Why Governance Matters and What It Requires
Society + AI, Technology Strategy

Building Trustworthy AI: Why Governance Matters and What It Requires

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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
Platform Thinking, Technology Strategy

Why AI Projects Fail and What to Do About It

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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.

A Forecast Worth Paying Attention To
Finance + AI, Society + AI

AI 2027: A Forecast of Superintelligence and Its Implications for Finance

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The AI 2027 scenario, developed by the AI Futures Project, presents a detailed forecast of the emergence of artificial superintelligence (ASI) by 2027. The scenario offers a stark, structured forecast of where artificial intelligence may take us over the next few years. Importantly, this is not science fiction. In this post, I provide my thoughts on the AI 2027 vision and try to answer the question: How should financial services prepare for the arrival of systems that can out-think, out-code, and out-iterate us?

How AI is Reshaping the Finance Industry
Finance + AI, Technology Strategy

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

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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.

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

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

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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.

How Artificial Intelligence Is Reshaping Society
Productivity & Mental Capital, Society + AI

The Everyday Impact of AI: How Artificial Intelligence Is Reshaping Society

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You don’t have to look far to see it—AI has moved beyond the tech labs and into our kitchens, clinics, classrooms, and commute routes. It’s shifting how we make decisions, how we access care, how we learn, and how we interact with the world around us. As someone who spends time bridging data science and operational systems, I’ve seen firsthand how AI is changing more than workflows—it’s changing the rhythm of everyday life. In this post, I’ll step away from finance for a moment and explore where AI is showing up in other industries and what it means for society as a whole.

Designing Ethical AI: From Risk to Responsibility
Society + AI, Technology Strategy

Designing Fair and Ethical AI: From Risk to Responsibility

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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.

How to Avoid a Crisis of Employment and Inequality
Finance + AI, Society + AI, Technology Strategy

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

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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.

AI, Finance, and the Future of Work
Finance + AI, Productivity & Mental Capital

AI, Finance, and the Future of Work: Highlights from My Talk at BU TechConnect

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Recently, I had the privilege of speaking at Boston University’s TechConnect event hosted by the Questrom School of Business. My talk focused on how artificial intelligence is transforming financial services—not in the abstract, but in the real workflows, technologies, and people that make this industry move. In this post, I recap key points from the session, including trends in intelligent automation, the rise of AI-native workers, and what it means to lead a data science function in today’s financial ecosystem.

From OLAP Cubes to Graphs and Vectors
Data & Analytics, Technology Strategy

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

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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.

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