In my previous article, The AI Shift Feels Familiar. Our Response Should Be Different., I argued that the greatest challenge organizations face is no longer the technology itself. It is building the operating models, governance, and leadership required to keep pace with AI.

I still believe that, but over the past few months, another realization has become increasingly clear: the biggest AI opportunity is no longer in engineering. It’s in everyone else. 

That may seem like a surprising statement. After all, engineers are often the first to adopt new technologies. Curiosity is part of their DNA. They naturally experiment with new models, frameworks, and tools, constantly exploring what is possible. That mindset has always been one of the greatest strengths of technical organizations. But they are also the minority. 

In most companies, roughly two-thirds of the workforce does not write software or design hardware. They work in Finance, HR, Marketing, Sales, Operations, Manufacturing, Customer Success, Legal, Product Management, and countless other functions that keep a business running every day. 

Ironically, I believe this “silent majority” represents the greatest untapped opportunity AI has to offer. 

Not because they work any less hard, quite the opposite, because every day they spend hours searching for information, preparing presentations, writing documents, summarizing meetings, analyzing data, coordinating projects, answering emails, and making decisions. 

These are exactly the kinds of activities AI is increasingly capable of improving. 

Imagine if every knowledge worker recovered just thirty minutes each day. Then, imagine that happening across hundreds or thousands of employees. 

The productivity gains would not come from one revolutionary application. They would come from thousands of small improvements quietly multiplying across the organization. 

The next AI revolution inside most enterprises may not be driven by engineering breakthroughs. It may very well be driven by ordinary work being done extraordinarily better. 

The Adoption Gap
One lesson I’ve learned throughout multiple technology transformations is that organizations often assume everyone begins the journey from the same place; they don’t. 

Every company has AI power users. They’re the people building prototypes, sharing prompts, testing the newest models, and speaking enthusiastically about what’s possible. They’re also the people we tend to notice. 

What we don’t notice as easily are the much larger number of employees who are simply trying to do their jobs well while AI evolves around them: some have embraced AI, some use it occasionally, some are curious but unsure where to begin and others feel overwhelmed by the pace of change or worry about using it incorrectly. This has very little to do with age and surprisingly little to do with job title. 

Technology confidence, curiosity, and AI maturity exist on a spectrum that spans every generation and every function, which means providing everyone with access to AI tools is only the beginning. 

Access creates opportunity, learning builds confidence, confidence changes behavior and changed behavior is where business value is created. 

Curiosity Before Capability
Organizations often approach AI enablement the same way they have approached software rollouts for decades: launch a training program, assign mandatory courses, track completion and move on. I don’t believe in this case that’s enough.  

AI is fundamentally different, learning to use AI isn’t simply about mastering another application, it’s about developing a new way of working. People rarely transform the way they work because someone assigned them a training module, they change because they discover something that genuinely makes tomorrow easier than yesterday. 

That’s why I believe our first objective should not be creating AI experts. It should be creating AI curiosity. Because curiosity leads people to experiment, experimentation builds confidence, confidence leads to discovery, and discovery is what transforms isolated productivity gains into organizational capability.

Small Steps Create Big Change
At Grass Valley, we’ve been experimenting with a deliberately simple idea we call The AI Minute. 

Every week, we share one practical use of AI that aligns with our governance framework and can immediately improve the way someone works.  One concept, one prompt, one productivity tip, one approved use case. Sometimes it’s about writing better prompts, sometimes it’s about identifying phishing emails and sometimes it’s about creating a simple AI agent.  

And every time, without fault I try to include a little humor, admittedly, a fairly nerdy humor, and it’s intentional as learning feels less intimidating when it feels approachable. 

The goal isn’t to teach everything, it’s to teach one useful thing consistently enough that people begin looking forward to the next one. Because momentum often begins with something surprisingly small. 

Measuring Success Differently
When we launched “The AI Minute”, I tried to keep my expectations realistic. If half of our workforce changes just one aspect of how they work because of something we shared, I would consider that a meaningful success. 

But that’s not my real objective, the real objective is creating a culture where employees begin teaching each other. The moment I’m most excited about isn’t publishing another edition of “The AI Minute”, it’s the day someone connects with me and says, “I’ve been using AI for this process, and it’s saving our team hours every week. Everyone should be doing this.” 

That’s when something much larger begins to happen. Innovation is no longer flowing only from leadership; it begins spreading organically throughout the organization. 

AI stops being “the new technology” and simply becomes the way people work. 

The Silent Majority May Become Our Greatest Innovators 
R&D will always play a critical role in pushing the boundaries of what AI can achieve. They should. That’s part of their mission. But I increasingly believe the next wave of enterprise transformation will come from somewhere much quieter, it will come from the financial analyst who automates reporting, the HR partner who accelerates recruiting, the project manager who eliminates hours of administrative work, the sales representative who prepares for customer meetings in half the time, the customer success manager who identifies issues before they become escalations, etc.  

None of these changes will make headlines, individually, they may even seem insignificant but collectively, they redefine how an organization operates. 

We often measure AI maturity by asking how sophisticated our models are, in hindsight, I think that’s the wrong question. A better question is this: How many employees have fundamentally changed the way they work because of AI?  

If the answer is five percent, the opportunity is still ahead of us, but if it’s fifty percent, the organization itself has changed. 

Moving Forward Together  
In my previous article, I argued that organizations need operating models capable of keeping pace with AI. That remains true, but operating models alone do not create transformation. People do. Our responsibility as leaders is not simply to provide access to AI, it is to make AI approachable, practical, responsible, and relevant to every employee and not just those already comfortable with technology. Because the organizations that will create the greatest advantage from AI may not be the ones with the most advanced engineering teams. They may be the ones that inspire the greatest number of ordinary employees to achieve extraordinary things. 

The next AI breakthrough inside most organizations won’t be a new model, it will be the moment the silent majority begins working differently.