Apply
Your AI made the call. Now someone is asking how.
Management could not specify what it needed, technology could not hear what was asked, and the spend went out anyway. Then a board, a regulator, a plaintiff, or a customer asks how the system decided, and there is no answer. The model is a black box, the prompt is gone, and the person who approved it does not remember why. And in Colorado, from January 2027, that question becomes statutory for consequential automated decisions, with other states drafting their own versions now.
Why
The model was never the thing that failed
I did the forensic analysis on a decade of AI failures. Twelve documented cases in the first paper, eight more on bias, five more on cost. Watson at MD Anderson, Zillow, Air Canada, Robodebt, Builder.ai. Twenty five autopsies, and I went in looking for the technology failures.
I could not find them. The models mostly did what they were built to do. The failures clustered in the same five places every time: use case definition, use case approval, risk classification, human in the loop, and output validation. Not one of those is a model. All five are management. The technical layers stay clean. The management layers are flooded.
That finding is the product. OrbisFramework is those five places built as infrastructure instead of left as good intentions: the workflow defined, the gates stated, the judgment recorded, and the record kept. The organizations in those papers did not lack intelligence. They lacked the system around it.
Value delivered
The problem it solves
Your AI is making calls nobody can explain, and what it learns accrues to the vendor instead of to you.
The value it delivers
Every AI decision becomes an owned asset. The workflow, the gates, the judgment, and the record compound with use, survive model changes, and stand up when a board, a regulator, or a plaintiff asks how.
Why talk now
Bring the AI call that matters most to the business. Thirty minutes shows you what owning it looks like.
Schedule a Strategic ConversationWhat it does
The documented failures broke in five management layers. These are those layers, built as infrastructure.
Actions. The workflow, defined so it runs the same way every time. In the failure record, this is use case definition and approval.
Decisions. The gates, so the call is made against stated criteria. In the record, risk classification.
Judgment. The human evaluation, recorded rather than assumed. In the record, human in the loop.
The audit trail. All three kept, with enterprise security around them. In the record, output validation and the proof it happened.
Proof
Three white papers, free to read: twenty five documented AI failures across a decade of deployments, forensically mapped to where each one broke. The diagnosis in one line: the technical layers stay clean, the management layers are flooded.
The evidence
Read the autopsies
Three white papers, free on bradleywpetersen.com, no form. They are the record this page stands on.
April 2026
When AI Fails
Twelve documented implementation failures mapped to the architectural stages where each one broke.
Read it free (opens in a new tab)May 2026
When AI Fails Through Bias
Eight cases of algorithmic discrimination, the five mechanisms that let bias in, and the Colorado statute written to make prevention the standard of care.
Read it free (opens in a new tab)May 2026
When AI Fails Through Unbounded Cost
Five cost and time-to-value failures, one economic law, and the stopping rule most deployments never set.
Read it free (opens in a new tab)
Own the learning loop
The future of enterprise AI is not model access. It is ownership of the learning loop: the workflow, the evidence, the evaluation, the gate, the record, and the human judgment that improve with every use. Satya Nadella has framed the next era of AI around the compounding of human capital and token capital. That compounding happens in the loop, and the question is who owns it.
Your organization’s expertise should not be absorbed into someone else’s model and disappear. It should become a controlled, reusable, defensible system that compounds over time. OrbisFramework routes and replaces the models underneath, while the workflows, decision gates, evaluations, and records you have built stay yours.
Models provide intelligence. Your organization provides decisions and judgment. OrbisFramework turns both into an asset you own.
Make every AI decision an asset instead of an exposure.
Thirty minutes. Bring the AI call that matters most to the business, and leave knowing how it compounds: defended today, smarter every time after.