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3% more invoices per person in an automated Procure-to-Pay cycle

Purchasing teams spent hours on each invoice, and the cycle had gaps in control. NTT DATA reviewed operations, tools and the organizational model, then built a roadmap with four automation scenarios. Each person in the process now handles 43% more invoices, and the process runs with 34% fewer full-time employees.

3% more invoices per person in an automated Procure-to-Pay cycle

43% more invoices per person in an automated Procure-to-Pay cycle

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Report

Oil & Gas

The Autonomous Barrel

18 Sep 2026

From automation to autonomy: how AI and Physical AI could redefine productivity in U.S. Oil & Gas by moving from the optimized asset to the autonomous asset.

America has never pumped more oil, and it has never had less room to fail. Refineries are running flat out, while the old productivity engine is running out of torque.

The market has also burned through its cushion against shocks. The next barrel of advantage will not be drilled. It will come from making the assets a company already owns run longer, fail less and adapt faster. That is the autonomous barrel, and it depends on putting AI to work in the physical plant and field.

Market Signals

Three pressures are shifting the source of advantage

Three facts hold at once in the U.S. oil and gas system this September. Together, they point to a different source of productivity.

13.8M b/d

Forecast U.S. crude production in 2026, a new record.

< 2%

Growth in new-well oil production per rig from June 2024 to June 2025.

~ 98%

Gulf Coast refinery utilization in mid-2026, with almost no spare capacity.

~$110 crude

record diesel prices.

Record output, less room to fail

The EIA forecasts record U.S. crude production of 13.8 million barrels per day in 2026. Yet new-well production per rig rose less than 2% between June 2024 and June 2025, while Gulf Coast refineries ran near 98% utilization in mid-2026. Shell and Equinor have also warned that the market’s capacity to absorb disruption is weakening. More production, less incremental productivity and almost no downstream slack point to the same conclusion: existing assets must run smarter.

These pressures shift the productivity question from how many assets an operator can add to how intelligently existing assets can perform. The move is from optimized assets that inform people to autonomous assets that can sense, decide and act within defined engineering, safety and governance limits. That opportunity is taking shape across three operating territories.

An autonomous robots in an Oil&Gas scenario

Where autonomy becomes tangible

Three operating territories define the opportunity

The autonomous well and field. Adaptative production, higher uptime and less human exposure in hazardous environments.
The autonomous refinery.Continous adjustment across equipment condiciont, process constraints, energy use and yields.
Physical AI as an operational shock absorber.Assets that detect and respond to operational shocks faster.

NTT DATA Point Of View

Connect AI to physical operations at scale

NTT DATA’s position is grounded in the integration challenge. Its Physical AI capabilities span edge intelligence, advanced connectivity, simulation, robotics and digital twins, IT and OT integration, cybersecurity, and lifecycle governance. For Oil & Gas, these capabilities connect technology to production, availability and resilience through a governed path toward autonomy.

NTT DATA Oil & Gas

Point of view

The next productivity cycle will not be won by the one with the most AI models. It will be the one that can connect AI to physical operations at scale.

The questions leaders should be asking now

Boardroom questions

Where do our highest-value assets sit on the autonomy matrix today, and what should their next step be?

Is our real constraint the AI, or is it OT and IT integration, data quality, edge connectivity and cybersecurity?

Are we investing to have the most AI models, or to connect AI to physical operations at scale?

See what it takes to move from the optimized asset to the autonomous asset

The extended edition maps the autonomy ladder, compares three operating scenarios and examines the integration, governance and value decisions required to move from pilots to autonomous assets at scale.

Download the full perspective

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