Section

A point of view

Length

~ 12 minutes

Updated

May 2026

AI in
Marketing

.
01 Six pillars

Where AI changes marketing — and where it doesn’t

Where AI

changes marketing.

01

Research.

From customer interview transcripts to category audits, the research pile is now a queryable asset, not a deck nobody opens.

02

Search.

When the answer comes before the click, content needs to be quotable. Schema, source authority, and editorial discipline matter more than ever.

03

Creative.

Generative tools are not a designer replacement. They are a velocity multiplier for the brands with the clearest visual language.

04

Decisioning.

The platforms are already AI. The advantage now lives upstream: clean signal, clear incrementality, and a structure that lets the model learn.

05

Measurement.

MMM and causal inference are no longer enterprise-only. The smallest D2C team can now know what actually drove the lift.

06

Workflow.

Briefs, QA, asset routing, reporting — the meta-work around campaigns is the next thing to compress.

“The platforms are already AI. The advantage now lives upstream — in the signal, the structure, and the discipline of the team feeding them.”

— from Schema is the new resume, May 2026

02 Five truths

The patterns that keep showing up

The honest

read.

01 — Truth

The platforms are AI now.

Bidding, audience expansion, creative selection — already a black box. The job is shifting from operating the platforms to feeding them the right signal.

02 — Truth

Search is splitting in two.

Classic SERP for navigational queries. Generated answers for everything else. Both need a content strategy. Most brands have neither.

03 — Truth

Content velocity is a strategic lever.

For the first time, the bottleneck on category coverage is editorial discipline, not headcount. Used carelessly, it becomes noise.

04 — Truth

Attribution is finally honest.

Modern incrementality + MMM frameworks can be stood up in weeks, not quarters. Hiding behind last-click is now a choice.

05 — Truth

Brand still wins long term.

Distinctiveness, memory structures, sonic and visual codes — none of this is automatable. Performance compounds on brand, or it doesn’t compound at all.

03 In practice

Measured, not theoretical

38 %

Average production cost reduction on always-on creative.

4.2 ×

Faster brief-to-asset turnaround on tested workflows.

180 %

Organic traffic growth using AI-assisted content systems.

0

Client data trained into a third-party model without consent.

04 How the framework runs

Three weeks · three artefacts

Three weeks.

Three artefacts.

Week 01

Map what you have.

Audit current stack, signal quality, data hygiene, and the people. Identify the three workflows worth re-architecting first.

Week 02

Design the operating system.

Tool selection, workflow maps, role redesigns, KPI structure. A working architecture, not a recommendation slide.

Week 03

Ship one workflow.

A single end-to-end pilot the team can run on Monday. Measurable, governance-clean, reversible.

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