The artificial intelligence (AI) landscape has become saturated with vendors and conferences touting endless “use cases,” presenting AI as a plug-and-play solution for any organization. However, 1898 & Co., part of Burns & McDonnell, challenges this norm. They view AI not as a destination, but as a tool to solve specific problems. The first question isn’t what AI can do, but what problems need solving.
This approach starts with understanding the business challenge, working with domain specialists to define problems, constraints, and desired outcomes. Only then is the technological toolbelt reached, which may include AI, advanced analytics, automation, or machine learning. The solution is architected to scale responsibly, improving operational reliability.
Last year, a client asked for a list of AI use cases. Instead of providing a catalog, 1898 & Co. engaged with operators, asset managers, engineers, and data teams. They found real opportunities hidden in day-to-day operational pain points. The path forward wasn’t AI for its own sake, but using AI as the most effective tool to address specific data challenges.
This problem-first focus led to a highly targeted pilot that solved a core operational bottleneck: generating clean, complete, trustworthy asset data. The pilot grew into a $1.3 million implementation, accelerating the client’s asset data environment and improving O&M activities. The success revealed new opportunities where AI could reduce effort, mitigate risk, and address previously intractable challenges.
At 1898 & Co., AI is never the starting line or the product. It’s a mechanism for solving problems tied to safety, reliability, compliance, productivity, and cost. They approach AI the same way they approach engineering: by defining the problem, understanding the system, selecting the right tools, and proving value in controlled increments.
This news challenges the sector to rethink its approach to AI. Rather than chasing trends or showcasing technology, the focus should be on solving real problems. This shift could lead to more meaningful, measurable outcomes, and a more responsible, scalable use of AI in the energy sector. As Chris Wiles, AI solutions architect at 1898 & Co., puts it, “We’re not helping clients apply AI, we’re solving problems with the new and advanced tools increasingly populating our technological environment.”