Understanding how people think
when technology changes.

Question

How should an AI product balance automation with user control?

Approach

I evaluated two fundamentally different interaction models using interactive prototypes designed to expose where trust broke down. Rather than comparing usability alone, the research focused on how people reasoned about AI decisions, uncertainty, and control.

Outcome

Established three design principles that became the foundation for subsequent AI features and informed the team's phased roadmap.

Human–AI Interaction Prototype evaluation Strategic research Design principles

Question

How do you make long-term product decisions when both the technology and the market are changing rapidly?

Approach

I synthesised multiple research streams (qualitative studies, behavioural data, competitive intelligence, industry trends) into a single strategic framework that helped teams distinguish established evidence from emerging hypotheses.

Outcome

Aligned multiple teams around a shared AI maturity model and established a trust-first approach for introducing increasing levels of AI autonomy.

Strategic synthesis Product strategy Workshop facilitation Research leadership

Question

Which usability problems were actually worth engineering investment?

Approach

I led comparative benchmarking research measuring comparable user behaviours across competing products, combining qualitative observation with structured scoring to distinguish cosmetic issues from those that genuinely affected confidence and task success.

Outcome

Shifted engineering priorities from simplifying workflows to improving predictability and feedback. The framework was reused across subsequent research programmes.

Comparative research Usability evaluation Research systems Executive communication