• Reliable, real-time decision support across well performance, water management, and capital accountability remains an unsolved operational challenge for oil and gas operators - not because data is unavailable, but because the relationships between data are not queryable.
• Critical engineering decisions involving well prioritization, produced water disposal routing, vendor cost attribution, and AFE compliance monitoring require simultaneous access to information distributed across production databases, ERP systems, completions repositories, and AP platforms.
• In the absence of a connected data architecture, this integration burden falls on individual engineers, introducing hours of manual data assembly per query and systematically limiting the frequency and quality of operational analysis.
   
• This session presents the real-world deployment of the reView Intelligence Platform, a graph-native AI reasoning system, that unified well data, production history, financials, vendor records, AFEs, and water infrastructure into a single auditable, queryable knowledge graph for Civitas Resources with these results in the first six weeks: - $6.7M in annualized disposal cost savings from a 40% reduction in produced water trucking - $12M in avoided capital surprises through early AFE overrun detection - Complex cross-domain query time reduced from 2+ hours to under 10 second

• A Strategy-First Framework. Most digital transformation efforts are initiated with a technology roadmap and an implementation plan.
• Anchoring Digital Ambition to Business Outcomes Before Any Initiative Launches. The framework’s first two phases, opportunity definition and strategy architecture, ensure that every transformation initiative is explicitly traceable to a prioritized business objective before investment decisions are made.
• People, Culture, and Operating Model as Strategic Design Inputs, Not Parallel Workstreams.
• MIT Sloan and Deloitte’s research confirms that digitally maturing organizations are four times more likely to equip employees with the skills needed for transformation and nearly twice as likely to have unified leadership driving the effort (Kane et al., 2015).

• How Petrobras architected and deployed an enterprise-wide intelligent automation framework using SAP S/4HANA, delivering a 47% reduction in process cycle times and 31% improvement in decision accuracy across upstream, midstream, and downstream operations.

• Pioneering implementation of an AI Agents platform specifically designed for regulatory compliance in the oil and gas industry, enabling real-time monitoring, risk mitigation, and automated audit processes at global scale.

• Design and integration of AI-driven financial systems (New Cash Flow Analyzer, TM-TRM, BPC) that increased forecast accuracy by 37%, combined with an enterprise-wide agile transformation that accelerated product delivery 3.5x while boosting employee engagement by 42%.

• Practical lessons learned from building a comprehensive digital skills acceleration program that upskilled over 3,000 employees and created sustainable ecosystem partnerships for continuous innovation.

• Improved data accessibility
• Faster data processing and analysis
• Enhanced accuracy and consistency
• Better decision-making
• Improved safety and environmental compliance
• Cost savings

• Overview of benchmarks and insights from 70% of North American operators regarding their specific use cases and adoption levels.
• Deep dive into pain points and challenges of scaling Generative AI for practical production environments.
• Summary of key findings and use cases collected from a Generative AI working group involving 25+ North American operators over the past 18 months.