Research

A brand is an identity commitment to its audiences: a value proposition enacted through consistent communication, built over time into a relationship in minds and markets. For centuries, this structure has been articulated in formats designed for human readers: chronicles, heraldry, brand books, style guides, each presuming an interpreter with institutional context, professional judgment, and tacit communicative competence. Since late 2022, language models increasingly produce brand communication under brand names at scale. The articulation formats remain. The interpreter has changed.

Without precise specification, language model outputs migrate toward the statistical centroid of the training distribution, a flattening of brand distinctiveness this paper terms Specification Drift. The cause is an Interpretive Gap between brand identity formats designed for human interpretation and the typed, validatable semantic structures that reliable, specification-conformant generation requires at inference time.

This paper argues that closing the Interpretive Gap requires a categorical shift in how brand identity is conceived: not as an interpretive document to be read by human practitioners, but as a formal specification to be processed by machines at inference time. This reconceptualization, from document to runtime artifact, is the paper's primary theoretical contribution; BrandKernel is its instantiation.

This paper proposes BrandKernel, a JSON Schema that formalizes brand identity as a machine-readable specification processable by language models at inference time, without a human interpreter. Drawing on Burmann et al.’s (2021) identity-based brand management model, the schema maps six brand identity components onto a typed, hierarchically ordered structure using the Specification Primitive, a cognitively grounded representation unit anchored in three constitutive semantic fields. A voice layer extends the schema, formalizing the communicative dimension of Markenpersönlichkeit that human interpreters previously supplied implicitly. Beyond generation, the typed artifact serves evaluation systems, retrieval layers, and fine-tuning pipelines from a single authoritative, versionable source, repositioning brand identity as auditable infrastructure for language-model deployment.

Following a Design Science Research orientation, the paper introduces Specification Fidelity, a proposed evaluation framework that defines language-model adherence to structured brand parameters along three assessment dimensions: Definitional Alignment, Anti-definitional Compliance, and Exemplar Proximity. The contribution is architectural; empirical validation is deferred to subsequent work. The formal schema specification is provided as a companion file: BrandKernel_Schema_v1.0.json.