By Jagadish Gattu, CEO of UptimeAI
This article originally appeared on LinkedIn.
The number 1 takeaway from Verdantix 2025 Industrial Asset Management Council reflects something we hear from our customers every week:
Industrial agility—the ability to rapidly adapt operations, processes and workforce focus—is becoming increasingly important, and the best way to improve industrial agility is to close the gap between insight and execution.
Industrial agility isn’t hindered by visibility; it’s a velocity issue. More precisely, it’s limited by the ability to turn an insight into a decision, and a decision into an action before the optimal moment passes.
Decades old challenges with a new urgency
The council members discussion highlighted tensions that will sound familiar to anyone running asset-intensive operations: balancing quality standards against delivery commitments, managing aging assets against cost pressure, maintaining continuous runtime in markets that keep getting less predictable. These aren’t new challenges, but with a slew of external factors complicating margin equations, there’s a new urgency.
Historically, the workflows around industrial agility have been software initiated but human bottlenecked. Industrial companies have the data necessary to solve most problems. Many of our customers even have existing software to detect when operating conditions have shifted. But then those detected events await human expert interpretation before a decision is made, and an action initiated.
Decision latency is introduced when software detects an issue, but then it takes days or weeks of human response time to act on the insight. Decision latency is the killer of industrial agility.
This decision latency created when you have an overabundance of software that detects and an underabundance of human experts that decide is why we built UptimeAI, and why this finding hits close to home.
Early industrial AI tools created an insight-to-action gap
The first wave of industrial AI solutions focused largely on prediction.
- Can we detect an anomaly earlier?
- Can we forecast a failure before it occurs?
Those capabilities are genuinely valuable, and they’ve become increasingly valuable as they’ve matured over the past several years. But prediction alone doesn’t close the insight-to-action gap. A flagged anomaly that doesn’t result in an automated, accurate diagnosis, and mitigation hasn’t actually moved the needle. It just adds another alert to a queue that a human still needs to reason through manually.
The next generation of industrial AI presents organizations with the opportunity to no longer stop at the alert. AI Reasoning systems can help answer the harder questions:
- Why is this happening?
- What are the tradeoffs?
- What should we actually do next… Given everything we know about this asset, this site, and this moment?
The Verdantix report notes that AI-driven planning tools have already reduced planning cycle times by 30 to 40 percent in real deployments. For UptimeAI customers, applying AI reasoning agents to close the decision gap in some of their most expert-intensive operations challenges has grown EBITDA margins by an average of 2-5%.
Operational agility meets human resiliency
In addition to the initial margin uplift realized when the insight-to-execution gap tightens, there are also some decidedly human benefits. When people aren’t buried in alert triage and manual data reconciliation, they think differently. They have space to use their judgment, to dig into their hunches. They start asking better questions, catch patterns earlier, and make the kinds of calls that only come from experience, and over time, they make them faster. And the AI learning from them gets smarter as a result.
Operational resilience goes beyond building a better dashboard. It’s also about cultivating a team that’s operating at a higher level because the noise has been cleared out of their way.
Make better decisions, faster, with the team you’ve got
The Verdantix findings confirm what we’re seeing in our customers throughout the asset-intensive industries. The urgency is real, because the opportunity is real. And the organizations that close this gap first won’t just perform better today. They’re building a moat of competitive advantage that will make them structurally harder to catch for years to come.
