AI can draft a tagline in seconds, suggest ad variations and organize campaign data. But a new commentary from the founder of Brick Marketing—who has spent 28 years in digital marketing and worked with more than 600 B2B and B2C companies—warns that speed is not the same as judgment. The core message: keep AI in implementation, and keep strategy with experienced marketers who understand customers, budgets and sales cycles.
An answer can sound reasonable and still overlook something as basic as how long customers take to buy.
The author argues that someone has to recognize what is missing before that advice becomes a marketing plan.
The test before you delegate
Before handing any decision to AI, ask whether you could evaluate the answer without the tool. If a report recommends more website traffic, a marketer still needs to know who already visits, what happens after they arrive, and whether the offer is clear. More visitors can simply amplify an existing conversion problem.
Knowing how to prompt a tool does not replace understanding customer behavior, reviewing performance or writing a message that gives someone a reason to respond. The author suggests making work part of training: review a campaign and explain what you would change before asking AI for suggestions.
Implementation yes, strategy no
The piece draws a clear line. AI can help with ad variations and tagline ideas, organizing information and suggesting questions. It should not decide positioning, priorities or investments. Those decisions require knowledge of the business, its customers and its sales process.
A six-month purchase cycle changes the reading of early campaign results. A few weeks without an immediate sale may not mean failure; it means evaluation has to match how the company wins business. An experienced marketer should decide what evidence would justify a change.
- Use AI for defined tasks such as ad variations and taglines.
- Keep positioning, budget and priority decisions with experienced marketers.
- Make AI cite its sources and read whether they support the recommendation.
- Test search marketing advice on a small scale before changing the whole site.
Search advice needs proof
Search marketing recommendations deserve scrutiny because acting on them can create work across an entire website. Before publishing more pages, ask which audience they serve, what information is missing and whether the content will help someone decide or just add volume. Then ask AI to cite where its advice came from and actually read the sources. A link alone is not evidence.
Test before scaling. Decide what improvement you expect, how you will measure it, and when you will review the results. Keep a written record of what changed and why. If you change content, navigation and contact processes at once, it becomes harder to tell which change helped.
Stay accountable to outcomes
AI does not absorb responsibility. An experienced marketer should approve the work and own the outcome: check accuracy, relevance and brand voice, and make sure the business can support any claims. Junior marketers should explain why they accepted one suggestion and rejected another—that conversation shows whether the person understands the work or is just relaying an answer.
Measure qualified leads, sales opportunities and revenue against the goal, not just publishing volume. If output rises while results plateau, the author suggests revisiting the offer, improving existing content, or speaking with the sales team about what prospects are asking—before asking AI to produce more.
Source: MarTech
