By Jagadish Gattu, CEO UptimeAI
This article appeared earlier on Jagadish Gattu’s Likedin profile.
A recent Verdantix global survey of more than 300 industrial transformation leaders offers a clear signal about where the industry is heading. Alongside familiar priorities like safety, uptime, and operational efficiency, one theme stands out: workforce retention, training, and productivity remain among the most pressing concerns for industrial organizations heading into 2026.
This is not surprising. Across asset-intensive industries, a structural shift is underway. Experienced operators and engineers are retiring faster than they can be replaced, while industrial environments are simultaneously becoming more interconnected, data-rich, and operationally complex. The result is a growing imbalance between the complexity organizations must manage, and the expertise available to manage it.
Source: 2026 Verdantix Global Corporate Survey
The Limits of the Traditional Response
Historically, the industry’s response has been linear: train more people, document more processes, and deploy more tools. Each of these approaches has value, but they share a common limitation: expertise doesn’t scale linearly. The more tools you have, the more experts you need. The ability to connect weak signals, contextual constraints, and real-world tradeoffs takes years to build, and deep operational intuition is accumulated through experience, not documentation.
This is one reason many digital initiatives plateau. They improve visibility, but don’t fundamentally scale judgment. Dashboards surface signals and analytics highlight anomalies, but the hardest part often remains unchanged: deciding what to do next.
Why This Moment Is Different
What makes this moment unique is that the expertise gap is widening at the same time technology is becoming more capable. The Verdantix research highlights two parallel realities: industrial companies are accelerating investment in digital transformation and AI, and they’re also facing a rapid loss of expertise that is preventing the successful scaling of those very initiatives.
Source: 2026 Verdantix Global Corporate Survey
This tension is reshaping how leaders think about transformation. The question is no longer just how to digitize operations; it’s increasingly how to scale the expertise required to digitize operations in a time when traditional expertise is rapidly declining.
From Digitizing Assets to Digitizing Expertise
The first wave of industrial digitalization focused heavily on assets: sensors, historians, condition monitoring, and predictive analytics. These technologies created unprecedented visibility into industrial systems, answering the questions of “What happened?”, “What’s happening?”, and “What will happen?” But visibility alone does not equal resilience, and the questions “Why did this happen?”, “What do I do about it?”, and “How do I keep this from happening again?” lingered.
The next phase of transformation will attempt to answer those lingering questions, and it’s likely to center on something more foundational: capturing and scaling operational knowledge. Instead of relying solely on recruiting and training pipelines, organizations are beginning to explore systems that can embed expert reasoning directly into workflows, helping teams make better decisions in real-time. This represents a meaningful shift in how AI is applied in industrial environments: not just as a predictive layer or a copilot for information retrieval, but as a reasoning layer that helps teams connect fragmented operational knowledge, evaluate competing constraints, and move faster from signal to decision.
Why This Matters for Industrial Leaders
For executives navigating the next phase of digital transformation, this shift carries important implications. First, workforce challenges are no longer just an HR issue. They are an operational resilience issue. Second, the value of AI will increasingly be measured not by the sophistication of models, but by their ability to influence real decisions on the ground. And third, organizations that find ways to scale expertise rather than simply automate tasks will likely build a structural advantage in operational performance and excellence.
The Bigger Opportunity Ahead
If the last decade of industrial innovation was about digitizing assets, we predict the next decade will be defined by digitizing expertise. This doesn’t mean replacing engineers or operators, it means amplifying them. The real opportunity ahead isn’t just smarter automation; it’s resilient operations powered by scalable expertise. As the Verdantix data suggests, the organizations that recognize this shift early will be better positioned to navigate the conflicting pressures of rising complexity and shrinking experienced talent pools.
The shift from digitizing assets to digitizing expertise is already underway. Let’s talk about what that means for your operations. [Connect with our team]