Tod McKenna: Technology Strategy

Building Trustworthy AI: Why Governance Matters and What It Requires

tod.mckenna / 2025-05-17

AI isn’t on the horizon—it’s here now, and adoption is growing. From credit models to clinical decisions, AI is touching systems that impact people’s lives at an increasing pace. And with that extended reach comes increased risk. The question isn’t whether AI needs governance; it’s whether your organization is ready to lead with it. In this post, I explain why AI governance matters and what it requires. We’ll look at three foundational frameworks: NIST AI RMF, ISO/IEC 42001, and the EU’s Ethics Guidelines for Trustworthy AI. I’ll also make the case that governance isn’t about bureaucracy: It’s about clarity, accountability, and the credibility to confidently scale AI.

Why AI Projects Fail and What to Do About It

tod.mckenna / 2025-05-03

Most AI projects fail. That’s a headline we often see. They fail not because the idea or design was faulty. Not because the technology wasn’t ready. No, they fail for the same reasons any ambitious project fails: weak alignment, unclear scope, lacking data quality, and poor governance. In this post, I explain why AI projects go off the rails, the signals to watch for, and the practices that high-functioning teams use to turn AI from hype into operational leverage.

How AI is Reshaping the Finance Industry

Finance + AI, Technology Strategy

The Hybrid Future of Finance: How AI is Reshaping the Industry

tod.mckenna / 2025-03-08

In finance and across other sectors, Artificial Intelligence isn’t just a layer of tech we bolt onto existing systems—AI is reshaping the business model, the business processes, and even the talent models that define the industry. This post explores how AI (Generative AI and Agentic AI in particular) is transforming financial services through intelligent automation, next-gen portfolio management, real-time compliance, and human-AI collaboration. The wave of AI excitement is more than a hyped trend; it represents a fundamental shift in how we think, work, and lead. But as we ride that wave, we have to keep to the human side of the fence—using AI not to replace judgment, but to elevate it.

Technology Strategy

Building the AI Operating Layer: Why the Model Context Protocol (MCP) Matters

tod.mckenna / 2025-02-01

Anthropic’s Model Context Protocol (MCP) is more than a technical standard—it’s a foundational shift in how AI systems interact with the world. MCP addresses the complex integration challenges that have long hindered scalable AI deployment by standardizing the connection between AI models and external tools. This post explores how MCP transforms AI from isolated models into integrated systems capable of dynamic, context-rich interactions.

Designing Ethical AI: From Risk to Responsibility

Society + AI, Technology Strategy

Designing Fair and Ethical AI: From Risk to Responsibility

tod.mckenna / 2024-11-09

As artificial intelligence becomes embedded in healthcare, finance, hiring, law enforcement, and everyday life, its ethical implications are no longer theoretical. AI systems reflect the data and assumptions we feed them, and that makes them vulnerable to bias, discrimination, and unintended harm. This post attempts to explore AI’s ethical challenges, existing policies that are trying to address them, and the strategic ideas needed to ensure its ongoing, responsible, and trustworthy use.

Finance + AI, Society + AI, Technology Strategy

AI, Automation, and the Future of Work: How to Avoid a Crisis of Employment and Inequality

tod.mckenna / 2024-09-07

As artificial intelligence and automation reshape global industries, mass unemployment and income inequality concerns have moved from speculative fiction to legitimate policy challenges. In this post, I present key ideas that examine how AI will likely impact employment, economic structures, and societal well-being. Most importantly, it outlines strategies that governments, institutions, and individuals can adopt to mitigate the risks and unlock the opportunities of the AI-driven economy.

Data & Analytics, Technology Strategy

The Evolving Role of Analytical Databases: From OLAP Cubes to Graphs and Vectors

tod.mckenna / 2024-05-11

Analytical databases are no longer confined to OLAP cubes and MDX. Today, they encompass a broader ecosystem of tools that enable fast, complex, and multidimensional querying across diverse data structures. This post traces my first-hand account of the evolution of analytical databases from traditional multidimensional OLAP to more modern paradigms, including graph and vector databases. I provide my views on selecting the right engine for the analytical job based on structure, purpose, and performance.