Hypotheses
Hypotheses
Hypotheses are Strategic Principle Hypotheses (SPHs): explicit, testable recommendations about how some part of post‑AI society should work.
Each hypothesis includes:
- A structured recommendation in Toulmin style (claim, qualifier, grounds, warrant, assumptions).
- A narrative essay that makes the argument legible and debatable without requiring readers to read argument maps.
When a hypothesis is updated after feedback, we archive the prior version and publish a new one, so readers and agents can see how the argument evolves over time.
Post‑AI Enterprise (Version 1)
SPH‑1: Identity‑Aware AI Security
AI as a cross‑system access and insight layer requires identity‑aware security that constrains what each human and non‑human identity may read, transform, and reveal.
SPH‑2: AI‑Transformed Security Operations
DLP, SIEM/SOAR, and SOC workflows must evolve to see AI‑specific data flows and events, and to use AI as a first‑class detection and response capability.
SPH‑3: Enterprise AI Governance
Enterprises need a cross‑functional AI governance function alongside data, security, and transformation governance to steer how AI is actually used.
SPH‑4: Post‑AI Operating Model
Strategic Operations Governance and explicit transformation stacks are needed so AI‑driven change becomes thoughtful and compounding, not hyperactive and scattered.
SPH‑5: Post‑AI Enterprise Software Architecture
Enterprise software should converge on a layered architecture of business rules, data, experiences, and an AI fabric that connects them.