From Disruption to Transformation Implementing AI for Business Growth #254036

Upon completion of this course, participants will be able to:

• Develop an AI Transformation Roadmap: Create a phased, actionable plan for AI implementation aligned with specific business growth objectives.

• Identify and Prioritize High-Impact Use Cases: Select AI projects based on their potential for ROI, strategic value, and feasibility.

• Build the AI Foundation: Understand and oversee the development of the necessary data architecture, technology stack, and talent model required for scalable AI.

• Lead AI Implementation Projects: Manage the unique challenges of AI projects, from data acquisition and model development to integration and change management.

• Measure and Scale AI Impact: Establish KPIs to track the performance and business impact of AI initiatives and create a plan for scaling successful pilots across the organization.

• Foster an AI-First Culture: Design strategies to overcome organizational resistance, upskill existing talent, and instill data-driven decision-making at all levels.

This course is designed for leaders and practitioners responsible for driving growth and operational excellence:

• C-Suite Executives (CEOs, COOs, CFOs, CTOs, CDOs) setting corporate strategy

• VPs and Directors of Digital Transformation, Innovation, Strategy, or Operations

• Business Unit Heads and General Managers with P&L responsibility

• Senior IT Leaders and Enterprise Architects

• Heads of Data Science and AI/ML Practice Leaders

• Product Leaders and Marketing Chiefs driving customer growth

• Management Consultants advising on technology-driven growth

• Pre-assessment
• Live group instruction
• Use of real-world examples, case studies and exercises
• Interactive participation and discussion
• Power point presentation, LCD and flip chart
• Group activities and tests
• Each participant receives a binder containing a copy of the presentation
• slides and handouts
• Post-assessment

Day 1: From Strategy to Action: Laying the Foundation for Growth

• AM: The AI-Powered Growth Mandate

  • Beyond Hype: Framing AI as a lever for revenue growth, cost optimization, and market differentiation.

  • Assessing your company’s AI maturity and readiness for transformation.

  • The Leader’s Role: Championing the vision and securing buy-in.

• PM: Building Your AI Growth Roadmap

  • Aligning AI initiatives with core business goals (e.g., entering new markets, personalizing at scale, optimizing supply chains).

  • Workshop: Drafting a high-level, 18-month AI transformation roadmap for your organization.

Day 2: Selecting and Scoping for Impact

• AM: The Use Case Prioritization Framework

  • How to identify and evaluate AI opportunities: Assessing value, data availability, and implementation complexity.

  • Focus on ROI: Building the business case and calculating the potential financial impact.

  • Hands-on Exercise: Applying a prioritization matrix to a portfolio of potential AI projects.

• PM: The Anatomy of a Successful AI Project

  • Defining project scope, objectives, and success metrics (KPIs).

  • The cross-functional project team: Roles and responsibilities.

  • Case Study: Deconstructing a successful AI implementation from ideation to impact.

Day 3: Building the Engine: Data, Technology, and Talent

• AM: The Data and Technology Stack for Growth

  • Data Strategy: Sourcing, governing, and preparing data as a strategic asset.

  • The AI technology landscape: Cloud platforms, ML tools, and MLOps for scalability and reliability.

  • Making build-vs.-buy decisions.

• PM: The Talent and Partner Ecosystem

  • Solving the skills gap: Upskilling, hiring, and leveraging external partners.

  • Designing agile workflows for AI teams (Data Scientists, ML Engineers, Domain Experts).

  • Workshop: Designing an optimal team structure for a high-priority use case.

Day 4: Execution and Integration: Turning Models into Value

• AM: Managing the AI Project Lifecycle

  • Agile for AI: Managing iterations, testing, and validation.

  • From prototype to production: Overcoming the “pilot purgatory” and integrating models into business workflows and systems (ERP, CRM).

• PM: Leading Change and Measuring Performance

  • Change management strategies for user adoption and overcoming resistance.

  • Monitoring model performance, drift, and business impact in real-time.

  • Hands-on Exercise: Defining a performance dashboard for an AI initiative.

Day 5: Scaling and Sustaining Transformation

• AM: From Project to Program: Scaling AI Across the Enterprise

  • Creating a center of excellence and governance model for AI.

  • Standardizing processes and technology to enable replication of success.

  • Managing a portfolio of AI investments.

• PM: Capstone: Your Transformation Plan

  • Final Exercise: Participants will present a comprehensive implementation plan for their chosen use case, covering:

    • Refined business case & ROI model

    • Project charter with team structure & timeline

    • Data & technology requirements

    • Change management & communication strategy

    • KPI dashboard for measurement

  • Peer feedback and expert review.

  • Course Wrap-Up: Committing to action and building a network for ongoing support.