Industrial AI’s Next Phase: Proof Before Scale | SPONSORED
At Infinite Uptime’s CXO Circle in Bangkok, the discussion around industrial AI felt different. The room was filled with people who run plants. They weren’t asking whether AI belongs in manufacturing anymore. They were asking how to make it work reliably, across complex environments where every process, every asset, and every operator matters.
The consensus was straightforward: AI earns its place on the factory floor only when it proves value, not when it promises it.
From Belief to Proof
As Kalyan Meduri, Global VP of Marketing and Partnerships at Infinite Uptime, explained in our follow-up conversation, the first step isn’t technology — it’s validation.
“Everything we build starts with the user at the center,” he said. “Every KPI — whether it’s energy efficiency, maintenance reduction, or throughput — has to translate into measurable progress.”
That’s the thinking behind Infinite Uptime’s Show and Grow approach. Instead of focusing on how fast adoption spreads, the company focuses on how much value users actually see.
In the last quarter alone, their AI-driven maintenance platform generated 4,186 actionable prescriptions. Operators acted on 4,096 of them, a 95% execution rate, with 99.97% accuracy. Those numbers tell a simple story: when people trust the output, they use it.
A Pragmatic Approach to Digital Transformation
Unlike many digital projects that start with sweeping goals, Infinite Uptime starts with baselines and benchmarks. Teams first define what success looks like — improved mean time between failures, lower energy consumption, or throughput increases — then track progress week by week.
Meduri calls it “show and grow” because value must be shown continuously. “Every week, every month, every quarter, our goal is to demonstrate measurable improvement,” he said. “When users see results, adoption takes care of itself.”
This approach stands in contrast to the “land and expand” model that prioritizes speed of rollout over sustained performance. The difference is subtle but significant: Show and Grow builds confidence before scale.
When Data Quality Defines Trust
Good AI starts with good data — a point Meduri emphasized repeatedly. Infinite Uptime’s newest innovation, a miniature piezoelectric sensor, measures vibration, temperature, and RPM in a single compact unit.
In heavy industries such as mining and metals, where conditions are harsh and equipment runs continuously, battery-powered sensors often fail or go offline. This new design eliminates that weakness and provides uninterrupted, high-fidelity data.
“The quality of insight depends on the quality of input,” Meduri noted. “If the data stream is incomplete or inconsistent, even the best models can misfire. You can’t build trust on unreliable data.”
Transparency as a Differentiator
Manufacturers often ask whether AI recommendations can be trusted. Infinite Uptime’s answer is to make results transparent. Plants can benchmark their own performance against global data from other installations, seeing exactly how their assets perform in context.
That visibility changes the conversation — from questioning the model to understanding what the data means.
Industrial AI’s Maturity Test
The Bangkok discussions and Meduri’s insights point to a quiet shift in industrial AI. The focus is no longer on proving that AI can work in plants. It’s on proving that it works consistently — across assets, environments, and teams.
The manufacturers succeeding today share the same habits:
- They start small and expand only after results are proven.
- They measure progress in real operational KPIs.
- They build transparency into every layer of data.
- They see AI not as a disruption, but as validation.
Industrial AI’s next phase will be driven by proof — proof that turns pilots into production, and skepticism into trust.
This article was written based on a video interview with Kalyan Meduri, Global VP of Marketing & Partnerships at Infinite Uptime.
Sponsored by Infinite Uptime.
About the author
Lucian Fogoros is the Co-founder of IIoT World.
