Building an AI Implementation Roadmap: Key Principles for Executing a Successful AI Strategy

Building an effective AI roadmap is essential for organizations looking to harness AI’s transformative potential. In this course, leading strategy advisor and futurist Ross Dawson guides business leaders through the critical success factors in developing and executing an AI strategy that will drive success. Learn how to effectively implement the four phases of an effective AI roadmap: framing the strategic and governance issues; planning use cases and required technologies; implementing pilots and capability development; and scaling to fully integrate AI for organizational transformation. Ross explains how to align AI initiatives with your broader organizational strategy, manage risks, and ensure successful implementation. Real-world examples and actionable insights will equip you with the tools to design an AI roadmap that drives sustainable growth and innovation.

Learning objectives
Analyze the key principles for AI roadmap development and implementation and explain their significance in creating a successful AI strategy.
Identify and describe the elements of a clear, actionable AI roadmap, and how each element contributes to accelerated learning and rapid iteration.
Develop an AI strategy that aligns with your business vision, addressing potential risks and establishing AI governance frameworks.
Plan and design pilots for AI implementation, including capability development initiatives and iterative improvements to the roadmap.
Compare and contrast different approaches to scaling AI initiatives, including the expansion of pilots to full-scale deployment and the integration of AI into business operations and workflows.