A Digital Enterprise Deep Dive with Jim Brown – Part 3 – Summary
On the Industry Forward Podcast, we recently wrapped up a three-part discussion on Digital Enterprise trends and technologies with Jim Brown, President of Digital Transformation Research for Tech-Clarity. In the final part of our discussion with Jim, the conversation turned to focus on the Industrial Metaverse as a culmination of the Digital Twin, AI, and digitalization. We also discussed how companies can start their digital transformation journeys before ending with some final thoughts from Dale and Jim.
We started with a discussion on the emergence of the Industrial Metaverse as a transformative concept in industry. Blending physics-based digital twins, artificial intelligence (AI), and immersive platforms, the Industrial Metaverse creates a connected, data-rich environment for manufacturing and operations.
As Jim noted, the Industrial Metaverse is not a sudden leap but “a natural progression of what we’ve been doing in the industry for the last 30 years.” It represents the culmination of digital twin technology, AI-driven insights, and integrated data environments. Companies that embrace this evolution can unlock new levels of efficiency, collaboration, and innovation.
However, the journey is not without challenges. Cultural resistance remains a factor, particularly around immersive technologies. “I’m one of those unfortunate people that get AR sick,” Brown admitted, highlighting that while hardware has improved, comfort and usability on the plant floor are still concerns. Beyond human factors, data integration poses a significant hurdle. Many organizations operate in brownfield environments with fragmented systems, legacy models, and even paper-based processes. Aggregating this data into a unified, actionable format is critical for success.
Industrial Metaverse Delivers Business Value to Digital Enterprise
One misconception persists: that the Industrial Metaverse is primarily about visualization. While visualization is part of the equation, the real value lies in aggregating and contextualizing data to drive business outcomes. “It’s not just doing it for the sake of doing it,” Tutt emphasized. “It’s the sake of having something that’s providing business value.”
This focus on value over novelty is essential. Companies should prioritize use cases that solve real pain points—whether improving design-for-manufacturing, optimizing plant layouts, or enhancing maintenance workflows. By embracing physics-based simulation and modelling and applying robust data governance, organizations can build a foundation for AI-driven insights that accelerate decision-making and reduce costs.
Interestingly, some of the most impactful technologies enabling the Industrial Metaverse have roots outside traditional manufacturing. Gaming engines, for example, have advanced physics modeling and 3D rendering capabilities, making them ideal for industrial applications. “I’ve got great respect for the gaming industry for making 3D so much more ubiquitous,” Brown said.
Reality capture technologies such as LIDAR also play a pivotal role, especially in environments where as-built conditions differ from original designs. Tutt shared a compelling example from aerospace: a veteran technician revealed that a part had been manually trimmed for decades due to a design clash that was never updated in engineering documentation. Capturing these discrepancies with LIDAR or AI-powered vision systems can prevent costly errors and streamline future projects.
Robotics adds another layer of opportunity. Brown pointed out that industrial robots equipped with advanced vision systems can autonomously scan facilities, creating high-fidelity models that surpass traditional methods. Combined with AI, these systems can interpret complex environments, tag assets, and link them to maintenance data—delivering actionable insights at scale.
Journey to the Digital Enterprise and ROI
Ultimately, the Industrial Metaverse aligns with broader digital transformation goals: managing complexity, accelerating product development, and improving supply chain resilience. Companies that embrace this roadmap are already seeing returns, particularly from AI initiatives. “Some of the data and analytics and AI initiatives are providing value much faster than traditional investments,” Brown observed.
For organizations starting this journey, Tutt offered practical advice: “Find your pain points and then find things that help solve those pain points. While you’re doing that, you’re putting yourself on a roadmap towards digital transformation.” This incremental approach ensures that investments deliver measurable business value while building toward a comprehensive Digital Twin and, eventually, the Industrial Metaverse.
