Structuring AI Innovation for a Global MedTech Enterprise

Designing the decision layer for their largest revenue-contributing division

AI innovation
regulated industries
product-Service design

ROLE

Strategic Designer

INDUSTRY

Medical technology

Timeline

Jan'25

(3 week sprint)

A large medtech organisation was pushing hard on AI as a strategic priority. Ideas were forming across the customer services team, but arriving half-formed, and always

at the same bottleneck.

Investments were being made before the right questions had been asked. Customer value wasn't being realised, and leadership had no real visibility into the innovation pulse of the team. As a result, initiatives were duplicated, with no institutional learning.


The right conversations were already happening just informally, inconsistently, too late. The intelligence existed inside the organisation, but had no structure.


And the entire weight of making AI innovation work was concentrated on one person.

In a regulated environment operating under the EU AI Act, early decisions about data, compliance, and ownership have consequences that are hard to undo

The Act mandates continuous risk management and documented data assumptions throughout the AI lifecycle, not at the end of it.

Solution overview - INTERNAL SERVICE-SYSTEM

I designed AI Front Door - an upstream sensemaking system that gives early-stage AI ideas structure and visibility before they reach formal evaluation.

I designed AI Front Door - an upstream sensemaking system that gives early-stage AI ideas structure and visibility before they reach formal evaluation.

A guided entry flow surfaces assumptions and uncertainties early. A shared living canvas makes thinking visible to the right people simultaneously. An intelligent routing system directs conversations to legal, data, and technical experts in a prioritised sequence, constraints discovered before commitment,

ENABLING LEADERSHIP VISIBILITY

For leadership: a real-time innovation intelligence layer tracking intake momentum, idea lifecycle, participation patterns, and recurring uncertainty trends.

For leadership: a real-time innovation intelligence layer tracking intake momentum, idea lifecycle, participation patterns, and recurring uncertainty trends.

Tracking success

Among other experience level feedback systems, two system-level metrics were designed to measure team-wide AI project visibility and productive idea development.

Among other experience level feedback systems, two system-level metrics were designed to measure team-wide AI project visibility and productive idea development.

Time to Evaluation

The time an idea spends in early sensemaking before reaching a clear outcome.

AI Registry Consultation

Whether contributors actively check existing initiatives before submitting or progressing an idea.

IMPACT

In a customer services (CS) team that represents the highest revenue contribution in the organisation, the cost of misaligned AI investment is not abstract. And for the first time, leadership would have real visibility into where innovation energy is forming, where it is stalling, and what is costing them before a single euro is formally committed.


The system was designed to reduce the time and cognitive cost of moving an AI idea from spark to structured conversation cutting the rework, duplication, and premature investment that accumulate when the wrong questions get asked too late.

Let's Build

it Right.

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Linkedin

ankulkarni98@gmail.com

Anuja Kulkarni

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