November 3, 20267 min read

How I’d Build a 2027 Marketing Plan When Half the Work Is Done by AI

Six steps and five frameworks — the AAO split, the Seat Test, the Rupee Audit, a 70/20/10 budget and four quarterly beats — plus a one-page plan to copy.

TL;DR

Budgets are flat at 7.8% of revenue. Every AI rupee has to come from somewhere.
Plan the work before the headcount: sort tasks with the AAO split, then run every seat through the Seat Test.
An agent’s real cost is its licence plus the human review time. Most plans forget the second part.
Prune with the Rupee Audit, pour the savings into proof and people, and run the year on a quarterly rhythm.
Copy the one-page template at the end.

Picture the November planning meeting. The CFO leans back and asks one question:

“If AI does half the work now, why does marketing need the same budget?”

Most marketers answer with a slide full of tool logos. Wrong answer. The right one is a plan that shows exactly which half, who checks it, and where the freed-up money goes. (If you need the measurement side of that conversation, start with the framework your CFO will accept.)

Here’s how I’d build that plan: six steps, five frameworks, one page.

Why last year’s template breaks

The money isn’t growing. Gartner’s 2026 CMO Spend Survey puts budgets at 7.8% of revenue, flat for three years (Gartner).
The buyer sends a bot first. Forrester’s 2027 predictions say agentic buying will touch 75% of B2B purchases, and two-thirds of providers will lose deals because buyers can’t verify their claims (Forrester).
The obvious move is a trap. Forrester also predicts CMOs will cut up to 25% of roles expecting AI gains that don’t arrive, then pay to rehire or bring agencies back (Forrester).

Quick check: score your current plan

Give yourself 2 points for every yes.

Can you list which tasks AI agents already own?
Does every agent have a named human reviewer?
Do you know the pipeline each channel created last year?
Could a buyer’s AI verify your top three claims?
Does every experiment have a kill date?

8–10: you’re ahead.
4–6: you’re normal, which in 2027 means behind.
0–2: keep reading.

Step 1: Audit the work, not the org chart

List every recurring task. Sort each with the AAO split:

Bucket	Who does it	Examples
Automate	Agent owns it; human spot-checks weekly	Reporting, list hygiene, meeting notes, ad variants
Assist	AI drafts; a human decides	Blogs, emails, battlecards, briefs
Own	Human only	Positioning, pricing, customer interviews, partner deals

Stuck on a task? Use the two-minute rule. If a human can check the output in two minutes and a mistake is cheap, Automate. If checking takes longer, or mistakes reach customers, Assist. If the task is the decision, Own.

In most mid-market teams I’ve seen, about half the hours land in Automate or Assist. The Own bucket is small, but that’s where revenue gets decided.

Step 2: Headcount vs. agents

Run every seat through the Seat Test:

Is it paid for volume, judgment or relationships? Agents absorb volume.
Who reviews the agent, and for how many hours a week? “Nobody” means not ready.
What breaks if this seat is empty for 90 days? If nothing, you have your answer.

Then do the maths honestly. The Starr Conspiracy suggests modelling an agent as licence plus review time, and notes most teams underestimate review overhead by half in year one (The Starr Conspiracy).

Illustrative example:

	Content executive	Agent stack
Annual cost	Rs 6 lakh	Rs 1.5 lakh in licences
Review time	—	4 hrs/week at Rs 1,500/hr ≈ Rs 2.9 lakh
Real total	Rs 6 lakh	≈ Rs 4.4 lakh

You save about 27%, not 100%. Different board slide.

Every agent that survives the test gets an agent job description, just like a hire (MarTech):

Field	Example: weekly pipeline report agent
Job	Pull pipeline by channel every Monday, flag drops above 15%
Inputs	CRM, ad platforms, web analytics
Reviewer	Marketing ops lead, 30 minutes a week
Success metric	Report ready by 10am; zero wrong numbers in a month
Kill condition	Two wrong numbers in a quarter

One warning: Contentful and Atlantic Re:think found 25% of marketing teams have reduced or paused entry-level hiring because of AI (Contentful / Atlantic Re:think). Hire one fewer junior, not zero. No juniors today means no seniors in 2030.

