Hello!
Using AI for content creation was an easy adoption for marketing orgs. Where have we gone since then? And where are we headed?
Startups are shrinking and “right-sizing” their marketing teams, not just because of budget pressure, but because they aspire to have AI take over the work.
Founders are hesitant to hire. And increasingly, they don’t.
Shopify and Duolingo have said they won’t fill a role unless AI can’t do the job. Klarna rolled out an AI assistant that performs the work of 700 people, they’ve since softened the initiative and are bringing some humans back into the equation.
The learning is still happening, but it’s clear that this IS the direction of businesses that want to scale fast.
And startups, unburdened by legacy systems or bloated headcount, are often the first to adopt a new model.
Vision Meets the Messy Middle
An AI-first marketing org isn’t just a team using ChatGPT to write copy faster.
It’s a re-architecture of how work gets done, where systems replace roles, and loops replace linear campaigns. The goal isn’t to scale content. It’s to scale outcomes.
Well, that’s the vision.
AI is transforming marketing fast, but we’re still in the messy middle.
From what I’ve seen across companies, tools, and marketing teams AI is dramatically reshaping how work could be done, but:
Legacy expectations and distraction still dominate “Can you make this viral?” “Get us in WSJ.” “Send champagne to our ICP.”
Processes are duct-taped together: AI tools are powerful, but orchestration is still clunky.
Humans still carry the strategic lift: positioning, creative judgment, prioritization, cross-functional alignment. And that may remain true for a while.
Leaders expect AI efficiency without changing the system. They want leaner teams and big output without treating AI like a real transformation.
So yes, while AI-first is the direction, the day-to-day still includes a mix of brilliance, brute force, and BS.
In the AI First Marketing Org, Strategy Still Leads, but Execution is Embedded
You still need a sharp go-to-market strategy:
Who are we for?
What do they care about?
What triggers action?
How does our product meet that moment?
But in an AI-first model, strategy isn’t something you finalize in a doc and revisit quarterly. It lives inside the system. You still have to do the work.
With AI embedded in execution your ICP, messaging and content aren’t locked in decks, Notion, or just tagged in a database. They are built into systems that feed targeting models, power AI-driven variations, and inform campaigns in real-time.
Strategy becomes modular, testable, and adaptable.
Strategy and AI work together in the best-performing marketing orgs.
🔁 Execution Moves from Campaigns to Loops
Traditional marketing = Plan > Build > Launch > Wait > Optimize
AI-first marketing = Build once, loop forever.
Here’s what the loop looks like:
Create: A strategist or founder outlines key ideas, POV, and assets (could be a product explainer, podcast clip, or sales deck)
Multiply: AI tools repurpose that asset into LinkedIn posts, blog snippets, emails, and even short video scripts
Distribute: Channels are auto-populated or lightly managed by a solo operator, think Buffer meets Zapier with smarter logic
Listen: AI tracks engagement signals (clicks, watch time, heatmaps, replies)
Adapt: High-performing ideas are recycled into future content; low-performing content is dropped or revised
Re-feed: Everything flows back into the AI content engine with updated inputs
What you end up with isn’t a never-ending content treadmill. It’s an active content engine that refines itself over time, driven by real buyer signals.
AI-first orgs don’t “launch campaigns.” They campaign constantly, always learning.
🧱 The Stack Becomes the Team (Sort Of)
The reality of automating loops, that always-on marketing, is reality. And it’s happening.
But marketing encounters a lot of extraneous projects, ad-hoc requests, and variation (crisis, events). And let’s not forget marketers are already doing multiple jobs as it stands today. This is where some of the reality of an AI-only vs an AI-first org hits.
So, while AI is accelerating processes and reducing the required team size, we’re not ready to replace the team.
But let’s look into the future! Picture, if you will, a strategist and one person who can architect and manage the stack.
Here’s how that might look at a startup:
Traditional Hire | AI-First Equivalent |
Content Marketer | Founder’s POV + AI copy system |
Paid Ads Manager | Intent data + AI-generated creatives |
Email Marketer | Automated flows fed by content loops |
Marketing Ops | No-code workflows + AI analytics |
SDR or BDR | Buyer signals + warm outbound engine |
This can turn marketing into a system where a startup can punch above its weight. We aren’t there today, but we are getting closer. Solid fundamentals, with AI efficiency, will be the winning combo.
AI-only vs an AI-first org - While AI adoption IS a big advantage, the idea of full auto pilot may not align with the expectations of marketing in the real world. At least not for now.
Instead of asking “who do I need to hire,” founders at lean startups are asking:
What can be done with systems, what needs a human, and where can I multiply the impact of both?
Most marketing teams don’t need to focus on more lead gen.
They need a consistent, smarter go-to-market engine.
Book a strategy sprint to start building your modern GTM system, built for AI-era buyers and efficient growth.
