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AI / Enterprise Technology

30% productivity gain identified through an AI-powered enterprise security hub

Created the service strategy, end-to-end workflow, and adoption conditions for a trusted AI-enabled development and security capability.

This is a condensed, NDA-safe format. Request a private case study walkthrough →
A human hand and a robotic hand reaching toward each other, representing human-AI collaboration
IndustryGlobal IT consulting
My roleLead Service Designer
Mixed-Methods Research
Product Designer
TeamProduct, AI/ML Engineering, Enterprise Architecture
TimelineFour weeks
The Mission

Turning an AI prototype into an enterprise-ready capability

The Situation

The organization was building a white-label enterprise security hub and developer lifecycle AI capability, one meant to work across teams and portfolios, not just as a single internal tool.

The Response

The response was a proof of concept built to provide decision confidence, stronger threat tracking and mitigation across the enterprise portfolio, and an accelerated development lifecycle.

My Role

As Service Design Lead, I guided the initiative from research to real workflow to prototype, uniting executive vision, developer needs, and AI ethics.

The Challenge

A working prototype that wasn't ready for real work.

The prototype demonstrated technical feasibility, but lacked research, workflow context, governance, trust considerations, and a scalable information architecture.

Security

Rapidly changing guidelines across the portfolio

Understanding

Limited grasp of the challenge across roles

Adoption

Hesitancy among users who feared replacement

ROI

Leadership pressure amid minimal experimentation infrastructure

"Threats are constantly emerging and the portfolio is large." Enterprise Architect
"Balancing features and speed with security." Product Owner
"Constant disruption to the SDLC with vague remediation guidelines." Project Architect
"Multiple insight formats are challenging to automate into PRDs." UX Researcher/BA
My Approach

The Strategic Shift

Reframing before refining: the prototype was not treated as proof that the right service had been designed. I reframed it as an enterprise service spanning multiple roles, decisions, workflows, trust requirements, and adoption conditions.

Can we build this?

Should we build this? Who is it for? What makes it successful?

Simplified reconstruction. Proprietary workflow details have been removed or altered.

The Transformation

From Technical Proof-of-Concept to Enterprise Capability

The engagement evolved from a technical proof of concept into an enterprise-ready capability with validated workflows, governance, and a clear path to adoption.

30% net increase in developer productivity

Achieved by automating repetitive cognitive tasks and surfacing relevant context at the moment of decision.

From manual threat tracking to continuous visibility
Automated tracking across the enterprise portfolio
Designed for confident decision making, not just speed
Human review, transparency, and explainable recommendations
Built for adoption, not just demonstration
Validated workflows, decision points, trust factors, and human judgment factors
"Every time I meet with this team, I'm blown away by the progress they've made! Thank you for the amazing work getting the AI Hub ready to demo." Global Consulting Partner

Want a private walkthrough?

This public version has been simplified to protect client confidentiality. I'd be happy to walk you through the research, strategic decisions, representative artifacts, and transformation roadmap with hiring teams and prospective clients.

Request a Private Case Study Walkthrough
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