From a macro level, the oil and gas industry is made up of just a few primary business processes, from exploring for and extracting hydrocarbons to asset management, midstream, and downstream operations. But as any energy professional can attest, that barely scratches the surface of what the real work looks like day to day. In fact, the American Process and Quality Center (APQC) lists nearly 1,800 distinct processes in its Process Classification Frameworks for upstream and downstream. Adding immeasurable complexity, every energy company’s business processes are unique to their operations.
As with most other industries seeking to unlock the game-changing performance of AI, energy companies are struggling to fully realize its potential. Many teams are stuck in a rut, searching for the right business processes to automate and enhance. Yet the most valuable AI use cases aren’t always the most obvious, making it essential to identify those workflows where AI can deliver the greatest value at scale. And with hundreds of processes to evaluate, energy companies are left hunting for a needle in a haystack at a time when operational and cost efficiency are more urgent than ever.
In the first blog in this series, we explored why building a solid data foundation is the key to any successful AI program. Now, let’s go a level deeper by exploring how your team can pinpoint exactly where AI can actually move the needle in your organization.
At Stonebridge Consulting, we believe the best AI strategies don’t start with the shiny tools. The most impactful approach starts with the work. When we partner with clients, we don’t call it an assessment. Instead, we sit side by side with operations, land, production, and supply chain teams to uncover the business processes that eat up time, require too many people, or rely on constant manual intervention.
This is where Stonebridge’s vast experience in data management, oil and gas business processes, and AI adds tremendous firepower. By mapping these workflows, we create a cross-departmental view of how information moves (or doesn’t move) through the enterprise. That’s where you start to see the real opportunities for AI to step in, not to replace people, but to amplify their work so they can focus on higher-value decisions.
Stonebridge’s approach to AI strategy is rooted in practicality. We connect AI and digital readiness with real business priorities, delivering a clear readout of where automation and intelligence can deliver measurable impact. The results often surprise clients: a land data reconciliation that once took weeks drops to hours, or a production variance analysis that used to require three spreadsheets now happens in real time.
We’re not interested in pilots that never scale. Our advisors combine deep energy expertise with the technical delivery skills to build and integrate the AI tools we recommend. That means you’re not just getting strategy, you’re getting working solutions that evolve with your data foundation.
In the next and final post of this series, we’ll explore how Stonebridge’s EnerHub platform turns that foundation into a living system, one that connects your corporate knowledge, enforces master data, and ensures every AI model you build is wired for maximum success.
Contact Stonebridge today to start your journey toward a strong, AI-ready data foundation.