Inspired by last year's nobel prize winners in Economic Sciences, Joel Mokyr, Philippe Aghion & Peter Howitt, I am proposing a value chain focusing on the processes & data from Knowledge to Innovation to Process Transformation to Value Creation to Economic Growth and eventually to New Innovation Opportunities.
How does management know what its AI agents are doing, why they are doing it, what information they use, what authority they possess, what they produce, who is affected & who remains accountable? The Enterprise Action & Delegation Architecture makes delegation governable from strategy to action. > Enterprise Principal Architecture:
The important architectural shift with the banker's algorithm is to treat capital not as a largely fixed annual constraint that business units subsequently consume, but as a continuously recalculated scarce safety resource attached to risk-taking. 1. Assess Risk Change Determine how a material change like a new transaction,
Traditional banking controls generally assume that actions occur at a speed at which limits, escalation processes & humans can intervene. Agentic AI changes that assumption. An action that is safe for an individual agent is not necessarily safe for the bank & an action safe for one bank may still
With this event-driven AI-ready QMS Assurance Architecture on three hierarchical levels, the process architecture becomes the audit architecture. Q1 Understand Context & Stakeholders Ensure the QMS remains aligned with organizational context & relevant interested-party requirements. Q2 Set Quality Strategy & Objectives Translate context & stakeholder requirements into measurable quality direction.
This AI-driven Business Model blueprint for professional services represents a transition from the traditional expert-hours business model toward a continuous Human & AI enterprise transformation & trust model. 1. Identify AI Opportunities Convert strategic, operational, regulatory & technological change into prioritized AI-enabled business opportunities. Should AI be applied here at
ProcessHorizon enables enterprises to design, govern, document and assure how humans, AI agents, data & controls work together. Its Enterprise Process & Action Architecture uses event-driven SIPOC to make the enterprise operating model transparent across three connected layers: Strategy > Management > Operations This provides the architectural foundation for a
1. American Law as Professional & Adjudication System Resolve concrete disputes through an adversarial, precedent-informed judicial process while maintaining constitutional constraints, due process and consistency across cases. 2. European Law as Codified Public Governance System Translate democratically determined societal objectives into coherent, accessible and predictable legal requirements so that citizens
Dataism explains the growing power of data processing while event-driven SIPOC explains how that power can be directed toward human progress. Data is the fuel. AI is the accelerator. Process is the engine. Human purpose determines the destination & event-driven SIPOC provides the architecture connecting them. From Data-centric to Purpose-centric
From an ethical sustainable growth perspective, the board's primary responsibility is not simply to oversee ESG reporting, but to ensure that executive incentives reinforce the enterprise's long-term ethical purpose. Compensation should be the governance mechanism that steers enterprise transformation. 1 Detect Strategic Change Identify structural change,
Can we trust Chinese made humanoids or the multi-purpose humanoid Optimus built be Elon Musk's Tesla company ? How about German made quality humanoids ? Germany could leverage its world-class automotive engineering into becoming Europe's leader in industrial humanoids and VW could repurpose automotive engineering teams to develop
Can you trust an AI Emergency Triage Agent who greets you with "good evening" on a Saturday morning and tells you that your emergency situation is actually no emergency and thus prevents human interaction e.g. with a doctor ? This is a fundamental AI governance challenge. Traditional call