Innovation Management Watch Summary: “How People Are Really Using AI in 2026” by Harvard Business Review

Source: Clara San Millán 

Generative AI is no longer a novelty people are simply testing. It is becoming part of everyday routines, work habits, and decision-making. In “How People Are Really Using AI in 2026,” Marc Zao-Sanders presents the third edition of a study tracking how people use AI in real life. The main finding is clear: AI adoption is widening, but the most important shift is not only about how many people use it. It is about how deeply AI is entering practical, personal, and professional workflows. 

The article highlights that AI use has moved beyond simple content generation. People are using it as a thinking partner, coach, assistant, tutor, analyst, and work companion. Some uses are clearly professional, while others blur the line between work and life. According to the article, 63 of the top 100 use cases are either explicitly work-related or applicable both at home and at work. This matters because it suggests that AI is not being adopted only through formal corporate programs. Much of the real experimentation is happening from the bottom up, as individuals discover what helps them save time, think more clearly, prepare better, or make better decisions. 

Source: AI Generated Image 

For innovation leaders, this bottom-up pattern is important. Many organizations still treat AI adoption as a technology deployment challenge: choose tools, define policies, train users, and measure productivity. But the article shows that actual AI use is more organic and adaptive. People are not waiting for perfect systems. They are experimenting with prompts, combining tools with their own judgment, and finding use cases that fit their own needs. This creates both opportunity and risk. The opportunity is that employees can surface valuable new applications faster than centralized teams. The risk is that organizations may not see where AI is already influencing work, decisions, communication, and learning. 

The study also suggests that AI value is not limited to automation. In many cases, users turn to AI for support in thinking, reflection, creativity, and confidence. This is a different kind of productivity. It is not only about doing the same task faster, but about making certain tasks less intimidating, easier to start, or easier to improve. For innovation management, this points to a broader role for AI: helping teams explore ideas, test assumptions, prepare scenarios, synthesize information, and accelerate learning cycles. 

The lesson for leaders is not to ask only, “Where can we automate?” A better question is, “Where are people already using AI to think, decide, create, and learn?” The answer can reveal emerging needs, hidden pain points, and new sources of capability inside the organization. 

Ultimately, the article shows that AI adoption is becoming less about the technology itself and more about how people integrate it into their daily work. For innovation leaders, the challenge is to turn scattered individual experimentation into shared organizational learning. That means creating space for responsible use, capturing useful practices, setting clear guardrails, and helping teams move from isolated AI habits to stronger innovation routines. 

This Innovation Management Watch Summary is based on the Harvard Business Review article “How People Are Really Using AI in 2026” by Marc Zao-Sanders (June 1, 2026). All rights to the original content remain with the respective copyright holders.