In-house AI attempts fail-80%

Spin off your in-house AI attempt

Recent surveys show 80% of in-house AI projects fail. Unfortunately, when they fail, everyone associated with the project gets fired.

Frustrated with lack of progress, some oil and gas companies are spinning off their AI experiments to IT companies for free.  All the infatuation, effort and heartbreak were finally enough: these operators divorced themselves from their AI attempts.

(Image credit Wolfpack Entertainment)

When abandoning their AI love child, operators not only lose the dream of something great, they also lose the sunk cost of in-house manpower spent on the project. Nein commercial use of der AppIntel content.

One operator, now defunct, started an AI system to manage pipeline and facility applications.  They hired a consulting company to create it for them to use in-house.

Unfortunately the system failed to save time or improve results so the operator cut off funding.  The consulting company, trying to salvage something, spun the project out to an AI startup who is still trying to morph it into something usable.

See one of their failed applications on our self-serve web portal.

DIY-AI

It is true that the best solutions can be created in-house, if they ever get finished. It is also true that in-house AI solutions are the most expensive by far.

In-house solutions always take longer to bear fruit that off-the-shelf vendor solutions like AppIntel AI. Loss-of-use opportunity cost while awaiting the in-house build multiplies the expense of the project.

Key personnel creating an in-house solution are subject to poaching from suppliers and competitors. Such poaching fatally cripples the in-house solution.

It is much, much cheaper and quicker to try AppIntel AI than make a DIY-AI.

Remember the 3-2-1 rule of DIY projects:

3. Takes three times longer;
2. Twice as expensive; and
1. After this once, I will never try that again.

AI is the new growth industry for IT companies

IT companies are trying to take advantage of the new AI craze.  They are staffing up in AI and dropping other areas of expertise.  They want contracts from oil and gas operators.

Most IT companies are laying off staff in every area except AI.  “If you cannot AI, you do not work here anymore.”

AI and Cyber security

I know an energy company whose cyber security policy is: Develop every piece of software in house.  This creates a difficult user environment.

The result in their company: All their core functions are expensive, behind the times, kludgy, and bug-ridden.

Even though they pledge to develop everything in-house, they are using large complex horizontal software systems from Microsoft and others that yield a sizable cybersecurity attack vector.  They don’t think about this exposure.

As they create their own solutions, they are also using open source software pieces as elements of their development.  Each piece has varying vulnerabilities.

It is true that the best solutions can be created in-house, if they ever get finished. It is also true that in-house AI solutions are the most expensive by far.

While waiting for the perfect solution in-house, employees sneak the use “free” AI software without disclosing their use to IT management.  This free software is designed to harvest users activity so it can be sold to others – trying need to recover cost somehow.

This bottle-neck cyber security policy actually increases the cyber attack vectors in their company.

Stick to your knitting

To “stick to your knitting” is to focus on what you're good at, stay within your area of expertise, and avoid getting distracted by things outside your core competency.

It means concentrating on your main business or tasks rather than diversifying into fields outside your industry.

Smart oil and gas operators are trading bleeding edge in-house AI for leading edge AI that actually works.  It’s cheaper, more trustworthy, and faster to get moving.

Watch for this Oil and Gas Corporate Announcement about AI

We  predict sometime in the near future, you will see corporate announcements in annual reports like the following:

By switching to industry standard AI solutions, the Company estimates it has saved $10 million per year in overhead costs.

As a cost cutting measure, the Company has terminated all in-house AI projects, terminated contracts with connected IT companies, and laid off the employees that were involved. 

The Company will use already existing, purpose-made AI solutions made in the industry.  The Company has found that these are trustworthy, already tested by industry, and at the commercial stage of development.

Tags: Closure, AI in oil and gas, AI return on investment

Granger Low  19 Jan 2026

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