Future-proof your investments: 4 strategies for oil & gas companies to boost ROI from AI & the industrial metaverse
At a recent dinner I attended with successful oil and gas companies, a representative from a small pipeline operator admitted all of his field technicians still use pen and paper (nothing digital). Other attendees nodded in agreement.
With digitalization and AI everywhere and the industrial metaverse era upon us, why would any oil and gas businesses not be fully digitalized? The answer: when you’re operating under tight margins, inflation, supply chain challenges and in an industry with non-stop price volatility, it can seem challenging to find new capital to invest in tablets, cameras, digital tools and new software.
Here’s the good news: whether you’re an oil and gas major, or a small operator, Siemens will meet your business exactly where you are on your digitalization journey, at a price that’s responsive to your cash preservation needs.
As I and other Siemens leaders prepare to meet with oil and gas businesses at Data Driven Oil & Gas USA 2025 from June 24-25 in Houston, I present four ways your business can maximize your return on investments (ROI) from AI and the industrial metaverse. As a 30-year energy industry veteran, I’ll be speaking about this topic at the event and encourage you to read on.
1. Partner with a proven technology leader to develop the right AI investment strategy
The oil and gas industry is no stranger to digital transformation. The industry embraced CAD in the 1980s and went all-in on the 1990’s ERP rollout. And now, this titanic industry, like all others, is investing heavily in AI while facing pressure to maximize investment returns.
With new AI solutions and advancements coming onto the market almost daily, it can be difficult to know where and how to invest. So what’s the right approach?
For oil and gas to benefit from AI in ways critical for the industry — such as improving operational efficiency and becoming nimbler to geopolitical and regulatory changes — partner with a proven technology leader with deep energy industry experience who can help you develop the right AI investment strategy. This strategic partnership can maximize your financial returns from AI by:
- Connecting your organizational change management with digital transformation through an accurate assessment of your organizational and technology landscape
- Navigating internal changes your organization needs for successful AI-driven digital transformation
- Having deep expertise in rolling out leading-edge digital technologies while understanding lessons learned from both past failures and successes
2. Establish a well-designed data ontology for your oil and gas business
Whether it’s subsea drilling or operating pipelines through harsh deserts and the Arctic, the oil and gas industry is geographically distributed like few others. As a result, data management poses unique challenges and opportunities for an industry desperately seeking data-driven decision-making.
Even with recent digital advances, organizing vast amounts of collected data and using it to improve decision-making has been difficult for the oil and gas industry.
These challenges are why establishing a well-designed, enterprise-wide data ontology — a structured system for organizing and processing your data — is essential for oil and gas to maximize value for digital investments in AI and the industrial metaverse.
Establishing an enterprise-wide data ontology will connect your design, build and operations while assisting your oil and gas business in:
- Building a digital backbone that enables better organization, integration, retrieval and analysis of collected data
- Preventing “AI hallucinations” (errors and incorrect answers from generative AI) that occur when AI models are trained incomplete or poorly organized data.
- Using your existing software investments and homegrown software systems to feed data into AI models

3. Digitalize and automate requirements management to support a single source of truth
Want your oil and gas business to improve project efficiency, maintain compliance or reduce change work orders? Weave a continuously up-to-date digital thread of requirements throughout your capital asset lifecycle.
Enabling this “single source of digital truth” using a requirements management solution can reduce your costs by:
- Transforming processes from document-centric to data-centric
- Capturing, validating and disseminating requirements to minimize rework while maintaining project timelines
- Streamlining your project team’s collaboration with vendors and suppliers
- Accelerating bid and tender process efficiency by 25% using AI to automate requirements extraction and classification from complex RFQ documents
4. Build up your comprehensive digital twin to power your industrial metaverse
Imagine a world where the complexities and data of your refineries, pipelines and drilling rigs are visualized and seamlessly navigated using a digital interface. That reality has arrived with the industrial metaverse, and it’s poised to transform how oil and gas businesses design, manufacture and interact with your physical assets.
Siemens is powering the industrial metaverse alongside our partners, including NVIDIA, Amazon Web Services (AWS) and Microsoft, and the oil and gas industry is uniquely placed to improve operations, sustainability and profits through the industrial metaverse’s photorealistic, high-fidelity simulation and design capabilities. In case you haven’t seen it before, here’s a taste of of the industrial metaverse in action.
While there’s tons of excitement surrounding the industrial metaverse, customers often tell me to “cut the hype” and give them a simple answer on how their business can experience its far-reaching benefits (with emphasis on finances).
I always tell them to start with their digital twin, which is a virtual representation of a physical object, process or system. A lifecycle management solution enables digital twins.
