A career path began with migration to the US and entry into a booming UX role that felt relatable and in demand. Early work emphasized data-driven design: decisions backed by numbers, user tests, and analytics. That approach produced strong operational results but also pushed the industry toward process, templates, and measurable optimization. Data-driven workflows are easily replicated by AI or lower-cost labor and tend to flatten experiences through convergent design patterns. Heavy reliance on past metrics favors reactive iterations over inventive foresight. The net effect has been the shrinking of roles and the commodification of design work, prompting signs of change.
When I first came to the US a decade ago, I wasn't sure how I'd fit into the job market. I wasn't from here and didn't know the playbook. Through trial and error, I eventually found myself in the then-booming role of UX designer - a job that felt relatable, in demand, and easy to explain to others at the time.
Data-driven design is easily replicable, especially with AI. It's a great tool for an operator, but that has risked some design jobs. It flattens experiences. Optimizing for numbers alone converges toward sameness: endless scroll feeds, grid layouts, the same funnels. It's reactive. Most available data reflects only the past. Leading indicators are often hard to identify or measure. As a result, we tend to focus on lagging data, making iterations reactive rather than inventive or preventive.
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