Operators link AI deployment to stronger project economics and investor confidence

AIQ CEO Dennis Jol explains how operators are quantifying AI’s impact on breakeven, uptime and subsurface certainty and why lenders are starting to factor digital maturity into risk and financing decisions.

Key takeaways:

  • Operators are quantifying AI in financial terms: AI initiatives are increasingly evaluated through ROI, IRR and payback metrics, signaling a shift from cost-center thinking to investment-driven decision-making.
  • Digital maturity is emerging as a risk indicator: Predictive analytics, real-time optimization and data assurance are beginning to influence how lenders and partners gauge operational predictability and project bankability.
  • Proven use cases support economics and asset life extension: AI applications have improved seismic accuracy (up to 70%), reduced downtime through failure prediction and extended well life by up to 20%, strengthening the case for marginal and late-life asset investment.

 

As offshore operators tighten capital discipline, AI-driven performance gains are being evaluated not as incremental efficiencies, but as measurable contributors to project economics and risk reduction. 

In this exclusive Q&A, AIQ CEO Dennis Jol discusses how digital maturity is beginning to influence breakeven assumptions, downtime forecasts and subsurface uncertainty, while also shaping how lenders and partners assess project bankability. He also outlines where AI has already delivered material operational improvements in offshore environments.


Offshore: How are operators incorporating AI-driven performance improvements into project economics, specifically when calculating breakeven prices, IRR and payback periods for offshore oil and gas developments?

Jol: What we see as a technology provider to energy operators is their desire to quantify in real terms the return on investment and internal rates of return [IRR] for AI initiatives. 

... It is imperative that all levels of employees at the operator must understand what is set to be achieved through digitization and buy into it.

Offshore: To what extent are lenders, partners or investors beginning to factor digital maturity (e.g., predictive analytics and real-time optimizations) into their assessment of project risk and bankability?

Jol: We see this as an emerging trend. As capital discipline heightens, operators increasingly have to evidence operational predictability, and digital maturity is becoming part of how this is demonstrated.

Our role is to support operators in clearly reflecting the positive impact of digital transformation in their operations and be able to report on the benefits in financially tangible terms. Real-time optimization, predictive analytics and data assurance are just a few areas where AI-led digitization can have a marked impact on project risk assessment and bankability. 

Offshore: Can you point to specific offshore use cases where AI deployment has materially reduced subsurface uncertainty, downtime or cost overruns in a way that would influence a final investment decision?

Jol: Yes, these types of scenarios are our bread and butter. Our AI-enabled solutions provide measurable operational improvements in live offshore environments.

On subsurface uncertainty, for example, our AI-driven interpretation capability has improved seismic accuracy by up to 70% and accelerated model-building by up to 75%, directly reducing geological uncertainty associated with risk premiums.

With respect to downtime, predictive analytics in a project we executed across hundreds of wells reached approximately 90% accuracy in forecasting pump failures and cut related downtime by up to half. 

On asset integrity and cost, AI-plus-robotics inspection has been linked to significant multi-year maintenance savings, not to mention massive health and safety gains. 

Offshore: As capital discipline tightens across the offshore oil and gas sector, do you see AI becoming a differentiator in securing financing or partnerships for marginal fields, brownfield redevelopments or late-life assets?

Jol: On marginal, brownfield or late-life assets, AI should most definitely be considered as a tool to extend life and profitability. Through the tailored use of our capabilities, we have been able to support operators extend productive well life by up to 20% over five years, while avoiding unplanned shutdowns, further supporting the operator’s business case. 

A better-instrumented, more intelligently operating asset is also more attractive to potential investors.

Offshore: Looking ahead, how might the integration of AI and data assurance reshape financing models, such as performance-based contracts, risk-sharing agreements or lender confidence in long-term production forecasts?

Jol: Forecasts are as reliable and bankable as the data and assumptions they are based on. One of our areas of specialization is in the use of assured, verifiable, real-world data and consistent, automated analysis, which provides for the development of much more accurate algorithms and solutions. If the data and analytics underpinning a production forecast are more trustworthy, more confidence is built around it. 

About the Author

Ariana Hurtado

Editor-in-Chief

With more than a decade of copy editing, project management and journalism experience, Ariana Hurtado is a seasoned managing editor born and raised in the energy capital of the world—Houston, Texas. She currently serves as editor-in-chief of Offshore, overseeing the editorial team, its content and the brand's growth from a digital perspective. 

Utilizing her editorial expertise, she manages digital media for the Offshore team. She also helps create and oversee new special industry reports and revolutionizes existing supplements, while also contributing content to Offshore's magazine, newsletters and website as a copy editor and writer. 

Prior to her current role, she served as Offshore's editor and director of special reports from April 2022 to December 2024. Before joining Offshore, she served as senior managing editor of publications with Hart Energy. Prior to her nearly nine years with Hart, she worked on the copy desk as a news editor at the Houston Chronicle.

She graduated magna cum laude with a bachelor's degree in journalism from the University of Houston.

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