Like other sectors, the energy industry is reaching for the prize of generative and agentic AI. IT researcher IDC reports that “masters,” companies that have achieved maturity in data management and governance, have seen a 24% increase in revenue and a 25% cost reduction by scaling AI across their organizations. That’s quite a prize, but for most energy companies, the revenue growth and operational efficiency remain out of reach because of their data. In fact, Gartner predicts that 60% of AI projects will be abandoned by the end of 2026 due to a lack of AI-ready data.
AI projects have been and will continue to be abandoned not only because relevant data is unavailable or unreliable, but because organizations want to move beyond proofs of concept and AI pilots to proof of ROI. In the last blog in this series, we explored how Stonebridge pinpoints the right processes out of hundreds to turn energy workflows into AI wins. In the first blog, we presented the AI imperative and why the game-changing benefits of AI are urgently needed now. In this final installment, we’ll explore the technology simplifying and accelerating the AI-ready, ROI-enabling data foundation for some of the biggest names in energy.
Artificial intelligence is only as good as what it learns from. “Garbage in, garbage out” isn’t a cliché, it’s the governing law of every machine learning model ever built. Imagine teaching a geologist with a 19th-century map or coaching a petroleum engineer with lessons from Hollywood scripts. The results would be as off-target as training an AI on inconsistent or incomplete operational data.
Adding to the challenge, large language models suffer from ungrounded content, hallucinations that produce inaccurate or misleading responses from chatbots. The solution? Grounding content with retrieval-augmented generation (RAG), which restricts LLMs to energy-specific data sources and corporate knowledge. All of this requires on-demand access to the full breadth of your digital ecosystem and automated data quality assurance with people in the loop. Yet energy companies struggling with AI are also struggling to manage sprawling, disconnected ERP systems, energy applications, and project databases using underpowered tools never designed for the data management realities of this industry.
That’s the problem EnerHub was built to solve. Stonebridge designed EnerHub to create a strong data foundation that ensures data availability, validates integrity, and enforces standards, from well, completion, and meter master data management to land and high-volume accounting transactions. The same technology is now uniquely positioned to deliver the trustworthy, high-availability data required to power AI success at scale.
With more than 50 pre-built connectors to enterprise and energy systems like SAP, Quorum, Enertia, and Peloton, EnerHub unifies up to 70% of an energy company’s software ecosystem out of the box. Its drag-and-drop integration builder handles the rest, while 2,800 built-in business rules and quality checks ensure every data point is validated and standardized.
EnerHub can manage data in place within your energy systems of record or populate your data lake of choice with consistent, governed, high-fidelity data ready to feed AI models. Through a publish-and-subscribe architecture, it enforces golden records across departments, ensuring that every system speaks the same language, whether it’s land, production, or accounting.
With EnerHub continuously orchestrating AI data pipelines, models learn faster, predictions sharpen, and insights begin driving more profitable decisions, not just incremental KPI improvements.
Beyond technology, Stonebridge helps your team build impactful business strategies on the strength of your data foundation through our expertise in process mapping to identify high-value AI use cases. Our clients also rely on Stonebridge to help them navigate and harness the evolving AI ecosystem, including SAP Joule and UiPath robotic process automation.
To stay competitive today and meet tomorrow’s challenges head-on, energy companies that embrace AI as a continuous process, not a one-and-done project, will see the benefits compound over time. The AI revolution is happening now, and data management is the strategic competency that will determine who excels and who is left behind.
Contact Stonebridge today to start your journey toward a strong, AI-ready data foundation.