Matthew Bertram

An empty community meeting hall at dusk with folding chairs and a blank projector screen, a lit gas plant outside the windows, and a hand holding a phone that glows with an abstract blue AI interface.

Before the Public Meeting, Someone Asks ChatGPT About Your Pipeline

Matthew Bertram6 days ago6 days ago07 mins

Permits are decided on the record. The people who show up to the public meeting make up their minds somewhere else, and more of them now start with a question typed into a chatbot.

An empty wood-paneled boardroom at night with a translucent blue network of glowing decision nodes floating above the table and a lit refinery visible through the windows.

AI Governance Isn’t an IT Project. It’s a Board Mandate

Matthew Bertram2 weeks ago6 days ago07 mins

In most energy companies AI governance sits wherever the first AI tool was installed, usually IT. That placement is the problem: IT can govern the tools, but only the board and executive leadership can own the decisions AI now shapes. What NIST says about ownership, who should own which layer, and five signs governance is in the wrong place.

A marketing executive seen from behind at a gas-processing plant at night, facing a translucent blue holographic planning board of linked timeline bars and blocks.

The Energy CMO’s 2026 Playbook for AI Visibility

Matthew Bertram4 weeks ago6 days ago07 mins

The energy CMO’s job is no longer to win the click. It is to be the source the generated answer gets assembled from, and to know with evidence whether you currently are. A quarter-by-quarter operating playbook: build the buyer prompt set and baseline first, fix the entity layer, rewrite the five capability pages that lost, then re-run the identical prompts and compare.

A technician in coveralls stands beside a compact skid-mounted gas-processing unit lit in warm amber, with an enormous refinery complex blurred in the background at dusk and a large translucent blue holographic answer panel hovering above, a beam of light singling out the small unit rather than the vast plant.

Why Energy Companies Lose the AI-Search Battle to Smaller Competitors

Matthew Bertram1 month ago6 days ago07 mins

On broad questions, scale wins. On the constrained questions buyers ask right before awarding work, a forty-person specialist routinely beats a four-thousand-person operator – because generative engines retrieve passages, not companies. Why the large-company publishing process strips out the specifics a model needs to quote, and the editorial fix that puts them back.

A reservoir engineer in a darkened room watching a glowing blue holographic production decline curve, with pump jacks and a tank silhouetted against an amber dusk sky through the window.

AI in Reserves Estimation: The Disclosure Risk Nobody’s Documenting

Matthew Bertram2 months ago6 days ago06 mins

Machine learning already sits inside the software that produces a reserves estimate. Regulation S-K Item 1202(a)(7) already requires you to describe the internal controls over that effort. Six questions that bring a stale control narrative back in line with the process you actually run.

An industrial control room at dusk with a holographic decision chain on screen, each step marked with a checkmark and one step highlighted in amber under review, a refinery glowing through the window behind, illustrating a traceable audit trail for AI-influenced decisions in energy operations.

What “Defensible AI” Means for Energy Operators in 2026

Matthew Bertram2 months ago2 months ago06 mins

Defensible AI has nothing to do with how advanced your models are. It is whether you can reconstruct how an AI-influenced decision was made, who reviewed it, and on whose authority. A six-item checklist for energy operators.

A holographic AI dashboard over a refinery control-room desk at dusk showing one validated panel with a checkmark beside a governance checklist and a demo-to-production arrow, illustrating why oil and gas AI pilots stall and the governance steps that get them to production.

Beyond the Demo: Why Oil & Gas AI Pilots Stall — and the Governance Checklist That Gets Them to Production

Matthew Bertram2 months ago2 months ago08 mins

Almost every operator now has an AI pilot that stalled in a corner. The reason is rarely the model — it is governance, traceability, and expert validation. Here is why oil & gas AI pilots stall before production and the readiness checklist that gets them there.

A glowing AI chat interface listing energy companies where only a couple are lit and the rest are greyed out, against a refinery skyline at dusk, illustrating how AI answer engines name only a few energy companies.

AI Names the Same Few Energy Companies. The Rest Are Invisible.

Matthew Bertram2 months ago2 months ago05 mins

Ask an AI assistant who to hire in oil and gas and the same handful of anchor names come back. The competitive middle of the industry is missing from the answers buyers now see first. Why it happens, where the engines get their answers, and what to do about it.

An oilfield buyer holding a phone showing an AI chat interface with an oil rig and pump jacks at dusk behind, illustrating a buyer researching an oilfield service company through an AI assistant.

When a Buyer Asks ChatGPT About Your Oilfield Service Company

Matthew Bertram3 months ago2 months ago07 mins

Your buyers now vet oilfield service companies by asking ChatGPT and Perplexity before they ever reach your site. How to find out what the AI says about your company, why it leaves you out or gets you wrong, and the checklist to fix it.

A boardroom at dusk with a holographic AI head, a governance checklist card, and a question mark, illustrating the questions boards should ask before approving an AI tool.

What Oil & Gas Boards Should Ask Before Approving an AI Tool

Matthew Bertram4 months ago2 months ago06 mins

AI tool approval is a board-level governance decision, not an IT purchase. The seven questions directors should ask before any AI tool touches a material energy decision.