Guide · 5 min read
How to Make Your Marketing Team More Efficient With AI
By Fredrika Frenkiel, Head of Studio & AI Creative Operations at Lunar, founder of Code of Alfred. About my work
Short answer
The fastest way to make a marketing team more efficient with AI is to target the specific bottleneck costing the most time or causing the most rework, not to introduce AI broadly across every task at once. Efficiency gains come from redesigning a handful of high-friction workflows properly, not from sprinkling AI tools across an unchanged process.
1. Efficiency comes from the operating model, not from more AI tools
Teams that get durable efficiency from AI have one thing in common: they changed how work moves, not just what software they use. That shared way of working is the AI operating model, and it is the first thing I build as a marketing operations AI specialist. Tools give one person a shortcut. An operating model gives the whole team the same shortcut every time the workflow runs, which is where hours, revision rounds and cost actually disappear.
2. Find where time is actually being lost, not where it feels slow
Ask the team directly: what gets redone most often, what takes the longest relative to its importance, and what causes the most last-minute scrambling? The answer is rarely “everything”, it's usually two or three specific workflows: brief intake, asset adaptation across markets, or repetitive QA and formatting checks.
3. Redesign the workflow, then decide where AI fits
For each bottleneck, write out the current steps plainly. Then identify which steps are mechanical and repeatable (a strong candidate for AI) versus which require judgment, taste, or a relationship (which should stay human). A useful rule: AI is a strong fit for generation, structuring, and scaling; it's a poor fit for prioritisation, final creative judgment, and anything where being wrong has real cost.
4. Build reusable systems, not one-off prompts
The biggest difference between teams that get lasting efficiency gains and teams that get a brief novelty boost is whether the AI work is treated as infrastructure. A one-off prompt saves one person time once. A structured, reusable prompt system, chained across a workflow, with defined inputs and outputs, saves the whole team time every time the workflow runs.
5. Automate the handoffs, not just the content generation
A large share of marketing inefficiency isn't the creative work itself, it's what happens between steps: briefs sitting unread, files being manually moved between tools, status updates chased over Slack. Automating triggers between systems (a brief being submitted automatically creating a project and notifying the right people, for example) often saves more time than automating the creative output itself.
6. Measure the efficiency gain honestly
Track a concrete before/after on the specific workflow you changed, time from brief to delivery, number of revision rounds, or hours spent on manual formatting, rather than a vague sense that things feel faster. This also protects the initiative: efficiency claims that can't be measured don't survive the next budget conversation.
7. Scale only what's proven
Once a workflow redesign demonstrably works, extend the same pattern to the next bottleneck rather than trying to overhaul everything simultaneously. Efficiency compounds when each fix is solid, not when many half-finished changes run in parallel.
How to do it, step by step
- 01
Find where time is actually being lost
Identify the two or three specific workflows causing the most rework or delay, not a general sense of slowness.
- 02
Redesign the workflow, then decide where AI fits
Separate mechanical, repeatable steps suited to AI from judgment-based steps that must stay human.
- 03
Build reusable systems, not one-off prompts
Treat prompt work as chained, reusable infrastructure so gains compound across the whole team.
- 04
Automate the handoffs, not just the content
Automate the triggers between steps, such as brief submission creating a project automatically, not only the creative output itself.
- 05
Measure the efficiency gain honestly
Track concrete before/after metrics on the specific workflow changed, such as time from brief to delivery.
- 06
Scale only what's proven
Extend a working pattern to the next bottleneck rather than overhauling everything at once.
This bottleneck-first approach, find the real friction, redesign the workflow, then build the technical layer, is the same method behind the systems I've built for marketing organisations. See how I approach this in practice.
Common questions
- Where do AI efficiency gains in marketing actually come from?
- From two or three high-friction workflows redesigned properly, usually brief intake, multi-market adaptation and the handoffs between stages, not from broad tool rollout across an unchanged process.
- How is AI efficiency measured in marketing operations?
- Track a concrete before and after on the workflow you changed: time from brief to delivery, number of revision rounds, cost per asset and on-time launch rate.
- Can a marketing operations AI specialist help without replacing our stack?
- Usually yes. Most gains come from redesigning the sequence and automating handoffs inside the tools you already run, then adding new technology only where a proven bottleneck remains.
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