Author: Keith Baldwin

This week, I read Dr. Jeffrey Funk’s insightful LinkedIn post on Disney and Lionsgate’s experiments—and frustrations—with generative AI in Hollywood. Richard Self’s comment got me thinking. He highlighted a fascinating contrast: studios that once boasted about AI generating anime versions of John Wick or cloning Dwayne “The Rock” Johnson for Moana sequels are now scaling […]

Introduction Forecasting has always been at the heart of supply chain management. The difference today? The complexity of global supply networks makes “gut instinct” forecasting obsolete. Inaccurate predictions lead to overstocked warehouses, stockouts, and disappointed customers. But there’s good news: AI-driven forecasting is no longer the exclusive domain of data scientists coding in Python. Thanks […]

Introduction Let’s face it: many AI projects don’t fail because of bad algorithms. They fail because AI team communication collapses somewhere between the boardroom and the buildroom. Developers speak in acronyms, stack traces, and C# snippets that might as well be Klingon. Executives counter with ROI forecasts, compliance demands, and slide decks that feel like […]

Introduction Artificial Intelligence (AI) has shifted from boardroom buzzword to boardroom mandate. For executives leading Microsoft-centric enterprises, the question is no longer “Should we adopt AI?” but “How ready are we to scale AI across our business?” That readiness is not a binary yes/no. Instead, it’s a progression—a journey marked by stages of maturity. Just […]

Introduction: Failure as a Teacher In AI development, failure is not a risk—it is an inevitability. The question is not if an AI project will stumble, but when and how. What distinguishes successful organizations is not immunity from failure, but the ability to catch it early, learn from it, and redirect before losses spiral out […]

Introduction: Why ROI Matters More Than Ever AI is no longer confined to research labs or pilot experiments. Executives and business leaders now demand measurable returns. In an age of budget scrutiny and heightened expectations, the question is no longer “Can we do AI?” but rather “Should we, and what value will it deliver?” The […]

Introduction: The Fragility of Trust In software engineering, and especially in AI, the act of deploying code is no longer a purely technical gesture—it is an act of trust. We trust the pipeline to safeguard sensitive data, the infrastructure to comply with regulations, and the organization to honor the confidence placed in it by clients, […]

Introduction In my previous article, we explored the big idea: why large enterprises lose their innovative edge, and how they can revive it in the age of AI. We looked at Intel’s missed opportunities, NASA’s bureaucratic slowdown, and the lessons from disruptors like SpaceX and TSMC. The conclusion was clear: innovation requires autonomy, speed, and […]

Introduction Success can be a trap. The very processes and structures that allow an organization to dominate can eventually suffocate the creativity that made it great. Intel once set the pace for the entire semiconductor industry, only to stumble as AMD and TSMC overtook it. NASA put humans on the moon, but decades later private […]

Introduction: Why Backcasting? When organizations talk about bias mitigation in AI, the conversation often sounds like compliance training: tick the boxes, fill the forms, move on. Yet fairness in AI is not about checklists—it’s about long-term trust, systemic resilience, and societal impact. To break free from the checklist trap, we’ll use future backcasting: envisioning a […]

Artificial intelligence isn’t short on hype. What it is short on are real-world success stories that go beyond flashy demos and actually deliver reliable, scalable, and useful systems. This is where applied researchers and systems integrators step in. They live in the messy middle ground between the lab and the boardroom — between “here’s a […]

Introduction: The Hype and the Fear When executives hear the phrase AI for compliance and risk management across industries, they often react in two extremes: The truth, as usual, lies somewhere in between. To separate fact from fiction, let’s bust some of the most common myths surrounding AI in compliance and risk management. Along the […]

Introduction Artificial Intelligence (AI) has moved from research labs into mainstream enterprise applications. Yet, as adoption accelerates, so do concerns about accountability, compliance, and trust. Executives increasingly face questions not about what AI can do—but about how AI does it and whether decisions are traceable, explainable, and secure. This is where audit trails and transparency […]

Introduction Intelligent Document Processing (IDP) is one of the most practical and impactful applications of artificial intelligence today. It’s the backbone of countless enterprise workflows — from processing invoices and contracts to digitizing healthcare records, government applications, and compliance documents. Yet despite the hype around large language models (LLMs), anyone who has tried to automate […]