligned with Business Goals

Morning Session: Crafting a Vision and Strategy for AI Integration

●     Developing a Vision for AI-Driven Transformation

○     Setting objectives: What does successful AI integration look like?

○     Aligning AI projects with broader business goals and objectives.

○     Workshop: Drafting an AI vision statement for participants' organizations.

●     Building a Roadmap for AI Strategy

○     Setting priorities and timelines for AI initiatives.

○     Building a project roadmap: milestones, resource allocation, and KPIs.

○     Exercise: Creating a high-level roadmap for one identified AI opportunity.

Afternoon Session: Assessing and Managing AI Investment and Resources

●     Budgeting for AI Projects

○     Estimating costs and evaluating ROI for AI initiatives.

○     Leveraging in-house resources versus outsourcing AI capabilities.

●     Partnering for AI Success

○     Identifying AI technology providers, consultants, and vendors.

○     Case study: Partnerships that accelerated AI-driven transformation.

Day 3: Change Management for AI Implementation

Morning Session: Preparing for Change in AI Adoption

●     Organizational Change Management for AI

○     Understanding the cultural shift required for successful AI adoption.

○     Change management frameworks for AI (ADKAR, Kotter’s Change Model).

○     Workshop: Identifying potential challenges and resistance points in participants' organizations.

●     AI Upskilling and Workforce Transformation

○     Identifying skills gaps and planning training initiatives.

○     Integrating AI roles and responsibilities within existing teams.

○     Case study: Workforce transformation and AI upskilling in a global company.

Afternoon Session: Ethics, Compliance, and Data Governance in AI

●     Ethics and Responsible AI Use

○     Addressing bias, fairness, and transparency in AI applications.

○     Creating ethical AI guidelines aligned with company values.

●     Data Privacy, Security, and Governance

○     Ensuring data governance for AI implementation.

○     Case study: Managing data compliance in AI projects (GDPR, CCPA).

Day 4: Implementation and Sustaining AI-Driven Transformation

Morning Session: Implementing and Scaling AI Projects

●     From Pilot to Scale: Implementing AI Initiatives

○     Managing AI project rollouts: pilot programs, testing, and scaling.

○     Continuous improvement through feedback loops and performance monitoring.

○     Group exercise: Developing an implementation plan for an AI project.

●     Monitoring, Measuring, and Adapting AI Strategies

○     Identifying and tracking KPIs specific to AI projects.

○     Establishing a review process to adapt and refine AI strategies.

Afternoon Session: Sustaining the AI-Driven Transformation

●     Building an AI-First Culture

○     Embedding AI thinking into organizational culture.

○     Creating a sustainable innovation process for ongoing AI development.

●     Wrap-Up and Action Plan Development

○     Participants finalize a personalized action plan for implementing AI strategy.

○     Final Q&A session, feedback, and course reflections.