AI Incubator and Innovation Hub Setup for a MedTech Corp
Waking Up to the New Reality
When generative AI forced its way onto the agenda and demanded change, even in a highly regulated MedTech environment with a lot of built-in inertia, it was clear this was not just another tool.
The day after ChatGPT's public release, our CEO called an emergency all-hands leadership meeting with a simple question: “How do we win in AI?”
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If we moved too slowly, we risked losing ground to more agile competitors. If we moved too fast without structure, we risked compliance issues, reputational damage, and chaos.
As a part of the digital transformation team spanning multiple brands, marketing, commercial, production, IT, and data, I joined a newly formed task force reporting directly to the Chief Transformation Officer.
We were given a rare combination in a corporate environment: a clear mandate, executive sponsorship, and enough freedom to get things done. My role was to act as program manager and operational backbone, coordinating local market teams, global functions, and external partners to turn AI from a buzzword into working solutions.
Figuring Out Where We Really Stand
Before talking about the future, we needed to understand the present. It turned out there was already a surprising amount of AI-adjacent work happening inside the organization. Data teams were experimenting with machine learning. Production and quality control were toying with computer vision. Local markets had small-scale tools built around sophisticated automation. None of this was visible from the top, and almost none of it was connected.
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We went hunting for the people who had been quietly building things for years – the data scientists, the engineers, the commercial leads who had been experimenting with AI-like tools long before it became a board-level priority. Talking to them gave us a map. Now we knew where the energy was and which ideas had the potential to grow beyond a single market or function.
The narrative shifted from “headquarters is launching an AI initiative” to “here is a platform to amplify what you’ve already started, with support, structure, and a route to global impact.”​​
Turning Ideas into a Real AI Pipeline
But simply cataloguing existing initiatives wasn't enough. We needed fresh ideas and broad engagement. That’s where the AI competition came in. We opened a company-wide call for AI projects, inviting teams from all functions and markets to propose initiatives that could genuinely move the needle.
This wasn’t a side contest for the intranet, but a strategic program with senior sponsorship and real outcomes. To support he project teams, we brought in Accenture as subject matter experts and transformation partners. They helped us educate leadership on what was and wasn’t realistic, while also supporting teams to translate their business challenges into viable AI use cases.
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Very quickly, we moved from “we should do something with AI” to a tangible portfolio. Hundreds of ideas came in from all corners of the organization: commercial, production, logistics, training, marketing, and more.
The challenge then was to bring structure without killing momentum. We worked with global IT, data, finance, legal, and compliance teams to design an evaluation and shortlisting process that would filter out the noise but keep the best ideas alive.
From MVPs to a Board-Backed AI Portfolio
Once teams had built their MVPs, the work shifted from ideation and experimentation to validation and selection. We organized an AI competition final where the most promising projects were presented to the C-suite.
Here, presentation mattered as much as technology. We needed to tell a clear story: what problem each solution solved, how it worked, what it would take to scale, and what value it would create. Together with Accenture and internal stakeholders, we developed a grading framework to help senior leaders compare very different initiatives on equal terms, looking at value, risk, scalability, strategic fit, and implementation complexity.
From hundreds of initial ideas, we ended up with dozens of functioning MVPs. Out of those, five flagship projects were selected for immediate funding and global scale-up.
Among them were a generative AI solution for partner training that created tailored educational video content at scale; a chatbot-powered product selection assistant that combined product knowledge with commercial logic and health education; and several production-focused use cases around fault prediction, prevention, and predictive maintenance.
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All these projects came with a clear financial story, measurable efficiency gains, and a realistic path to integration into the existing digital ecosystem.
A Lasting Innovation Engine
The final step was to make sure the momentum carries onward. To make innovation stick, we needed a permanent structure to own and grow what we had started.
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Working with the Chief Transformation Officer, business architects, Accenture, and senior stakeholders, we designed an Innovation Hub for our business unit. This structure brought together a multidisciplinary global team and a group of senior sponsors, who took over responsibility for scaling the winning MVPs, maturing the rest of the portfolio, and continuously sourcing new ideas.
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It became the place where experimentation and governance met. Instead of every new initiative having to fight its way through the organization one stakeholder at a time, the hub provided a clear process, shared standards, and a common language for AI projects.