One question has guided much of our work on artificial intelligence:
How can we use AI to make it easier for customers to do business with us?
For our robotics and automation business, that question led us to tackle a significant challenge.
Our product portfolio includes more than 70,000 SKUs and millions of potential configurations. Finding the right solution requires a deep understanding of product specifications, application requirements, and compatibility across a broad range of options. Historically, customers relied heavily on our application engineering teams to navigate that complexity.
While that expertise remains one of our greatest strengths, we recognized an opportunity to make it available anytime, anywhere.
Capturing Decades of Knowledge
What makes this solution unique is that it is built on decades of accumulated engineering expertise. Across our business, application engineers, product managers, and technical specialists have developed a deep understanding of how to match customer requirements with the best possible solution. The challenge was never creating that expertise. The challenge was making it accessible at scale.
Much of this knowledge existed in the experience and judgment of employees who had been solving customer problems for years. Our goal was to capture and scale that expertise without sacrificing the accuracy customers expect.
The challenge was never whether we had the expertise. We did. The challenge was making that expertise accessible at scale while maintaining the high level of accuracy and confidence customers expect.
The result is a virtual application engineer (AE) that helps customers quickly identify the right product for their needs through a self-service experience.
Solving More Than a Technology Challenge
This was not an easy challenge.
When millions of possible product combinations exist, there are often many ways to solve a customer problem, but only one optimal solution. Replicating that decision-making process required more than product data. It required capturing the practical knowledge our experts apply every day when helping customers make critical decisions.
Success required close collaboration between technology specialists and our application engineers. Throughout development, employees tested the configurator using real customer inquiries, validated recommendations, identified gaps, and helped refine the system’s performance.
This human feedback loop proved to be one of the most important ingredients for success. The team needed to tap into the brains of very intelligent people that have been doing this for a long time. Their expertise helped transform a promising technology into a tool customers can trust.
Where AI Creates Real Value
The experience reinforced an important lesson about AI.
Technology alone is not the answer.
The real value comes from combining AI capabilities with deep human expertise.
Customers gain faster access to answers. Our engineering teams can focus on more complex challenges. The result is not a replacement for our engineers. Instead, it extends their reach. Customers can access expert guidance around the clock, while our technical teams can dedicate more time to solving complex application challenges and supporting innovation.
Preserving Knowledge for the Future
The project also reinforced an important business reality. Some of an organization’s most valuable assets are the knowledge and experience of its people.
By capturing and structuring that expertise, we are helping preserve decades of institutional knowledge while making it more accessible to customers around the world.
This is about more than solving today’s customer challenges. It is about ensuring the knowledge our employees have built over decades continues creating value for years to come.
Innovation That Matters
I am also proud of what this project represents from an innovation standpoint.
Many organizations are experimenting with AI. Far fewer are successfully deploying solutions that create measurable business value. This project demonstrates a practical application of AI that improves customer access to expertise, increases efficiency, and creates a foundation for future growth.
The ultimate measure of success is not the technology itself. It is the value we create for customers.
This virtual application engineer is more than a new tool. It is an example of how we are transforming decades of engineering knowledge into a digital experience that helps customers move faster and make more informed decisions, accessing our expertise whenever they need it.
We are delivering innovation that matters.
Read the full case study: Quick Consult | ReshapeX
By Ajaiey Sharma, Vice President & General Manager R&A