Your Weekly Industrial Intelligence: AI, Data/3D, Reality Capture, Digital Twins & Spatial Computing
April 2, 2026: Issue 2
AI isn’t a magic wand, it’s more like espresso: it won’t fix a mess, but it’ll supercharge whatever you’ve already got brewing. Get your data clean, your processes tight, and your people sharp. Then AI turns “meh” operations into “more please” performance. ☕
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What’s Inside:
🚧 How Marathon Petroleum Uses Data and AI to Improve Safety & Reliability
😱 Smartglasses At Work: Productivity Dream Or Privacy Nightmare?
💡 AI-First Utilities: Defining the Future of the Grid in 2026
💰 The $10:1 ROI: Why Autonomous ERP Agents are the New O&G Gold Standard
📝 From Hype to Hard Results: Making XR Actually Useful at Work
↗️ Scan to BIM 2026: Leveling Up with AI-Powered Digital Twins
WHAT'S BIG
Marathon Petroleum: AI Isn’t the Strategy. It’s the Multiplier
(Image Credit: Enki)
If AI were a magic wand, every refinery would run perfectly and every dashboard would be optimized the first time.
Alas, reality insists on something less glamorous:
Good data
Clear processes
People who know what they’re doing
That’s the refreshingly practical message from Marathon Petroleum’s Chief Digital Officer, Ehren Powell, in a recent Technovation podcast. His take? He told Peter High, Metis Strategy President, that AI isn’t the strategy—it’s the multiplier. And like any multiplier, it only works if there’s something solid underneath it.
Step One: Fix the Foundation Before Buying the AI
Before scaling AI across 13 refineries, Marathon focused on organizing and connecting its data to make sure disparate sources come together into a coherent picture of how equipment actually behaves.
Because raw data is like a box of puzzle pieces. Useful, but only after you figure out how they fit together.
Once the data foundation was in place, Marathon could use AI to do what it does best:
Spot patterns humans might miss
Flag problems before they turn into downtime or safety incidents
Reliability = Safety
In industrial operations, reliability requires keeping production running as well as keeping people safe.
Predictive maintenance helps teams fix issues before equipment fails unexpectedly. That means fewer emergency repairs, fewer risky interventions, and a much calmer night shift.
It’s the difference between planned maintenance and scrambling during a crisis.
The Skills Transformation
One of the more interesting shifts Marathon is making has nothing to do with technology. It’s focused on people.
The company is moving from job-based roles to skills-based teams where employees continuously build capabilities in data, analytics, and process design—skills that help them make the best use of AI.
All This to Say
Companies getting the most value from AI are the ones doing hard, foundational work first—cleaning up data, redesigning processes, and building teams that can adapt. From there, progress can multiply.
This all makes AI sound a bit like coffee. It’s not the strategy, but it can definitely be a multiplier.
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WHAT'S UP
Autopilot Mode Activated: AI in ERP is leveling up from “hey, here’s a dashboard” to “don’t worry, I already handled it,” with autonomous agents making multi-step decisions that cut downtime and slash maintenance costs. The catch? You need tight governance and modern, connected systems, because when AI starts running the playbook, everything better be audit-ready and working in sync.
Eye Spy Work: Smartglasses promise a hands-free productivity boost at work, but they’re also raising eyebrows as employees worry about being secretly recorded or monitored. As the tech goes mainstream, companies are stuck walking a tightrope between embracing innovation and setting clear rules to protect privacy.
Power Upgraded: Power and utility companies have a rare shot to reinvent themselves with AI, but the real winners won’t just bolt it on, they’ll rewire the entire business around it. The playbook is simple: start fast, go deep across core operations, then leap ahead with AI-first systems that run smarter grids and create next-gen customer experiences.
WHAT'S NEXT
XR is graduating from flashy demos to real work, as companies like Lenovo and Arthur focus on practical use cases like training, collaboration, and digital twins that save time and money. By combining AI with immersive workflows, they’re turning XR into something businesses can actually deploy, measure, and rely on, not just experiment with.
Scan to BIM turns laser-scanned data into accurate 3D models, helping teams collaborate on digital twins for renovations, retrofits, and smarter construction decisions. Companies like ScanToBIMOnline are using AI to deliver fast, high-accuracy models at scale, making as-built documentation quicker, more precise, and easier to act on.
Smart Spatial is deploying enterprise digital twins that turn complex products and infrastructure into interactive, real-time 3D environments for visualization, simulation, and operations. Built on platforms like Unreal Engine and NVIDIA Omniverse, these solutions help organizations move beyond static models to actively test, train, and operate using dynamic digital assets.
Google showcased something that could redefine how we think about language barriers: Android XR glasses with real-time voice translation that preserves the speaker's original voice. Google is adapting technology from the Pixel 10 series to create conversational experiences that feel remarkably human, even through AI mediation.
WHAT'S THE DEAL
Deeplify, a Bochum-based industrial AI startup, announced that it has raised €2 million in a pre-Seed round to modernise how critical infrastructure is inspected and managed.
Autodesk just dropped $200M into World Labs, betting big on physical AI and 3D model generation in its largest startup investment ever. The move pushes World Labs past $1B raised and signals that real-world, construction-ready AI is where serious money is flowing next.
WHAT ELSE
The Rise of the Bot Boss: Would You Work for an Algorithm?
Would you trade your manager for a chatbot? A growing number of Americans are saying yes.
According to a Quinnipiac University poll published Monday, 15% of Americans say they’d be willing to have a job where their direct supervisor was an AI program that assigned tasks and set schedules. Quinnipiac surveyed 1,397 adults in the United States and conducted the poll — which included questions about AI adoption, trust, and job fears — between March 19 and 23, 2026.
Of course, the majority of respondents said they wouldn’t be willing to swap their human boss for an AI people manager. But the use of AI as a supervisor is gaining in popularity, even if one isn’t directly in charge of steering entire teams of people.
Companies like Workday have launched AI agents that can file and approve expense reports on employees’ behalf. Amazon has deployed new AI workflows to replace some of the responsibilities of middle management, laying off thousands of managers in the process.
Engineers at Uber even built an AI model of CEO Dara Khosrowshahi to field pitches before meetings with their actual boss. Read more! --> (h/t TechCrunch)
