Framework guide
The SCOPE AI governance framework for marketing
Most marketing teams adopted AI faster than they governed it. SCOPE is a five-part framework for answering the questions an executive is actually accountable for: where AI is used, what it may do, who owns it, which platforms are approved, and what it costs.
Suitability
Where should AI be used?
Start with the work, not the tool. Document the marketing job to be done, the audience it touches, and the data it consumes. Suitability separates tasks where AI adds leverage (drafting, summarising, variant generation, research triage) from tasks where the cost of a wrong output — regulated claims, pricing, crisis comms — outweighs the speed gained.
- —Written use case with a named business outcome
- —Data classification of every input the task requires
- —An explicit non-AI fallback if the model is unavailable or wrong
Controls
What may AI do?
Controls translate policy into permitted and restricted actions per use case, tied to an autonomy level from A1 (advises a human) to A4 (acts autonomously). As autonomy rises, oversight rises with it: review gates, logging, human sign-off before publication, and rollback paths.
- —Permitted and restricted action lists per use case
- —Autonomy level A1–A4 with matching review requirements
- —Disclosure rules for AI-assisted customer-facing output
Ownership
Who is accountable?
Every AI use case and every tool carries a business owner, a technical owner, and a data owner. Accountability is what makes governance enforceable — orphan AI is the single most common failure mode in marketing teams that adopted tools faster than they assigned responsibility.
- —Named business, technical, and data owners on every record
- —Approval routing across marketing ops, infosec, legal, and the CMO
- —A review cadence with dates, not intentions
Platforms
Which AI tools should be approved?
A tool registry replaces the shadow stack. Each platform is scored on a consistent set of factors — capability fit, data handling, security posture, integration, vendor viability, cost, and support — producing an approve, conditional, or reject decision rather than a preference.
- —One registry entry per AI system in use, including free tiers
- —A standardised scorecard applied to every candidate
- —Redundancy analysis so three tools do not fund one capability
Economics
What does AI cost, and what does it return?
AI FinOps gives marketing a per-tool, per-outcome view of spend instead of a single consolidated invoice. Duplication, unused seats, and rising usage-based costs become visible early enough to act on at renewal.
- —Spend tracked by tool and category, not just by vendor invoice
- —Cost per outcome for the workflows AI actually supports
- —Duplicate-capability report reviewed each quarter
Applying SCOPE in five steps
- 1.Inventory every AI tool marketing touches, including personal and free-tier accounts.
- 2.Register the top use cases and classify each by risk tier and autonomy level.
- 3.Assign business, technical, and data owners to every entry — no exceptions.
- 4.Score the tools, retire duplicates, and route the remainder through approval.
- 5.Put spend and outcomes on one page, then review on a fixed cadence.
Run SCOPE as a system, not a spreadsheet
MarGov AI turns each part of the framework into a working surface: a use-case registry, a tool registry with scorecards, autonomy-driven approval routing, and AI FinOps.