Generative AI has taken the corporate world by storm. From boardrooms to engineering teams, “AI” is on everyone’s lips as the next game-changing force. Companies are deploying chatbots, code assistants, and content generators at a dizzying pace. Yet in the midst of all this excitement lies a puzzling reality: despite widespread adoption of generative AI, many businesses aren’t seeing meaningful results on their bottom line. In fact, nearly eight in ten companies report using generative AI, yet roughly the same proportion say it has produced no significant impact on earnings [1]. This is what McKinsey dubs the “GenAI paradox”, AI is seemingly everywhere, except where it truly counts in the profit-and-loss statement [1].

In this article, we’ll unpack what the GenAI paradox means for today’s enterprises and why it’s happening. We’ll explore how most organizations are using AI in shallow, “horizontal” ways that yield only diffuse benefits, while the more transformative “vertical” applications remain stuck in pilot purgatory. Then, we’ll discuss agentic AI, a new approach that promises to break this paradox by moving AI from a passive assistant to a proactive agent deeply integrated into business processes.

Understanding the GenAI Paradox: Adoption Outpacing Impact

The term GenAI paradox captures a striking disconnect: generative AI is being adopted at scale, but tangible business impact remains elusive [1]. Surveys and studies throughout 2024–2025 paint the same picture.

By early 2025, “nearly 80% of companies have deployed GenAI in some form,” yet roughly “the same percentage report no material impact on earnings.”

Think about that — after significant investments in AI pilots and tools, four out of five companies haven’t moved the needle on revenue or profit [1]. It’s a paradox that has many CEOs and CIOs scratching their heads.

Why is AI’s impact lagging so far behind its uptake? One factor is that GenAI made AI incredibly accessible. Large language models and tools like ChatGPT, Microsoft 365 Copilot, or AI image generators put sophisticated capabilities at anyone’s fingertips. Unlike earlier waves of AI (which required data scientists and bespoke models), generative AI is as easy to try as opening a web browser [1]. This fueled explosive adoption, AI is now embedded in everything from email writing to meeting notes. But accessibility doesn’t automatically translate to ROI.
[1] McKinsey & Company, Seizing the Agentic AI Advantage, 2025. Link