Author: Robb Bush
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The Economics of Intelligence: How to Stop AI from Becoming a Cost Spike
← From AI-Centric to Orchestration-Native | PART 3 / 8 In the first two articles, we made a simple argument: That all sounds promising. But if you’re a CFO, COO, or P&L owner, there’s another question sitting underneath all of this: Will this actually make us more efficient – or just more expensive? Recent analysis…
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What an Orchestration-Native System Actually Looks Like (in Plain Language)
← From AI-Centric to Orchestration-Native | PART 2 / 8 In the first article, we argued that “AI-centric” is only a half-step. Adding copilots and assistants into individual tools is helpful, but it doesn’t solve the hardest problem large enterprises face: coordination. Sales, supply, logistics, finance, and operations all get “smarter” – but who keeps them…
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Beyond the ‘AI-Centric Imperative’: Why the Next Frontier Is Orchestration
← From AI-Centric to Orchestration-Native | PART 1 / 8 If you work in enterprise software or supply chain, you’ve probably read some version of the same message by now: AI agents are coming. Products, pricing, go-to-market, operations, infrastructure, and talent will all have to adapt. McKinsey’s recent “AI-centric imperative” paper captures that moment well. It…
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i5 Series: From AI-Centric to Orchestration-Native
Many enterprises are now chasing an AI-centric imperative1: copilots in tools, agents in workflows, intelligence embedded everywhere. That’s progress – but it doesn’t solve the hardest problem large organizations face: Some parts may be getting smarter. The overall system is not. Sales, supply, logistics, finance and operations can each have their own AI. Without a coordination…
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Autonomy Is Not the Breakthrough… Accountability Is
The HBR article “When Supply Chains Become Autonomous” captures an important inflection point: reasoning-capable AI agents can now outperform humans in tightly scoped, simulated supply chain environments. The central question is no longer whether agents can make decisions, but whether organizations can prove – across time, scenarios, and constraints – that those decisions are safe, consistent, and aligned…
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When Supply Chains Become Autonomous (HBR)
Generative AI models, particularly those with advanced reasoning capabilities, can autonomously manage supply chains, outperforming human teams in simulations like the MIT Beer Distribution Game. These models can learn, adapt, and make cross-functional decisions with minimal human oversight, reducing supply chain costs by up to 67%. Key factors for success include selecting capable models, implementing…
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McKinsey: The agentic organization – the next paradigm
AI is bringing the largest organizational paradigm shift since the industrial and digital revolutions. This new paradigm unites humans and AI agents—both virtual and physical—to work side by side at scale at near-zero marginal cost. We call it the agentic organization. https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/the-agentic-organization-contours-of-the-next-paradigm-for-the-ai-era
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i5 Context Engineering
i5’s dynamic system design turns context into computation. In i5, context engineering is the practice of embedding dynamic, structured, and evolving information into the simulation engine to generate richer, more adaptive scenarios that respond to real-world shifts. Unlike narrow prompt tuning, i5 context engineering spans: In i5, everything starts from “context.” Traditional systems WAIT for…
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i5 AI Trust & Transparency (i5 AI-BOM)
Introduction Modern enterprises are increasingly asked not only to adopt AI systems, but also to prove that those systems are safe, transparent, and accountable. Regulators (like the EU AI Act), customers, and procurement teams all expect clear evidence of how AI makes decisions, where its data comes from, and what guardrails keep humans in control. The AI-BOM…
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The Trust Deficit in Enterprise AI
Enterprises are accelerating their adoption of AI, but face a widening trust deficit. While models grow more powerful, most systems still operate as opaque black boxes – difficult to govern, risky to procure, and vulnerable to regulatory scrutiny. Procurement teams demand documentation, regulators require oversight, and boards insist on explainability. Yet current remedies – explainable AI,…