Where does AI pay off in marketing for mid-sized companies, and where not?
AI pays off in marketing above all where one clear, approved message turns into many versions: variants for channels and audiences, translations, content from existing material, research and testing messages before launch. It does not pay off as a replacement for deciding what your company stands for, and not for more content without a goal. People set the direction, AI delivers, people check and decide.
Where AI really helps in marketing
1. Turning one message into many versions
The core message is set and approved. AI turns it into versions for the website, ads, mailings and social media, for different audiences and languages. This saves the most time, because the thinking has already been done.
2. Making use of existing material
A talk, a webinar, a customer conversation with consent: there is usually material for several posts, an article and an email in it. AI finds the best parts and turns them into drafts.
3. Testing messages before budget is spent
Which message convinces which audience? With an AI market simulation, launches, messages and competitor responses can be played through with thousands of simulated stakeholders before you go to the real market. More on the AI market simulation
4. Research and market monitoring
What are competitors writing, what are customers asking, which topics are emerging? AI collects and summarises. Important: always check figures and studies against the original source before they go into a text.
5. Preparing approval early
In many companies a text has to pass a specialist or legal review. AI can work through a checklist beforehand, for example whether every figure has a source. The review itself stays in the company. Plan it in early instead of bolting it on at the end.
Where AI does not help in marketing
- Positioning: what your company stands for and whom it wants to reach is a leadership decision. AI can make suggestions, a person has to decide.
- More content without a goal: twice as many posts without a clear message mostly create noise, not customers.
- Unchecked expert claims: figures, studies and product promises never go out unchecked.
- Invented voices: testimonials, experiences or quotes that do not exist have no place in marketing, no matter who writes them.
How to choose your first use cases
The Shortlist Rule applies in marketing too:
No AI project without a shortlist: collect 10 to 20 ideas, sort them by effort, value and risk, pick three.
How to do this step by step is in the answer How do you choose your first AI use cases?
Possible metrics in marketing:
- Time from briefing to approved version
- Number of variants you actually test
- Enquiries or conversations that come out of a campaign
Frequently asked questions
Does Google rank AI-written content lower?
In the post “Google Search's guidance about AI-generated content” (Google Search Central, 8 February 2023), Google explained that what matters is the quality of content, not how it was produced. Using automation to generate content mainly to manipulate rankings, on the other hand, violates Google's spam policies. So what counts is whether your text answers a real question well. Source: https://developers.google.com/search/blog/2023/02/google-search-and-ai-content
Do we have to label AI-generated content?
That depends on the content and how it is used. The EU AI Act sets out transparency obligations for certain cases, for example artificially generated images, audio or video. Clarify internally what applies to your content. This is guidance, not legal advice.
Who checks what the AI writes?
The people who check today: your team for the substance, and where needed the legal or specialist approval. AI shortens the way to the draft, not the accountability for the result.
Do we need a dedicated AI tool for marketing?
Start with the work, not the tool. To begin with, what you already have in the company is often enough. Which tool fits follows from the three use cases on your shortlist.
More answers
- Where does AI deliver measurable results in sales first, in mid-sized companies?
- How do you choose your first AI use cases?
- Why do AI pilots get stuck, and how does AI get into daily business?
About the authorSelina Gaertner, AI for Leadership, Sales and Marketing. TÜV Rheinland certified AI Strategy Consultant, more than ten years in sales and marketing in medical technology, co-author of the Amazon bestseller “Fokus Mensch”.
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