When my role as SVP at Lark Health was eliminated on May 2nd, I found myself with something I hadn’t had in years: time to think deeply about what’s happening in our industry right now. And what I’ve been seeing in enterprise AI transformation frankly concerned me.
Not because AI is dangerous—though it can be—but because so many organizations are making the same mistakes I’ve watched companies make during every major technology shift over the past two decades. I’ve led organizations through DevOps transformations, Agile adoptions, and cloud migrations. Beyond the corporate roles, I was deeply involved in the broader transformation community; running meetups, speaking at conferences, and actively sharing what I was learning and developing with others. I know what successful transformation looks like, and more importantly, I know what failure looks like.
So I decided to do something about it.
Why I Started Groktopus
For the past few months, I’ve been pouring my energy into Groktopus, a newsletter and research publication focused on human-first enterprise AI transformation. The name comes from my belief that we need to “grok” AI—truly understand it at a deep level—before we can implement it successfully.
What makes my perspective different? Being AuDHD—a portmanteau of “Autism” and “ADHD” for those diagnosed with both conditions who experience the combination as something more complicated than just the sum of the two conditions—has actually been an advantage here. Being Autistic and having ADHD helps me cut through industry noise and see patterns others miss. My decades of transformation leadership give me a framework for what actually works when organizations try to change. And my background as an applied futurist helps me connect dots between academic research, industry trends, and real-world implementation.
The result has been some of the most in-depth analysis and practical guidance I’ve ever produced. And here’s something my readers might find interesting: I’m doing this by practicing what I preach about human-AI collaboration. Most of my Groktopus articles have accompanying podcast episodes that are AI-generated under my direction—showing how we can multiply human capability rather than replace it.
We’re at a Critical Inflection Point
The central thesis driving all my work right now is simple: we’re at the AI inflection point, and the next 18 months will determine everything. Organizations that get AI transformation right will gain sustainable competitive advantages. Those that don’t risk becoming irrelevant.
But here’s what most leaders are missing—this isn’t primarily a technology challenge. It’s a human challenge.
Take Salesforce’s recent $8 billion acquisition of Informatica. On the surface, it looks like a data infrastructure play. But dig deeper and you’ll see it’s really about solving the trust problem that makes AI agents viable in enterprise settings. You can’t have autonomous AI making decisions without clean, governed, contextual data that humans can trust.
Or consider what I’ve discovered about employee readiness. Your employees are ready for AI, but are you leading fast enough? Most executives think their workforce isn’t prepared for AI adoption. The reality is exactly the opposite—employees are eager for AI tools that make their work more meaningful, but leadership isn’t moving fast enough to provide clear vision, training, and support.
The Human Cost of Getting It Wrong
The consequences of AI-first thinking are already showing up in real organizations. I’ve documented cases like Duolingo’s AI-first disaster—a cautionary tale of what happens when you prioritize automation over human partnership. The result? Mass layoffs, product quality issues, and a brand crisis that could have been avoided.
The 55% regret club keeps growing—companies that rushed into AI-first transformations without considering human impact are now backtracking. Meanwhile, 38% of workers fear for their jobs because of how AI is being positioned in their organizations.
This isn’t just about individual companies. The hidden crisis in tech reveals what 8,200 workers told us about burnout, AI anxiety, and leadership failures. We’re creating a workforce crisis while trying to solve productivity problems.
What Human-First AI Transformation Looks Like
The alternative approach—what I call human-first AI transformation—starts with a different question. Instead of “How can AI replace human work?” we ask “How can AI multiply human capability?”
I’ve been studying organizations that get this right. Microsoft’s vision for the frontier firm provides a compelling framework for thinking about hybrid workforce revolution where humans and AI agents work as teams rather than competitors.
The practical implications are significant. Harvard Business Review validates what we’ve been saying—the human-AI hybrid workforce isn’t coming, it’s already here. The question is whether organizations will embrace intelligent augmentation or continue down the path of replacement-focused automation.
Practical Implementation Guidance
Theory is useful, but transformation requires practical steps. That’s why I’ve developed comprehensive implementation guides for the major enterprise AI platforms. Microsoft 365 AI: The complete enterprise guide walks organizations through everything from technical setup to change management for Copilot deployment.
Google Workspace AI: The complete business guide takes a similar approach for organizations in the Google ecosystem, focusing on how to multiply human capability rather than simply add AI features.
For leaders ready to take a systematic approach, The Human-First AI Implementation Playbook provides six concrete steps to avoid the 42% failure rate that plagues most AI initiatives.
And because individual effectiveness matters too, I’ve created guides like Getting exceptional results from AI: A beginner’s guide to better prompting and explored how personalizing AI chat tools for neurodivergent communication needs can make these tools more accessible and effective.
Preparing for the Future of Work
The changes coming are bigger than just new software tools. Beyond AI assistants, human-agent teams will transform organizations in ways most leaders haven’t fully grasped yet. This requires becoming an agent boss—developing skills for the AI-enhanced workplace.
Building your own frontier firm requires understanding both the technology possibilities and the human factors that determine success or failure.
I’ve even explored when machines dream—the top AI films and shows that shaped how we think about tomorrow, because understanding our cultural narratives about AI affects how we implement it in practice.
Staying Ahead of Rapid Change
The pace of change in enterprise AI is accelerating. That’s why I publish at least one well-researched article every weekday, synthesizing the most important developments across technology, research, policy, and business strategy.
Recent developments like Grammarly’s $1 billion test case for human-centered AI platforms and Claude 4’s emergence as the first AI agent boss-ready assistant show how quickly the landscape is evolving.
The AI workplace skills gap crisis reveals what academic research tells us about what enterprises are missing in their transformation efforts.
Additionally, I’ve published pieces like Executive AI Intelligence Brief: 5 key developments this week and provided a Week in Review and welcome back to help readers stay current with the rapidly evolving landscape.
An Invitation to Join the Conversation
What I’ve built at Groktopus represents the most focused and impactful work I’ve done in my career. It combines decades of transformation leadership experience with deep research into what actually works when organizations try to change.
If you’re interested in following along with my analysis and insights, I’d encourage you to sign up for the free Groktopus newsletter. You’ll get daily synthesis of the most important developments in enterprise AI delivered each weekday morning at 7am Eastern, practical implementation guidance, and early access to frameworks and tools that can help your organization navigate this transformation successfully.
And if you find something useful there, please share it with someone else who might benefit. The more leaders who understand the human side of AI transformation, the better outcomes we’ll all see.
This inflection point won’t last forever. The organizations that move decisively in the next 18 months will shape the future of work for decades to come. The question is: will you be leading that change, or reacting to it?