The objective of this study was to understand how GenAI features within financial desktop platforms were being accessed, used and trusted in real professional workflows. The focus was on identifying adoption patterns across roles, repeat usage behaviour and whether these capabilities were becoming embedded tools or remaining occasional experiments.
GenAI was becoming a visible part of financial desktop platform positioning. But teams still lacked clear evidence on what actually stuck in day-to-day work and what was only being tried once.
We treated GenAI capabilities as behavioural signals rather than feature checklists.
Here’s how we did it:
The analysis showed that GenAI adoption was present but uneven across roles and tasks. Features supporting summarisation, information scanning and initial analysis gained more traction, while others saw limited repeat use.
Trust emerged as the defining factor. Where outputs felt predictable and grounded, adoption deepened. Where results required constant verification, usage declined.
These insights helped shift conversations from “Do we have GenAI?” to “Which capabilities are genuinely embedded in workflows?” This provided clearer direction for product refinement, positioning and long-term roadmap priorities.