Question 1

How is AI used in the office's marketing work?

Accepted Answer

AI is used as a craft tool inside the operator's workflow — for research synthesis, creative iteration, predictive segmentation, content production, and measurement. It does not replace the operator's judgment. Every AI move in market is first pressure-tested against governance, evaluation, and reproducibility criteria, then deployed with discipline in the field.

Question 2

Which AI tools and vendors do you work with?

Accepted Answer

The work is vendor-neutral. The office designs the operating model and use-case prioritisation, then makes a build-versus-buy recommendation grounded in the organisation's data maturity, team capability, and regulatory environment. There is no preferred vendor partner.

Question 3

What does a typical AI transformation engagement cost?

Accepted Answer

A diagnostic plus operating model design runs for eight to twelve weeks on a fixed fee. A diagnostic plus twelve-month transformation roadmap runs longer and is scoped against the use cases. Detailed fee ranges are shared after the first discovery call.

Question 4

How is AI risk and governance handled?

Accepted Answer

Risk and governance are designed in from week one — covering data lineage, model evaluation, content provenance, regulatory exposure, and the human-in-the-loop checks the operator's judgment requires. Governance is treated as an operating capability, not a compliance checkbox.

AI Marketing Transformation: generative ai and predictive analytics, deployed with operator discipline.

When the engagement fits.

Marketing leaders who have AI pilots but no operating model

Conglomerates that want AI across business units, not in silos

Boards that want an honest, defensible AI strategy

Concrete deliverables, not adjectives.

An AI marketing operating model with use-case prioritisation

A roadmap with measurable outcomes over four quarters

An internal capability and upskilling plan

A vendor and build-versus-buy recommendation

A clear operating rhythm.

Weeks one to four: discovery across use cases, vendors, and data

Weeks five to eight: use-case prioritisation and operating model design

Weeks nine to twelve: pilot kickoff with success criteria

Quarters two to four: scale, measurement, and capability build

What the organisation can expect.

An AI marketing function that ships measurable work each quarter

A defensible operating model for AI in the marketing org

Internal capability that outlasts any single tool or vendor

The work behind the model.

AI-powered marketing transformation

Twelve brands, one operating discipline

Answers to common questions.

Field notes on the work.

AI in marketing is a craft tool

What AI will not replace

Discuss a ai marketing transformation.