AI Marketing Health Check: 15 Questions to Audit Your Strategy

AI can massively boost your marketing efforts, but only when used with intention, structure, and clear goals. This health check transforms random AI usage into a simple system you can audit in just one afternoon.

Why an AI Marketing Health Check Matters

Many businesses rushed into AI tools for content creation, advertising, and automation without establishing a solid plan. The result? Duplicated tools, messy workflows, and content that doesn’t quite match your brand voice.

This AI Marketing Health Check provides 15 targeted questions to quickly identify what’s working, what’s risky, and where your biggest opportunities lie. It’s perfect for small businesses, in-house marketing teams, and agencies that already use AI or are planning to start soon.

Section A: Strategy and Goals (Questions 1-3)

Without strategy, AI simply helps you move faster in the wrong direction. Start by checking whether your AI usage actually ties to clear business outcomes.

Q1: Do you have clear marketing goals that AI is supposed to support?

Think traffic, leads, sales, retention, or brand awareness. If you can’t connect each AI use case to a specific goal, you’re guessing rather than managing.

Q2: Do you know which core marketing activities AI should and shouldn’t help with in your business?

For example, AI might assist with drafts and data analysis, but critical positioning or offers should remain human-led.

Q3: Is there a simple, documented AI usage policy or playbook your team understands?

Even a one-page document clarifying where AI is allowed, how it’s used, and what requires human review can prevent chaos down the line.

Section B: Tools and Workflows (Questions 4-6)

Most teams are either under-using AI or drowning in too many tools. This section checks how organized your setup actually is.

Q4: Which AI tools are you using today, and do you know exactly what each one does?

Create a simple list including tool name, main use (content generation, image creation, automation), and the person responsible for managing it.

Q5: Are your AI-assisted workflows documented, or do they only exist in people’s heads?

A workflow could be as straightforward as: Brief → AI draft → Human edit → Approval → Publish.

Q6: Are you paying for duplicate tools doing the same job?

If two tools both generate blog drafts or both schedule posts, consider consolidating to cut costs and reduce complexity.

Section C: Data, Privacy, and Risk (Questions 7-9)

AI can create significant risk if data and compliance aren’t handled carefully. This section ensures you’re not accidentally exposing sensitive information.

Q7: Do you have clear rules on what data can and cannot be shared with AI tools?

For instance, no raw customer personally identifiable information (PII), no confidential financial data, and no unreleased product details in public tools.

Q8: Do you know how each tool handles, stores, and uses your data?

At minimum, someone on your team should have read the data and privacy sections before using a tool with customer information.

Q9: Do you consistently review AI outputs for legal, compliance, or brand risks before publishing?

This is especially critical in regulated industries. AI can hallucinate claims or promises, and a human must catch anything that could create legal or trust issues.

Section D: Quality, Brand Voice, and Accuracy (Questions 10-12)

AI can write, but it doesn’t truly “own” your brand. This section checks whether your outputs still sound like you and remain accurate.

Q10: Do you have clear brand voice guidelines, and are they applied to AI-generated content?

Define your tone (friendly, formal, expert, playful), vocabulary to use or avoid, and include examples of what “good” brand copy looks like.

Q11: Is there always a human review and editing step for important AI outputs?

Web pages, emails, landing pages, and ad campaigns should never skip human oversight. AI drafts are starting points, not final versions.

Q12: Do you regularly check AI content for factual accuracy and originality?

Spot-check statistics, quotes, and claims. Make sure your content isn’t just a bland remix of what’s already available online.

Section E: Measurement, ROI, and Optimization (Questions 13-15)

If you don’t measure results, you can’t know whether AI is an asset or a distraction. This final section focuses on real impact.

Q13: Can you clearly show what AI has actually saved or earned?

Measure time, cost, revenue, or leads. For example: “AI cut blog drafting time from 4 hours to 1 hour per article,” or “AI-assisted ads improved click-through rate by 20%.”

Q14: Are you running simple tests to compare AI-assisted versus non-AI approaches?

Try A/B testing AI-assisted email subject lines, ad copy, or landing pages against your traditional versions.

Q15: Do you have a plan to improve your AI setup every quarter?

This might include refining standard prompts, replacing underperforming tools, or adding one new automation at a time.

How to Score Your AI Marketing Health Check

Use this simple scoring system to see your baseline clearly.

For each question, give yourself:

• 1 point for “Yes, clearly and consistently”
• 0.5 points for “Partially / sometimes”
• 0 points for “No” or “Not sure”

Then total your score out of 15:

• 0-6 points: High risk / low maturity. AI is likely adding more noise and risk than value.
• 7-11 points: Decent foundation, but significant room for optimization. Prioritize strategy, workflows, and quality assurance.
• 12-15 points: Strong AI foundation. Focus on deeper automation and performance optimization.

You can also color-code each section (strategy, tools, data, quality, ROI) as red, yellow, or green to identify where the main gaps exist.

Quick Wins You Can Implement This Week

Even if your score is low, a few simple actions can quickly improve your AI marketing setup.

Write a one-page AI policy. Include allowed use cases, banned data types, review requirements, and who approves new tools.

Document one core AI workflow end-to-end. For example: “How we use AI to draft and publish blog posts” with each step and owner clearly defined.

Add mandatory human QA before publishing. No AI-generated content should go live without a human checking brand voice, accuracy, and compliance.

Cancel overlapping tools. If two tools do essentially the same thing, keep the better one and remove the rest to save money and mental energy.

Set one clear KPI for AI. For instance: “Reduce content production time by 40%” or “Increase ad click-through rate by 15% using AI-assisted copy.”

Turn Random AI Usage Into a Real System

AI itself isn’t a strategy. It’s a set of powerful tools that, without clear goals, standards, and ownership, can easily create more confusion than value. With a simple health check like this, you can assess where you stand in a single afternoon and decide exactly what to fix next.

Revisit these 15 questions every 3-6 months as your tech stack and skills evolve. If you run an agency or internal marketing team, you can even transform this into a structured “AI marketing audit” that you use with clients to diagnose issues and propose clear, human-plus-AI improvement plans.

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