Data Makes the World Go 'Round

Chapter 2The Leadership Challenge

In this chapter, we will examine the following:

• The AI trap: vision vs. execution
• Examples of failed AI implementations
• The importance of an AI strategy that aligns with business goals
• How to craft an AI strategy

A compelling vision for AI can inspire teams, secure funding, and set a clear direction. But vision alone doesn’t deliver outcomes; execution does. Too often, executives announce bold visions for AI only to watch them slow in the face of data silos, cultural resistance, or unclear priorities. This chapter examines why execution is harder than vision, explores high-profile failures and draws out the strategic principles that enable leaders to translate aspiration into measurable results.

The AI Trap: Vision vs. Execution

“We see artificial intelligence as a key enabler of innovation and efficiency across our organization. By embracing AI, we aim to enhance customer experiences, streamline operations, and stay competitive in a rapidly evolving marketplace.” Does this sound familiar? Have you heard a statement something like this or perhaps said it yourself? These are aspirational vision statements that may align with your organization’s strategic goals, even if they don’t discuss technical details. Vision involves setting a strategic direction and imagining what is possible. I’ve seen over the years that executive vision and support are critical for AI success.

In a recent 2025 TDWI survey, almost half of the respondents reported feeling ...