Stability · Stability AI
On-brand AI: Strategy guide for customization success
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Key facts
- Cross-pollination: If employees are using personal AI tools for work tasks without IT permission – which 90 percent of employees are doing – they’re sharing your brand’s secret recipe with the public
- Instead of the model trying to guess what you want by looking at 10,000 cookies, it starts with your specific style as the baseline
- For brands Stability AI works with, the goal is usually to scale AI use across the entire marketing org
- In other words, it’s been trained on 10,000 images of cookies, and your cookie is going to start to look the same as your competitor’s cookie
Summary
By Alex Gnibus, Enterprise Product Marketing. Prompt engineering can produce good results at first, but it becomes complex, time consuming, and inconsistent at scale. Relying on out-of-the-box models leads to generic outputs and potential brand risk, especially when competitors use the same tools and data.