Last month, Harvard Business Review published Marc Zao-Sanders' follow-up article on "How People Are Really Using Gen AI." As someone who's spent over two decades guiding organizations through digital transformation, I found myself nodding at some insights while raising an eyebrow at others.
The Shift to Personal Applications
What struck me immediately was the significant pivot in how people are using AI. The article notes that "Personal and Professional Support" is now the largest category of usage, with "Therapy/companionship" emerging as the #1 use case. Having witnessed countless tech trends come and go, this evolution doesn't surprise me—technology ultimately serves human needs, and what's more human than seeking connection and meaning?
However, I question whether this represents a genuine trend or simply the bias inherent in Reddit-based research. Forum users are more likely to discuss personal applications than business ones, which might distort the picture. My work with enterprises suggests that business applications of generative AI, while perhaps less discussed on Reddit, are no less transformative.
The Missing Business Context
The article touches briefly on EY 's deployment of 150 AI agents for tax-related tasks, but this barely scratches the surface of enterprise adoption. Where are the examples of supply chain optimization, customer service automation, or predictive maintenance? From my experience, these are the areas where AI is quietly revolutionizing operations.
Zao-Sanders mentions Microsoft Copilot as a personal assistant at work but doesn't explore how it's reshaping workflow processes or decision-making frameworks. The enterprise story seems oddly underrepresented for an HBR piece.
The Double-Edged Sword of AI Therapy
The emergence of AI for therapy deserves careful consideration. While I applaud technology that increases accessibility to mental health support, particularly in underserved regions like South Africa (as mentioned in the article), we must approach this trend with caution.
AI therapy presents both opportunity and risk. On one hand, it provides 24/7 support without judgment—on the other, it lacks the nuanced understanding and human connection that often drives therapeutic breakthroughs. As organizations integrate AI into their employee wellness programs, they'll need to find the right balance between technological convenience and human expertise.
The Learning Paradox
The article highlights the paradox at the heart of AI adoption: the tension between enhanced learning and potential dependency. This resonates with conversations I've had with countless business leaders who ask, "Are we using AI to augment our thinking, or are we outsourcing it entirely?"
I've seen both extremes—teams that use AI as a springboard for deeper insights and those that rely on it as a crutch. The difference often comes down to leadership and culture. Organizations that approach AI as a collaborative tool rather than a replacement tend to see the most sustainable benefits.
What's Missing: The Integration Story
What's notably absent from the HBR piece is how people are integrating multiple AI tools into cohesive workflows. In my consulting work, I rarely see businesses using a single AI application in isolation. Instead, they're creating ecosystems where multiple AI agents interact with each other and with human teams.
This integration represents the next frontier of AI adoption—not just using AI for isolated tasks but weaving it into the fabric of how we work and live. We're moving from "AI as a tool" to "AI as an environment."
The Privacy Conversation
I appreciated the article's inclusion of privacy concerns, though the quoted Reddit user's resignation to data sharing doesn't reflect the nuanced approaches I'm seeing in forward-thinking organizations. Companies are increasingly adopting "privacy by design" principles in their AI strategies, recognizing that ethical data practices are not just a compliance requirement but a competitive advantage.
Looking Forward: Evolution, Not Revolution
Zao-Sanders concludes with what he calls an "insipidly safe prediction" that AI will continue to develop. I'd offer a more specific forecast: we're moving from an era of AI experimentation to one of AI integration. The focus is shifting from what AI can do to how it can be woven into existing processes in ways that respect human agency while enhancing our capabilities.
The most successful organizations won't be those with the most advanced AI, but those that most thoughtfully blend AI capabilities with human expertise. This balanced approach has been my north star when guiding clients through digital transformation.
What are your thoughts on how AI is being used in your organization? Are you seeing the same shift toward personal applications, or is your experience different? I'd love to hear your perspectives in the comments.
Source: HBR - How People Are Really Using Gen AI in 2025 (by Marc Zao-Sanders)