Most Operators Skip This Step. Then Wonder Why AI Didn't Work.

Why This Assessment Exists

More than half of AI initiatives in oil & gas stall before delivering value (Gartner, 2025; RAND Corporation). Most operators jump straight to hiring data scientists or signing six-figure vendor contracts — without understanding whether their data infrastructure, team skills, or workflows are ready for AI.

The result? Expensive pilots that stall, dashboards nobody uses, and AI teams that quit because "the data is too messy to work with."

This 5-minute assessment tells you where you actually stand — so you can invest where it matters and skip what will fail.

It evaluates your organization across five dimensions: Data Infrastructure (how your production data is stored, collected, and governed), Analytics Maturity (the sophistication of your current decision-support tools), Team & Skills (data science capability and leadership buy-in), Process & Workflow (standardization and data accessibility), and Budget & Readiness (funding mechanisms and prior AI experience).

Each question is calibrated against real-world E&P operations, referencing tools petroleum engineers actually use (OFM, Aries, PROSPER) and infrastructure they work with (SCADA, RTU, historians). Your results include a scored breakdown per category, a radar chart of strengths and gaps, and prioritized recommendations.