LLMs can produce strategy decks in minutes — but many are built from SEO-era patterns, recycled playbooks, and case-study storytelling. Here’s how to build a strategy that survives contact with reality.
You can ask an AI to “create a marketing strategy” and receive a confident plan in seconds:
It reads like competence.
“The problem is not that AI can’t write strategy. The problem is that it often writes the shape of strategy — based on what the internet rewards — not the substance that grows a business.”
Many LLM outputs are trained on a web flooded with marketing content created for one purpose: to rank higher on Google. This environment generated a massive volume of polished “SEO copy” that optimizes for keywords rather than outcomes. When a model learns from that distribution, it inherits the tone, the structure, and the habits — including the flaws.
This article explores why AI-generated strategies so often contain nonsense (and why it’s hard to spot), how SEO-era writing distorts “case study thinking,” and how to build a strategy that is both modern and grounded — using AI properly.
If you’re also using AI to produce marketing assets, the same “fast but risky” pattern shows up in creative production too — see AI Marketing Visuals: The Boom, the Blind Alley, and the Hidden Cost of “Fast”.
LLMs learn patterns. Much of what they see online consists of:
As a result, the model becomes adept at producing:
But strategy is not “complete sentences plus a funnel chart.” Strategy is a set of choices under constraints.
Under-discussed effect: AI tends to optimize for “narrative closure.” Real strategy often ends with discomfort: tradeoffs, risks, what you will not do, and what you will measure to determine if you’re wrong.
Case studies online frequently suffer from:
AI doesn’t “know” which case studies are real experiments and which are marketing theater — it treats them all as equally learnable patterns. That’s why AI can confidently recommend the wrong path: it’s repeating narratives, not verifying causal links.
This is also why “strategy decks” often sound like polished copy instead of decision-making. If you want to sharpen the difference, start with Is Copywriting a Talent or a Skill?.
If you encounter these, treat the output as a draft of words, not a strategy:
Think of AI as a junior analyst with infinite speed and zero accountability. Your role is to add accountability.
Begin by listing constraints before considering any channels:
Without constraints, you get generic output.
If the problem is actually “who we are” and not “which channel,” you’ll get more leverage from fixing the brand system first — How to Rebrand: A Complete Breakdown of the Process (and Pitfalls).
Not all inputs deserve equal weight. Use this simple hierarchy:
AI can synthesize across levels — but you decide which level carries the most weight.
Books aren’t perfect, but they filter out much of the SEO noise:
Use AI to extract frameworks from books and turn them into checklists — but keep the source list explicit, so you know what the strategy is built on.
Instead of: “Create a marketing strategy for my brand.”
Try: “Ask me 25 questions you need answered to build a defensible strategy. Group them by research, positioning, channel economics, and measurement.”
Then answer only what you can support with evidence.
Replace statements with tests:
| AI-style claim | Strategy version |
|---|---|
| “TikTok will drive awareness.” | “We will test 12 short videos, measure branded search lift and site visits by geo, and decide after 3 weeks.” |
| “Email will improve retention.” | “We will run a 4-email onboarding sequence and compare 30-day retention vs control.” |
| “SEO is important.” | “We will target 5 high-intent queries and track assisted conversions over 90 days.” |
This automatically removes nonsense: claims that can’t be tested aren’t strategy.
After drafting your strategy, ask:
AI excels at stress-testing your plan if you prompt it to challenge it.
You can experiment with bold creative directions — but keep operational standards consistent:
When execution is standardized, experiments become measurable rather than chaotic.
Combine:
“If a strategy can’t explain what it will not do — and how it will detect that it’s wrong — it’s probably not a strategy. It’s a content artifact.”
AI didn’t invent bad marketing. It just makes it faster to produce a plan that looks strategic without being anchored in reality.
The long-term fix is simple (not easy): treat strategy as a system of choices, evidence, and tests. Use AI to accelerate the boring parts — summarizing, comparing, red-teaming, drafting variants — but keep a hard rule that every important claim must attach to either:
One practical “anti-nonsense” trick: if you can’t write down a kill rule (“we stop if X doesn’t improve by Y in Z weeks”), you’re probably not running strategy — you’re running hope.
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