Data First, AI Next: How to Build the Future of Test

Test and measurement exists because of the need for certainty. Business results (and often lives) depend on engineers being absolutely sure components and products will reliably perform the way they’re intended.

Yet today, the only real certainties about the role of artificial intelligence (AI) in test & measurement are that it is transformative and that it will continually evolve. So, it’s not surprising the topic generates more questions than answers within organizations: What’s coming next? What about five years out? Should we invest now? If not, when? How much will that cost? Which model should we use? What will we do with it? How will we protect our IP??

This “analysis paralysis” can keep companies from taking any action until they’re sure they’re making the “right” decision. But that certainty may remain elusive, and by waiting to act, the “right” decision might come years too late, causing companies to miss opportunities, dulling their competitive edge, and putting them that much further behind.

The good news is every organization can—and should—take some essential, concrete steps right now that don’t require a massive investment and will set them up for success wherever they are on the AI adoption timeline.

Get Your Data Ready

Effective and meaningful adoption of AI within the test and measurement industry will always demand a coherent, strategic approach to managing immense volume of test data. Historically, this treasure trove has been discarded or underutilized as an operational byproduct rather than a strategic asset.?

For organizations to take full advantage of AI, they must have an intentional, structured strategy for ensuring that extensive amounts of AI-ready data will be accessible and meaningful. Disciplined collection, consistent schemas, and organized storage allow the abundance of raw information to be transformed into well-structured datasets—the fuel that drives effective AI and more meaningful insights.

In addition, standardizing and cataloging detailed metadata—such as test conditions, equipment specifics, environmental contexts, measurement parameters, etc.—creates rich context that amplifies the value of the data and enables AI to identify deeper patterns and correlations.?

Breaking down data silos, standardizing formats, and implementing clear governance policies for data stewardship ensure data integrity, security, and long-term accessibility. While structured data frameworks improve how information is managed and utilized, protecting that data requires clear policies and commitments. At Emerson T&M, we follow a simple principle: your data remains your data. We do not use customer data to train our AI models, and our customers have control over where and how their data is stored.?

In a recent interview, Emerson T&M CTO Kevin Schulz related his experience talking to multiple companies about AI. “They're excited about AI. Then, when we talk about their data, we see that their data is not ready for AI. I can say that’s step one: get your data in order.”?

By implementing an effective data management strategy now, companies can position themselves to quickly adopt and take advantage of AI advancements as they emerge.?

Get a Good Navigator

Whether the focus is an AI data strategy tune-up or a major AI implementation, applying artificial intelligence to test and measurement requires specialized knowledge of both AI and the intricacies of testing technologies and processes.?

Engaging a partner with that kind of dual expertise is crucial so engineers can continue tackling high-stakes challenges, rather than puzzling over how to shoehorn powerful but generic, AI models into sensitive test environments and specialized workflows. The right partner will understand specific testing needs and tools, and provide priceless guidance when evaluating and differentiating between beneficial AI technologies and those that will be impractical for your application.?

Says Taylor Riché, Ph.D., Director of Technology and Innovation Software at Emerson T&M, “Off-the-shelf AI models are evolving at an impressive rate, but they aren’t built with test and measurement in mind. That’s where Emerson T&M comes in. As experts in test and measurement, we take these powerful models and augment them with our deep industry knowledge and experience to create solutions that truly serve our customers. Our goal is to enable engineers to focus on advancing their increasingly complex products while we handle the testing challenges that come with those advances."

Today, Emerson T&M is applying this same innovative approach to AI. By combining modern, general-purpose technology trends with deep domain expertise, Emerson T&M is leading the way in creating intelligent solutions designed for the unique needs of the test and measurement industry. In addition, their ecosystem of open and modular NI hardware and software enables companies to integrate these solutions with agility and precision, customized to their specific requirements.

Get On the Road to an AI-Enabled Future

Artificial intelligence is already rapidly changing the face of test and measurement. And it will continue accelerating, with capabilities beyond what we can imagine today. Get ready for what’s next by creating an AI-ready data strategy and engaging a trusted partner with the specific tools and expertise to turn complexity into opportunity, provide clarity, and deliver a strategic advantage in AI adoption.?

Join us April 28-30, at NI Connect 2025 in Fort Worth to experience firsthand the exciting advancements ahead of us as we shape the future of test and measurement.