Step 3: Where to cut — the Rupee Audit

Ask one question of every budget line: what pipeline did this create? (For a line-by-line version on your tools, see how to audit your AI marketing stack.)

Named pipeline: keep it.
“It influenced deals”: cut 30% and make it prove itself by Q2.
“Not sure”: cut it.

Lines that usually fail:

Volume content written for clicks. Similarweb shows 68% of Google searches now end without a click (Similarweb).
Overlapping tools. Platform agents like HubSpot Breeze and Salesforce Agentforce do what three point tools used to (MarTech). The CMO Survey shows martech already at a five-year low of 19.4% of budgets (Webtonic).
Execution-only agency retainers. Forrester expects agencies to split between orchestration and execution (Forrester). Pay for thinking; let agents do the typing.

Step 4: Where to double down

Proof machines can verify. Use the claim ladder: adjective (“best-in-class”) → number (“cuts handle time 30%”) → named customer → third-party verified. Move your top five claims up two rungs by March.
Humans in the deal. Forrester expects buyers to double their human interactions to validate AI recommendations (Forrester). Fund customer advocacy, solution-engineer time and founder-led content.
AI visibility. Track citations in ChatGPT, Gemini and Perplexity, not just rankings.
Data and ops. Gartner found 70% of CMOs say their processes can’t yet scale AI (Gartner). Companies with optimised AI programmes get 8.9% of revenue, against the 7.8% average (Marketing Dive via Yahoo Finance). Clean data earns the bigger budget.

Step 5: Split the budget 70/20/10

Run (70%): channels with proven pipeline.
Prove (20%): proof assets, advocacy, AI visibility.
Bet (10%): one or two agent experiments, each with a kill date.

Illustrative example: on Rs 2 crore, that’s Rs 1.4 crore Run, Rs 40 lakh Prove, Rs 20 lakh Bet. Fund Prove and Bet from what you pruned, not new money.

Step 6: Run the year in four beats

Quarter	Beat	Exit test
Q1	Audit and prune	AAO split done; Rupee Audit cuts made
Q2	Pilot two agents	Each beats its job-description metric
Q3	Scale what worked	Hours saved moved to Own work
Q4	Review and plan 2028	Pipeline per rupee up on 2026

Five mistakes that sink an AI-era plan

Cutting people before the agent has proved itself.
Counting licences and ignoring review time.
Buying tools before cleaning data.
Measuring output (posts, emails) instead of pipeline.
Hiring zero juniors.

The one-page 2027 plan (copy this)

Section	What to fill in
Revenue target	The company number marketing answers to
Pipeline needed	Target ÷ win rate
Readiness score	Your score out of 10 from the quick check
Work audit	Hours in Automate / Assist / Own
Humans	Roles, and what each one Owns
Agents	One job description per agent
Prune	Rupee Audit cuts, and the rupees saved
Pour	Where the savings go
Budget split	Run / Prove / Bet amounts
Quarterly beats	Exit test for each quarter
Scorecard	Pipeline, win rate, AI citations, CAC payback

The real shift

A 2027 plan isn’t really a budget. It’s a decision about which judgment stays human. So when the CFO asks why marketing needs the money, the answer isn’t “AI”. It’s “here’s the half we automated, here’s who checks it, and here’s what we bought with the savings.”

Marketers who can fill in this page will run teams. Anyone whose whole job sits in the Automate column should start moving now. That’s the next post in this series: what this plan means for the people inside it.

PS: If your plan has an “AI” line item but no named human reviewing each agent, you haven’t planned for AI. You’ve planned to be surprised by it.

PPS: Every rupee figure here is illustrative. Swap in your own before it goes anywhere near your CFO.