How does AI strategy change with scale?

How does AI strategy change with scale? My thesis research revealed that for a global agency, it's a tool for cultural change. For an individual film director, it's a filter to protect their craft.

In today's turbulent environment, many are realizing that rigid tech roadmaps are fragile. Instead, my research found that a more resilient (what I call "vision-led") approach is emerging, but it uncovered that this concept has two very different meanings.

For a large corporation, a "vision-led" strategy is a top-down imperative. It's about inspiring thousands of employees to embrace change, creating a shared culture and helping them find personal value in adapting. The vision is the engine for organizational transformation.

But for an individual creator, like the established film director I interviewed, the logic is completely reversed.

For them, a "vision-led" strategy is a bottom-up filter. It's not about embracing all of AI, but about using their own unwavering artistic vision to decide which parts of the technology to adopt, and which to actively reject. The vision becomes a defensive wall to protect their craft and values.

This duality is at the heart of my "Value Fit" model. There is no single "AI strategy." Its meaning and application are fundamentally shaped by your context, whether you're trying to steer a ship or sail your own small boat.

Which approach resonates more with you in your work? Are you building a vision to guide a team through the chaos, or using your personal vision to filter it out?

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