Smart AI for SMEs is about providing Enterprise Intelligence at SME Affordability. My business model objective is to enable small & medium-sized enterprises (SMEs) to improve productivity, quality, customer service, security and profitability through affordable, integrated and responsibly governed Agentic AI solutions. 1 Assess SME Opportunities Identify & prioritize AI
LLMs learn to become #superintelligence by capturing how business & processes work resp. how outcomes can be achieved & business value is created. And there are always better ways to reach a goal & create value for all stakeholders. Based on the process knowledge gained by using the event-driven #SIPOC
Porter's five forces model analyzes the competitive structure & profitability of industries but the cumulative consequences of changes across industries can then reshape entire national & global economies. The most disruptive force by AI ecosystem integration will be the threat of substitutes. 1. Identify AI Integration Opportunities Assess
Nvidia's five-layer AI cake explains the industrial architecture for producing intelligence. The Event-driven SIPOC Action Architecture explains how that intelligence is transformed into governed human and AI actions, measurable outcomes and sustainable economic and societal value. I am thus proposing a further top layer representing enterprise value realization,
My objective was to provide one universal, intuitive and stakeholder-oriented Action Architecture for understanding, designing, governing and executing value-creating activities across the enterprise, from business modeling to autonomous AI operations. The architecture consists of five interconnected layers, each using the same Event-driven SIPOC methodology, with explicit objectives, trigger events, process
Governance defines what should be achieved. Risk Management determines what could go wrong. Compliance establishes what must be respected. Quality Management ensures that processes and their outcomes consistently fulfill requirements & intended objectives. Together, they establish an integrated management system for responsible human & AI-driven enterprise operations. Event-driven SIPOC model
My objective is for AI users to understand: how information becomes AI intelligence, how intelligence is used to perform tasks & how the entire journey is governed to produce reliable, safe & useful outcomes. The five-stage event-driven AI Operating & Control model follows the analogy of the Vacuum Cleaner sucking
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.