AI Adoption Roadmap for a Connected Health-Device Brand's Data Ecosystem
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Problem
Rich device data, no AI plan
A consumer connected-health device brand selling smart scales and blood-pressure monitors across 12 markets was accumulating millions of daily readings but had no AI plan. Product teams pitched competing ideas, three separate ML platform purchases were under discussion, and health-data regulation differed by market, leaving leadership unable to commit budget to any single direction.
Solution
Phased AI adoption roadmap
We built a phased AI adoption roadmap for the brand's data ecosystem. The engagement mapped the device, app and support data landscape, reviewed health-data regulatory constraints in each of the 12 markets, scored 26 candidate use cases on value and feasibility, set build-versus-buy positions for each, and defined a three-horizon delivery plan starting with one tightly scoped pilot.
Measurable Impact
What changed after launch
26 AI use cases assessed across devices, app and support, prioritised into a three-horizon roadmap
Health-data regulatory constraints mapped for all 12 markets before any model work was scoped
Estimated first-horizon platform cost cut by roughly 30% after consolidating three proposed ML stacks into one
First pilot, an automated device-reading quality-flag service, scoped, staffed and launched within 12 weeks of sign-off
Tech & Tools Used
What powered the build
Ready to Build your Connected Health Devices Business with AI Adoption Roadmap
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