The missing layer: Why enterprise AI fails without a compliant data foundation

The following is an excerpt from ‘The new enterprise growth engine: Unlock your data’s true ROI with unified consent and preference management'. Download the full guide here.

Executive summary

The CIO mandate has fundamentally changed. Once focused on infrastructure modernization and cost control, today’s CIO is accountable for enabling enterprise growth—powering AI, personalization, and data-driven products at scale while maintaining control and trust.

Consumer data is at the center of this shift. For many enterprises, the ability—or more often, the inability—to confidently activate consumer data across the organization has become the defining constraint on AI and growth. Disparate data systems, fragmented consent management, and manual governance processes create data foundations that appear modern, but break down under the demands of AI.

Scaling AI and personalization requires consumer data that is clean and fully permissioned across every system, region, and brand. Legacy tools were never designed for this reality. They capture consent at the point of collection, but fail to operationalize it across the enterprise—leaving CIOs with data that is technically available, but strategically unusable.

This gap is one of the most material, and least visible, barriers facing modern CIOs.

This playbook is for CIOs tasked with closing that gap. It examines where consumer data foundations break, why legacy approaches fall short, and what it takes to build a permissioned, AI-ready data foundation that scales with the enterprise. By the end, CIOs will be able to assess whether their consumer data can truly support AI and growth, as well as understand the steps required to move forward with confidence.

The new CIO mandate: Activating consumer data for AI and growth

With AI now embedded in every major growth initiative, CIOs have become the de facto owners of whether consumer data can actually be used at scale. The question is no longer whether data exists, but whether it is reliable, permissioned, and usable across the enterprise.

Consumer data underpins every AI model, personalization engine, and digital product. But the standard for that data has fundamentally changed. It must be accurate, purpose-specific, and provably compliant across systems, regions, and brands. Availability alone no longer creates value—and in many cases, it introduces risk.

This puts CIOs at the center of competing demands:

• Business leaders expect faster AI-driven innovation and measurable returns
• Privacy, legal, and regulatory teams require stricter, demonstrable controls
• Engineering teams are stretched thin maintaining custom data logic and workarounds

Historically, these concerns lived in silos. Marketing optimized activation. Privacy set policy. Data teams managed pipelines. But no function owned the end-to-end execution of consumer permissions i.e. how user choices are translated into enforceable rules across the enterprise. That accountability has now converged on the CIO.

Activating consumer data so it can power AI and growth without introducing compliance or reputational risk has become a foundational infrastructure problem. And CIOs are now expected to ensure that every consumer interaction, insight, and AI-driven decision is backed by data that’s not just accessible, but allowed.

This is where the mandate collides with reality: most enterprise consent and preference systems were designed for surface-level compliance, not real-time enforcement at AI scale. The result is a growing gap between an enterprise's data-driven ambitions and what can be safely executed in reality.