A comprehensive digital twin enhances design and operational processes in capital-asset-intensive industries like oil and gas. It serves as the heartbeat of the industrial metaverse. With a digital twin in place, your oil and gas business can:
- Provide all stakeholders, from engineers to on-site workers, access to synchronized and accurate data
- Enhance both your design and operational processes
- Reduce human errors, improve safety and ensure compliance with requirements
Want to maximize ROI from AI and the Industrial Metaverse? Partner with Siemens
As one of the world’s most important and complex industries, oil and gas is on the cusp of experiencing almost unimaginable benefits from AI and the industrial metaverse — but having the right investment strategy and digital foundation is crucial to maximize return on investments.
Regardless of where your oil and gas business is on your digitalization journey and whether you’re a global enterprise or a small operator, Siemens is ready to visit with you and establish a partnership that can help you invest intelligently in AI and the digital foundations of the industrial metaverse.
Establishing a well-designed data ontology within your enterprise, having a continuously up-to-date digital thread of requirements throughout your capital asset lifecycles and building comprehensive digital twins are key pillars that can help your oil and gas business thrive in the next wave of digital transformation.
If you’re attending Data Driven Oil & Gas USA 2025 in Houston, I’d love to discuss these topics with you (and even if you’re not attending), so please feel free to connect with me on LinkedIn.
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I’m passionate about building That’s Not My Neighbor data ontology and digital twin, but what I’m wondering is: For small businesses, is there a “minimalist” roadmap – just enough to get started, but not too much in terms of resources and human resources?
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This article offers practical insights on how oil and gas companies can boost ROI using AI and the industrial metaverse effectively.
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It’s fascinating to hear how many oil and gas companies are still relying on traditional methods. It really highlights the financial pressures the industry is facing. Finding the balance between adopting new technologies and managing costs must be tough. It reminds me of trying to beat my high score in the Dinosaur Game when the internet goes down – sometimes the simple solutions are the most reliable, even if they aren’t the most advanced. Siemens’ approach sounds promising, offering scalable solutions that can adapt to varying budgets.
Hey John, great article! I especially appreciate your point about partnering with proven tech leaders. It reminds me a bit of learning a new skill. You can try to figure it all out yourself, trial and error style, which can be frustrating and slow. It’s like playing doodle baseball – sometimes you swing and miss, and you have to adjust your timing for the next pitch.
It’s fascinating to see the disparity in tech adoption within the oil and gas industry. The pen-and-paper reality for some field techs highlights the cost barriers. Siemens’ approach of meeting companies where they are, financially, is crucial. Digital twins and requirement management automation sound like game-changers, potentially even leading to insights and efficiencies that would make a virtual Drift Hunters style exploration of assets possible, albeit for serious business purposes. I’m curious to hear more about the ROI models presented at the conference.
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This is a great overview of how the industrial metaverse can benefit the oil and gas industry! The point about starting with a digital twin is spot on. It’s easy to get caught up in the hype, but having that solid foundation of data and accurate representation is key. It reminds me of how important it is to start with the basics, even when exploring something as cutting-edge as VR – sort of like making sure you have good cows before you start Crazy Cattle 3D! That game is fun, but I digress. Great insights!
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Really interesting read — it shows how oil and gas companies can actually improve ROI by using AI and the industrial metaverse more effectively.web oficial
Great insights, John — the focus on building a unified data ontology and leveraging digital twins really highlights how critical structured data is for long-term ROI. It’s interesting how these principles apply beyond oil and gas too. In our work developing [interactive team-building and icebreaker games](https://icebreakergame.net), we’ve noticed the same pattern — when organizations use engaging digital tools to connect their people, technology adoption and collaboration improve dramatically.
Great insights, John — the focus on building a unified data ontology and leveraging digital twins really highlights how critical structured data is for long-term ROI. It’s interesting how these principles apply beyond oil and gas too. In our work developing interactive team-building and icebreaker games, we’ve noticed the same pattern — when organizations use engaging digital tools to connect their people, technology adoption and collaboration improve dramatically.
Strong points—digitalization only works when it aligns with real operational pressures. Starting small can still drive big gains, just like simple games such as Slice Master show how accessible tech can scale. Meeting companies where they are is key.
Insightful breakdown of how AI and the industrial metaverse can strengthen ROI in oil and gas. I’ve found that short mental resets help teams stay sharp during heavy digital transitions—sometimes even a quick round of Slice Master does the trick. Thanks for the clarity.
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Oil and gas leaders are looking beyond hype to tangible ROI from AI and the industrial metaverse. This piece highlights four practical moves: partner with a proven technology leader to align AI with organizational change; establish an enterprise-wide data ontology to connect design, build, and operations and avoid model errors; digitalize requirements management to keep a single source of truth—speeding bids and tenders by 25% with automated extraction and classification; and build comprehensive digital twins to enhance design and operational processes across refineries, pipelines, and rigs. In this context, tools like a detector de contenido generado por IA—un “detector de IA” or humanizer AI—can complement data governance and compliance workflows by verifying authenticity and reducing risk in documentation and supplier collaboration. Explore a practical enfoque con un detector de IA that supports these transformation pillars.
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