Can You Use Gen AI for Qualitative Data Analysis? Here Is a Procedure, Not a Position
Short answer: Yes – if you’re doing certain things under certain circumstances that you have to verify yourself. No, if you do those things by producing this kind of content in an afternoon. Large Language Models (LLMs) can help us carry out some types of qualitative analysis. For example, descriptive coding using a fixed set […]
Using Large Language Models for Qualitative Data Analysis In 2025, more than four hundred experienced qualitative researchers from over thirty countries signed an open letter rejecting the use of generative AI in reflexive qualitative research. Not merely restricting it. Rejecting it—at every stage, including the first pass of coding. Their argument deserves to be heard […]
Why AI Fluency is Non-Negotiable for Today’s Business Leaders The landscape of modern business is undergoing a profound transformation, driven by the unprecedented speed of artificial intelligence (AI) advancement. In a mere two years, AI has evolved from niche applications with often poor results to mainstream adoption across virtually every industry. This shift signifies that AI is no longer a
Introduction: AI as a Strategic Imperative The Evolving Landscape of AI in Business Artificial intelligence has rapidly transitioned from a futuristic concept to a critical strategic imperative in boardrooms globally. Its pervasive presence in business discussions signals a profound shift in how organizations operate and compete. AI is no longer a distant possibility but an immediate strategic necessity. It is
To make strategic decisions, leaders must first understand that “AI” is not a single entity but a broad field encompassing distinct capabilities. In 2025, the business landscape is being reshaped by a triumvirate of AI categories, each with unique functions and applications. Analytical AI: The Insight Engine Analytical AI is the most mature and widely adopted form of artificial intelligence,
Today, the question is no longer if an organization will adopt AI, but how . While AI adoption continues to surge, a significant gap has emerged between ambition and execution. Industry and vendor reports suggest that firms demonstrating high AI readiness are up to three times more likely to achieve their strategic goals. Conversely, rushing into AI without a thorough
A troubling paradox has emerged in the corporate world of 2025. While AI adoption rates are soaring, a 2024 study from BCG reveals that a staggering 74% of companies are struggling to achieve and scale tangible value from their investments. This disconnect is not typically a failure of the technology itself, but a failure of strategy. The primary culprit is
As artificial intelligence permeates every facet of the modern enterprise, a new leadership challenge has emerged: “AI opportunity paralysis.” The sheer volume of potential AI applications—from optimizing supply chains to personalizing marketing and redesigning products—can be overwhelming, leaving many organizations stuck in a state of endless exploration with no clear starting point. This indecision is costly. Without a structured and
In today’s business environment, characterized by unprecedented data volume, velocity, and complexity, even the most experienced leaders face the inherent limitations of human cognition. Information overload leads to decision fatigue, while deep-seated cognitive biases can subtly distort judgment, leading to suboptimal outcomes. Artificial intelligence is now emerging not as a replacement for executive leadership, but as a powerful strategic partner—an