Part 1: Introduction

Series: What Every CEO Should Know About Generative AI

In the mid-1990s, when the internet began to take off, we witnessed a wave of new business ideas. Some made sense, others didn’t. Many projects failed, and adoption was slower than expected. Yet over the past 25+ years, the internet has profoundly transformed nearly every industry, fueling the rise of new giants and the decline of once-dominant players.

Now, a quarter century later, we’re seeing similar patterns emerge with Generative Artificial Intelligence (Gen AI). Once again, we have overpromising tech leaders and overly enthusiastic managers on one side, and uninformed or even ignorant leaders on the other. While many early projects fall short of expectations, Gen AI is arguably the most transformative technology since the advent of the World Wide Web.

The Reality Behind the Hype

A recent MIT study, State of AI in Business 2025, made headlines by stating that 95% of organizations are getting zero return from AI. Many are stuck in “pilot purgatory", unable to scale beyond isolated proof-of-concept projects.

While minimizing unproductive AI investments is important, it’s also normal for early-stage technologies to have a high failure rate. What matters is how we learn and adapt.

The Role of Leadership: Knowledge as the Key to Success

I believe that successful adoption of Gen AI can be significantly improved if leadership—especially at the C-level—develops a deeper understanding of how these systems work and what they can (and cannot) do. Informed executives are better equipped to:

• Recognize the true potential of Gen AI for their business

• Select and prioritize the right use cases and projects

• Assess both the risks and opportunities of Gen AI

• Align Gen AI with their business models and organizational capabilities

Gen AI excels at solving problems that are difficult for traditional IT, especially those involving unstructured or semi-structured data like text, speech, images, and video. But it often performs poorly on tasks that are already well-handled by conventional systems.

Failing to Act Is Not an Option

In Switzerland, where productivity growth has lagged behind the U.S. and fast-growing East Asian economies such as South Korea and China, Generative AI offers a unique opportunity to improve efficiency, quality, and speed and to enable entirely new business models. With high wages and a high cost of living, Switzerland cannot afford to ignore these opportunities. Falling behind would mean losing ground to more agile international competitors.

A Short Article Series as a Guide

Generative AI applications and projects may look like traditional IT initiatives at first glance, but they behave fundamentally differently. The intuition many executives have developed over years of managing conventional IT often leads to misjudgments and poor decisions here.

In the coming weeks, we will publish a short series exploring the unique characteristics of AI applications and projects, providing a foundation for better assessing opportunities and risks and enabling informed decisions.