When people talk about AI, the conversation often focuses on technology.
What I find far more interesting is what happens when people begin using that technology to solve real problems.
Over the past year, our AI Champion network has grown into a community of employees representing functions across Advanced Surgery. From technical writing and software engineering to systems engineering, design assurance, quality, and many other disciplines, employees are finding practical ways to use AI to work more efficiently and focus their expertise where it creates the greatest value.
What has impressed me most is how quickly curiosity has turned into practical impact.
Rather than viewing AI as a future possibility, our teams are applying it today. They are accelerating access to information, strengthening collaboration, streamlining complex processes, and creating more time for the problem-solving and critical thinking that drive meaningful results.
Scaling Innovation Through Shared Learning
One of the most important lessons from this journey is that successful AI adoption is not driven by technology alone. It is driven by people who are willing to experiment and share what they discover.
That is the role our AI Champions play across Advanced Surgery. Each champion serves as a resource within their function, helping colleagues understand new capabilities and identify opportunities to create value. As teams gain experience, they begin developing solutions tailored to their own challenges and sharing those ideas across the organization.
The result is a network of employees who are accelerating adoption and helping successful ideas spread across the organization.
Turning Innovation into Everyday Practice
One of the earliest lessons I learned through this initiative is that the most impactful AI applications are often surprisingly practical.
Technical Writer David Konečný helped identify opportunities to automate repetitive documentation activities that traditionally required significant manual effort. During a branding project, AI supported large-scale document updates while helping maintain consistency across hundreds of files. His team has also used AI to review extensive documentation sets and identify issues that might otherwise take days to uncover.
In software engineering, Marion Schmidt has helped teams integrate AI into everyday development workflows. Tasks such as code-generation, documentation generation, unit testing, code reviews, and understanding legacy code are becoming more efficient, allowing developers to spend more time solving complex technical challenges.
For Systems Engineering AI Champion Max Pittman, one of the most valuable applications has been using AI to navigate complex requirements and documentation. By helping engineers quickly understand how different teams structure information and manage requirements, AI is reducing barriers to collaboration and accelerating knowledge transfer across projects.
These examples are different on the surface, but they share a common outcome: Employees spend less time organizing information and more time solving problems.
Enabling Better Decisions
AI’s value extends beyond productivity.
In design assurance, Luis Alberto Ortiz Haro has been exploring how AI can help engineers evaluate increasingly complex technical and regulatory information more efficiently. By bringing relevant information together more quickly, AI creates a stronger starting point for analysis and decision-making.
At the same time, Luis consistently reinforces a principle that applies across every function: Human expertise remains essential.
AI can help us find information faster and identify patterns more efficiently, but it cannot replace the experience and accountability required to develop medical technologies safely and effectively.
The same philosophy guides our quality teams.
Sebastian Kratzsch and his colleagues have explored AI applications ranging from document migration and audit preparation to training management and root-cause analysis. Their goal is not to automate decision-making. Their goal is to eliminate manual effort so employees can dedicate more time to evaluation and continuous improvement.
Across every application, AI provides a stronger starting point, while employees provide the judgment needed to turn insight into action.
The Power of Shared Learning
While the technology itself continues advancing at an incredible pace, one of the most valuable outcomes of the AI Champion program has been the collaboration it has created across functions.
Champions regularly share use cases, demonstrate tools, discuss lessons learned, and exchange ideas that can be adapted to other parts of the business. A solution developed in one function often sparks innovation in another.
I’ve watched employees who initially joined the initiative to learn about AI become active contributors, helping colleagues discover new possibilities within their own work.
That exchange creates a multiplier effect, allowing teams to build on proven approaches rather than starting from scratch.
For me, that collaborative mindset is where the greatest value exists.
Looking Ahead
AI continues to evolve rapidly, and the capabilities available today are dramatically different from what we had even a year ago.
Despite that pace of change, I believe the key to success remains simple.
The organizations that benefit most from AI will not be those that simply adopt new tools. They will be the ones that empower employees to experiment and solve meaningful challenges.
That is exactly what I see happening across Advanced Surgery.
Our AI Champions are helping transform AI from a technology discussion into a business capability. By combining artificial intelligence with deep domain expertise and practical problem-solving, they are creating new opportunities to improve how we work and deliver value.
As successful approaches spread across functions, individual ideas become shared capabilities that strengthen the organization as a whole.
The technology matters, but it is the people who apply it to real challenges that drive transformation.
By Moritz Böttger, AI Technology Lead