Is ADL another AI model?
No. ADL sits between intelligence and consequence. Models can recommend, tools can act, and ADL keeps authority, evidence, and accountability attached to the decision.
ADL
Adaptive Decision Logic
Intelligence is getting easier. Authority is not.
Govern intelligence.Preserve human decision.
Adaptive Decision Logic keeps authority, evidence, and accountability attached as AI moves from answering questions into work with real consequences.
AI recommends. People authorize.
Any intelligence can connect.
No intelligence governs itself.
INTELLIGENCE
Any intelligence can connect.
AUTHORITY
Human authority stays explicit.
PROOF
Actions remain understandable and attributable.
The governed handoff
The answer is not the decision.
ADL creates a governed path from intelligence to consequence while keeping the person, rules, evidence, and resulting record connected.
1
ASK
Bring the problem and context
2
RECOMMEND
Intelligence proposes a next step
3
AUTHORIZE
A person retains decision authority
4
ACT
The allowed action moves forward
5
PROVE
A durable record preserves what happened
One chassis
Context → recommendation → human authority → governed action → durable proof
The questions people ask first
Start where an answer can become an action.
What does governance look like in practice?
The rules, permissions, evidence, and approvals for a specific action stay attached to that action—along with a durable record of what happened and why.
Do we have to replace our existing AI and software?
No. ADL is designed for a multi-model, multi-tool world. It governs how intelligence enters consequential work without requiring one model or one stack.
Why build this now?
Because intelligence is becoming abundant faster than trustworthy decision infrastructure. The harder question is no longer only what AI can answer, but who may act on it, under what rules, with what evidence.
One simple example
The recommendation is only part of the decision.
Imagine an AI recommends the next step in a customer, financial, clinical, or operational workflow. The useful question is not only whether the recommendation is good.
Who is allowed to approve it? What evidence mattered? Which rules applied? What happened next—and can you prove it later?
About the founder
Kellen Wilkinson
Founder, Adaptive Decision Logic
After more than a decade in enterprise technology, including leadership roles at SAP, Kellen kept seeing the same shift: increasingly capable systems were moving closer to decisions with real consequences.
His legal and operating background made the missing layer hard to ignore. Intelligence was improving quickly; the infrastructure for authority, evidence, accountability, and human judgment was not.
ADL began with a simple question: if intelligence can connect to almost anything, how do we make sure it never quietly becomes the authority?
Field Notes from ADL
Follow what changes when AI stops only answering and starts participating.
Short notes on human authority, governed intelligence, real workflows, and the questions that appear when AI gets close enough to work to have consequences.
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The premise
The future is not one model making every decision. It is many forms of intelligence participating in work that still needs a clear human authority model.