The following blog is distilled from Enverus Intelligence® Research (EIR) publications.
As the upstream oil and gas sector faces mounting pressure from rising costs and dwindling Tier 1 inventory, the need for smarter, faster and more efficient development strategies has never been greater.¹ AI has been thrown into this mix and is already proving to be a transformative force that’s reshaping how operators evaluate acreage, plan development and optimize production. GenAI was a hot topic at this year’s EVOLVE Conference, where we heard from industry experts discussing “AI in Asset Development: Inventory Analytics and Activity Prediction” and more sessions with expert panelists weighing in on this new chapter for the industry.
From real-time data analysis to rapid prototyping of development scenarios, AI is no longer a futuristic concept—it’s a competitive necessity for oil and gas. Here are four key ways AI is revolutionizing acreage strategy for upstream operators.
- Accelerated Decision-Making
- Data-Driven Optimization at Scale
- Operational Efficiency and Automation
- Strategic Focus and Cultural Shift
1. Accelerated Decision-Making
Traditionally, evaluating inventory and development scenarios could take weeks or even months. However, AI is collapsing that timeline to hours.
Generative AI tools now allow engineers and planners to move from idea to prototype in a single afternoon. Instead of waiting on developers or data scientists, teams can interact directly with large language models to test hypotheses, simulate outcomes and iterate quickly. According to EIR, Devon Energy has embraced this approach, enabling rapid prototyping across thousands of wells.² This acceleration means operators can evaluate more scenarios, faster, leading to better-informed decisions and a more agile response to market dynamics.
2. Data-Driven Optimization at Scale
AI is only as good as the data it is built on, and upstream operators are sitting on a goldmine. We are seeing operators that can feed machine learning models that optimize production in real time and by using AI to determine optimal flow conditions for each well. By integrating real-time sensor data with physics-based models and algorithms, they’re unlocking new levels of efficiency and performance.
This kind of optimization benefits you not only by squeezing more out of each well, but it also allows you to make smarter decisions across the entire asset development plan, from spacing and stacking to timing and completion design.
3. Operational Efficiency and Automation
AI is also driving gains in operational efficiency through automation. Early implementations of AI-powered control systems have shown 6–8% improvements in efficiency. Results like these can translate into millions in savings across large-scale operations.
According to EIR, one example comes from a sand plant in Texas, where integrating generative AI into the control system led to a 6% reduction in gas usage and an 8% increase in sand production. Similar efforts are underway to automate entire power plants, with the goal of reducing costs and increasing output.
For upstream operators, this means AI can help maximize the value of existing inventory while reducing the cost of supply, a critical advantage in today’s competitive landscape.⁴
4. Strategic Focus and Cultural Shift
While the technology is powerful, successful AI adoption requires more than just tools; in reality it requires a significant shift in your company’s culture.
Industry leaders agree that the most successful implementations come from companies that treat AI as a strategic priority. That means investing in high-quality, standardized data, while empowering employees to use AI tools and aligning leadership around clear, measurable goals.
Some companies are setting baseline expectations for all employees to understand and use generative AI. They’re also rewarding innovation and creating a culture where experimentation is encouraged, but within a framework that values methodical, scalable solutions.
In the end, embracing AI means adapting to a more exploratory and nondeterministic way of working. Unlike traditional tools, AI systems often behave like black boxes producing outputs that may not always be predictable. To navigate this, companies should be embedding human feedback loops and domain-specific knowledge into their AI systems, helping to improve accuracy and build trust in the results. To learn more about how oil and gas companies can integrate AI into their current workflows be sure to watch our “Synergistic Systems: Multi-Agent AI for Energy Application” session, from our recent EVOLVE Conference.
Final Thoughts
The energy sector may be slower to adopt AI than industries like media or finance, but the momentum is building. From optimizing well performance to automating control systems, AI is set to become a cornerstone of modern acreage strategy.
The key to success? Start small, focus on specific problems and build from a strong data foundation. As AI continues to evolve, the operators who embrace it early (and thoughtfully) will be best positioned to lead in the next era of energy development.
AI’s impact on the industry goes beyond its utility as a tool; it’s also strategic enabler. For upstream oil and gas companies, it offers a path to faster decisions, smarter development and more efficient operations.
The future of acreage strategy is here, and it’s intelligent.
References:
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[1] 2025. Enverus. North American Inventory: Increasing Cost of Supply
[2] 2025. Enverus. Despite Slow Uptake, GenAI Promises to be a Disruptor in Energy.
