About

Amanda Bailey is an enterprise AI, analytics, and data executive with more than 20 years of experience helping organizations build data, analytics, data science, and AI into the operating model. Her background spans large-scale digital, D2C, and subscription environments, with work centered on strategy, transformation, operating models, and leadership alignment.

She works with organizations that need more than technical enthusiasm. They need a clearer path for how AI should create value in the operating model, how governance should work, and how leaders should organize for adoption, accountability, and execution.

About

Amanda Bailey

Executive advisory for organizations building durable Data, Analytics & AI capabilities.

Bailey Applied Intelligence helps leaders turn AI, data, analytics, and governance into real operating capability, not isolated experimentation. The work focuses on the strategy, structure, and leadership decisions required to scale AI responsibly inside the business.

Built around a practical view of enterprise AI: durable progress comes from operating discipline, clear ownership, strong governance, and leadership alignment.

That often means helping organizations:

• Clarify where AI should create value in the operating model.

• Define ownership, decision rights, and accountability.

• Build governance that supports adoption rather than slowing it down.

• Translate strategy into an operating model the business can sustain.

How Amanda works
The work is structured for leaders who need clarity, judgment, and practical movement.

Amanda’s approach combines:

• Executive-level strategy and decision support.

• Deep understanding of data, analytics, and AI operating models.

• Practical governance design.

• Cross-functional alignment across business, data, product, and risk stakeholders.

Who this is for
Bailey Applied Intelligence works with executive teams, data and technology leaders, and cross-functional stakeholders responsible for moving AI from experimentation into execution.

This is often the right fit when the challenge is not whether AI matters, but how to make it real inside the organization.