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The Brando IBOM

Intelligent Brand Operating Model

The Brando IBOM (Intelligent Brand Operating Model) defines how Brando-based brand intelligence is introduced, governed, executed, and sustained as a live operational capability across AI systems, workflows, and enterprise platforms.

Brando Schema: AI-native vocabulary for brands

Where Brando Schema defines what brand intelligence is in machine-readable form,
the Brando IBOM defines how that intelligence is assessed, codified, deployed, operated, and assured over time.

Together, they enable Brand-as-Code to function as governed infrastructure, not static documentation.

Why the Brando IBOM exists

Most organisations already have:

  • brand strategy and guidelines,
  • governance, legal, and risk functions,
  • marketing, CX, data, and AI delivery teams,
  • and an increasing number of AI-powered systems operating at scale.

What they lack is a shared operating model that connects:

brand intent → structured brand intelligence → AI execution → ongoing governance and assurance

As a result, brand behaviour in AI systems is often:

  • fragmented across tools and teams,
  • encoded informally in prompts or playbooks,
  • difficult to audit or enforce,
  • and fragile under change.

The Brando IBOM exists to close this gap.

It provides a clear, repeatable lifecycle for running brand as a machine-actionable, governed operational asset — in the same way organisations already operate security, data, and financial controls.

Brando and IBOM: separation of concerns

The Brando ecosystem is deliberately split into definition and operation.

Brando Schema

  • The definition layer
  • A linked-data vocabulary and Brand Definition Vocabulary (BDV)
  • Encodes brand identity, expression, personas, context, and governance as data
  • Forms the canonical Brand Knowledge Graph

The Brando IBOM

  • The operating layer
  • Defines lifecycle stages, controls, and responsibilities
  • Governs how Brando assets are created, deployed, executed, monitored, and evolved
  • Ensures brand intelligence can safely operate across AI systems, markets, and time

Brando provides the building blocks.
The Brando IBOM provides the operating discipline.

Neither is sufficient on its own.

IBOM is not a generic framework

The Brando IBOM is not:

  • a generic enterprise operating model,
  • a data science lifecycle,
  • or a rebranded consulting methodology.

While informed by frameworks such as CRISP-DM, TOGAF, and ITIL, IBOM is purpose-built for:

  • AI-native brand governance
  • Machine-actionable knowledge and policy graphs
  • Probabilistic systems (LLMs, agents, multimodal AI)
  • Continuous, cross-channel brand execution

IBOM assumes that:

  • brand rules must be interpretable by machines,
  • governance must operate at inference time, not just design time,
  • and brand change is continuous, not episodic.

The Brando IBOM lifecycle

At its core, the Brando IBOM defines a single, consistent lifecycle:

Assessment → Definition → Codification → Deployment → Operation → Assurance

Each stage answers a distinct operational question:

  • Assessment — What brand intent, risk, and exposure must be understood?
  • Definition — How is brand intent formally defined in Brando terms?
  • Codification — How is that intent encoded as machine-actionable intelligence?
  • Deployment — Where and how is it introduced into AI systems and workflows?
  • Operation — How does it behave at runtime across channels and contexts?
  • Assurance — How is compliance, quality, and drift monitored and corrected?

This lifecycle applies whether you are:

  • onboarding a new brand,
  • launching a new AI assistant,
  • entering a new regulatory market,
  • or evolving brand policy over time.

How the IBOM is implemented in practice

The Brando IBOM is not theoretical.

It is executed in production through the Brando IBOM Implementation Service, which delivers the official reference implementation of:

  • the Brando Schema and BDV,
  • the Brand Knowledge Graph,
  • Machine-Actionable Policy Graphs,
  • AI Brand Impact Assessments,
  • and a live Brand Operating System (Brand OS).

The Implementation Service maps each IBOM stage to concrete artefacts, controls, and runtime integrations — ensuring that the operating model is real, auditable, and enforceable.

→ Brando IBOM Implementation Service

IBOM stages in context

1. Assessment

Brand readiness, risk, and exposure

Establishes the current state of brand maturity and AI exposure.

Typical outputs include:

  • brand ambiguity and interpretation risk,
  • AI misuse and regulatory exposure,
  • priority AI use cases and value hypotheses,
  • initial AI Brand Impact Assessments.

2. Definition

Formal brand intent and governance

Defines brand meaning in explicit, unambiguous terms.

Outputs include:

  • brand intent, values, and narrative,
  • verbal, visual, and behavioural rules,
  • constraints, exceptions, and approvals,
  • governance logic suitable for codification.

3. Codification

Machine-actionable brand intelligence

Transforms definition into structured data using Brando Schema.

Outputs include:

  • Brand Definition Vocabulary (BDV),
  • Brand Knowledge Graph (JSON-LD / YAML),
  • context-aware personas and tokens,
  • policy derivation logic.

This is where brand becomes executable.

4. Deployment

Controlled activation

Introduces codified brand intelligence into live systems.

Outputs include:

  • versioned Brand OS deployments,
  • API and runtime integrations,
  • validation and approval workflows,
  • alignment with enterprise architecture and security.

5. Operation

Runtime governance

Brand intelligence operates continuously as a system of record.

This includes:

  • enforcement of policy at inference time,
  • integration across channels and tools,
  • controlled overrides and campaign logic,
  • monitoring of usage and behaviour.

Integration is an operational capability, not a separate phase.

6. Assurance

Auditability, trust, and evolution

Ensures long-term defensibility and performance.

Outputs include:

  • audit trails and traceability,
  • impact assessment updates,
  • drift detection and remediation,
  • evidence for internal and external assurance.

Who the Brando IBOM is for

The Brando IBOM is designed to align multiple disciplines without collapsing them into one owner:

  • Brand and marketing leaders — retain control and consistency
  • Legal, risk, and compliance teams — enforce policy and audit behaviour
  • AI, data, and platform teams — operationalise brand rules reliably
  • Agencies and integrators — deliver repeatable, governed implementations

It provides a shared language and operating discipline across strategy, governance, and execution.

Relationship to other Brando components

  • Brando Schema → definition vocabulary and data model
  • Brando IBOM → operating model and lifecycle
  • Brand Operating System → runtime execution layer
  • Implementation Service → reference execution of all three

Each layer has a distinct role — and together they form a complete, enterprise-grade Brand-as-Code system.

Next steps