Case study

Enzo.Reimagining healthcareworkforce operations through AI

AI product strategy, systems thinking, interaction design, decision frameworks, prototyping

Transforming a chatbot-style assistant into the central operating system for healthcare workforce operations, with an AI-first interaction model and ecosystem vision.

Reimagining healthcare workforce operations through AI

Overview

Transforming a chatbot-style assistant into the operating system for healthcare workforce operations.

Enzo began as a chatbot-style AI assistant used to answer questions and provide operational support for hospital and care staffing teams.

Working closely with business and product leadership, I helped define a broader vision: transforming Enzo from a standalone AI agent into the central operating system for healthcare workforce operations.

Rather than requiring teams to navigate multiple tools, dashboards, and rotas, Enzo would become the intelligence layer connecting them all.

The platform would proactively identify issues, coordinate actions, and enable faster decision-making across hospitals, trusts, and care providers.

This work established the strategic direction, interaction model, and ecosystem vision for AI-powered healthcare workforce management.

The challenge

Operational decisions were reactive because critical information lived across fragmented systems.

Operational teams managed nursing rotas, compliance, shift fulfilment, forecasting, and payroll through a fragmented collection of systems.

15–20 min

Average time to investigate a single staffing gap before action could be taken.

The challenge wasn't improving individual workflows. It was redesigning how operational decisions were made.

As a result

Critical information was spread across multiple tools
Operational issues required manual investigation
Decisions were often reactive rather than proactive
Scaling operations meant increasing headcount

My role

Partnering with executive stakeholders to define the product vision, interaction model, and AI operating model.

I partnered with executive stakeholders, product leaders, and engineering teams to define the future vision for Enzo.

Creating the long-term product vision and designing how autonomous agents would operate across workflows.

Responsibilities included

Creating the long-term product vision
Designing the AI interaction model
Defining how autonomous agents would operate across workflows
Developing high-fidelity prototypes to validate concepts
Aligning stakeholders around an AI-first operating model

The vision

Moving from a chatbot to an ecosystem that monitors, recommends, and automates where appropriate.

The key shift was moving Enzo from a chatbot to an ecosystem. Instead of asking AI for information, Enzo would actively monitor staffing operations, identify risks, recommend actions, and automate decisions where appropriate.

Connected experiences forming the Enzo ecosystem, from Inbox to Performance.

Inbox

Decision-ready staffing issues requiring attention

Agent Hub

Visibility into autonomous agents working in the background

Operations Hub

Live rota insights, forecasting, and scenario planning

Ask Enzo

Conversational access to workforce intelligence

Train Enzo

Governance, rules, policies, and AI behaviour management

Enzo Performance

Transparency into automation, confidence, accuracy, and business impact

Key design principles

Transparent automation, human control, and one connected ecosystem.

AI as a Decision Engine

Enzo continuously monitors staffing activity and surfaces only what requires human judgement

Transparent Automation

Every recommendation includes reasoning, supporting evidence, and confidence levels

Human Control

High-confidence actions can be automated while more complex decisions remain human-led

One Ecosystem

A connected experience replacing fragmented rota and compliance workflows

Impact

Early-stage work that established vision, alignment, and validation through interactive prototypes.

Although still in early-stage development, the work has already influenced strategy around agentic systems and created a shared AI operating model across stakeholders.

Complex staffing workflows were validated through interactive prototypes before roadmap commitment.

Established the organisation's vision for AI-powered healthcare operations
Influenced strategy around agentic systems and automation
Created a foundation for future product roadmap planning
Enabled stakeholder alignment around a shared AI operating model
Validated complex staffing workflows through interactive prototypes

Stakeholder feedback

“An incredibly exciting design that uses AI to solve real staffing challenges, pushing us towards a future of agentic workforce management. Excited to see how this evolves into our future product.”

01Enzo

Inbox

Decision-ready staffing issues surfaced with confidence scores, reasoning, and evidence, so operational teams act on what matters instead of searching across tools.