Users are dissatisfied with purely AI-generated creative outputs like interior design, calling it "slop." This creates an opportunity for platforms that blend AI's efficiency with a human's taste and curation, for which consumers are willing to pay a premium.

Stripe's website features a data visualization that isn't functionally interactive but serves a critical purpose. It communicates care, technical prowess, and global scale. For a company handling money, this "utility in beauty" builds subconscious user trust and makes the product more compelling.

Customizing AI image models provides concrete business advantages. E-commerce companies can ensure consistent product visualization, design agencies can automate client-specific styles without manual editing, and art studios can generate concept variations that adhere to their established visual language, increasing efficiency and brand consistency.

Don't accept the false choice between AI generation and professional editing tools. The best workflows integrate both, allowing for high-level generation and fine-grained manual adjustments without giving up critical creative control.

AI tools are raising the baseline quality of design, making a "7 out of 10" experience nearly free to produce. Stripe sees this not as a call to do more, but to reallocate saved time toward creating exceptionally crafted, "15 out of 10" moments that truly differentiate the product.

Because AI can generate content in seconds, it is perceived as low-effort. This violates the "labor illusion," where effort signals quality. A study showed that when a poster was labeled "AI-powered" instead of "hand-drawn," purchase intent dropped by 61%. Brands using AI must reframe the narrative around the effort of building the system.

AI can generate vast amounts of content, but its value is limited by our ability to verify its accuracy. This is fast for visual outputs (images, UI) where our eyes instantly spot flaws, but slow and difficult for abstract domains like back-end code, math, or financial data, which require deep expertise to validate.

By handling repetitive production work, AI gives designers bandwidth to focus on high-impact, creative problems. This includes innovating on previously overlooked details like loading states, which have new importance in AI-driven products for building user trust.

Consumers equate effort with quality and devalue work perceived as instant, like AI output. To combat this 'labor illusion,' stress the human expertise, years of research, or complex system development that enables the AI. Focus on the effort invested in the process, not just the speed of the result.