A hiring-process exercise exploring how an enterprise could move from isolated AI generation to a governed content-adaptation engine across brands, markets, channels, and compliance requirements.
Role
Collaborators
Scope
The exercise began with a hypothetical enterprise scenario: AI-assisted hero-asset creation had proven faster, but localization, channel adaptation, compliance, metadata, and DAM handoffs remained manual. The next bottleneck was no longer generation; it was governed adaptation at scale.
The brief asked for a path from a successful pilot to a global operating model spanning many brands and markets without multiplying risk, fragmentation, or manual effort.
The proposed Content Adaptation Engine sits between an approved hero asset and downstream asset packages. It combines market localization rules, brand standards, legal requirements, channel specifications, metadata, and package definitions in one rules-based adaptation layer.
A three-wave roadmap moves from defining rules and validating the operating model, to building integration and coverage, to enterprise deployment and continuous improvement.
The governance model assigns ownership across regional marketing, brand, creative operations, legal, engineering, and business stakeholders so automation remains accountable as it scales.
This was a hiring exercise, not an implemented Adobe engagement. The scenario metrics and projected business impact were inputs and hypotheses, not Grove + River results.
What the work demonstrates is the ability to connect an AI use case to operating-model change, governance, technical handoffs, adoption, and measurable business value rather than treating the tool itself as the transformation.