AI Image Generation Tools
AI image generation tools don't replace a photographer or designer. They replace the time spent searching for the generic stock photo that, deep down, nobody really found suitable.
“An AI-generated image to illustrate a real case study with a real customer, without disclosing it, isn't a time saving. It's a credibility risk no saving justifies.”
Otto GTM ObservatoryWhere it works and where it generates reputational risk
AI image generation is particularly effective for abstract illustrative content (concepts, visual metaphors for blog articles) and for quickly generating visual variants to test in ad campaigns. It becomes risky when used to represent verifiable facts, like real people from a case study or actual company events, without explicitly disclosing that the images are generated.
In B2B contexts, where credibility is the decisive factor, a generated image mistaken for real photography of a customer or event, if discovered, damages trust far more than the time saved in production.
Anti-patterns
Common mistake: using AI-generated images to illustrate real customer case studies or testimonials without disclosing it, exposing the company to serious reputational risk if the practice is discovered by the public or the customer themselves.
Second mistake: generating a high volume of generic images without editorial curation, getting visual material the B2B audience quickly recognizes as mass-produced and lacking specific care.
Practical Application
A company uses AI-generated images to illustrate abstract concepts in a series of blog articles, explicitly disclosing the use in the caption. Visual content production time drops 70% with no negative credibility impact, measured via reader surveys. In parallel, the company maintains verified real photography for all case studies with named customers, avoiding the associated reputational risk.