The AI Dependency Model and How It's Shaping Our Future

In my quest to be a better storyteller, I’ve been watching closely over how artificial intelligence (AI) is reshaping communication and how it influences what I like to call our “narrative intelligence.” It’s no surprise that AI isn’t just another shiny new thing anymore—it’s taking hold in everything we do, especially quickly becoming an unofficial? standard with written communication. (and not necessarily for the betterment of humanity). With all these integrations I’m still seeing a lot of fear and anxiety across the board, but what disturbs me the most is still seeing a significant number of people and organizations still? taking a passive “wait and see “ approach to integrating? AI. The concern I have is enough to warrant me creating a simple model to give those of a passive nature a way to see a new perspective on what is happening with AI adoption. Consider this a push to integrations now vs later.? I’d like to introduce the AI Dependency Model.

Now, I can't seem to escape my technical roots as an ISP co-founder.? I see too many similarities on how the integration of the? Internet relates to exactly how we are integrating AI, albeit, with one critical difference. The current speed of AI evolution is surpassing most modern models of adoption.

I’ve outlined four? stages of AI integration that I see happening—Appreciation, Anticipation, Expectation, and Dependency. These stages chart how we, as individuals, organizations, and society, will integrate AI until it becomes indispensable in our daily lives.

The Four Stages of AI Dependency

• Appreciation: This is where it all starts—people notice AI, talk about it, and get curious about its possibilities.
• Anticipation: As people start to understand AI more, they look forward to how it will change their jobs, lives, and industries. We will eagerly await new products and services that utilize AI.
• Expectation: Before you know it, AI isn't just a nice-to-have, it’s expected—just like we expect electricity to work when we flip a switch. Products and services will be expected to have some level of AI integration. Products or services not utilizing AI will not even be considered in our buying process.
• Dependency: Finally, the real kicker—AI becomes so critical that we can’t function without it. It’s everywhere, from the way businesses run to how we make daily decisions. We are dependent on it.

Why It Matters: A Lesson From the Internet

This model is nothing new. I love looking at the parallels between AI today and the internet back in the late ‘90s. Back then, the internet was a novelty. I remember when businesses didn’t see it as essential, and now… well, we all know how that turned out. The Internet went through all four stages and for many products, services and people, it's a dependency, we can’t live without it. This timeline in general took about 20-30 years from the Internet as a novelty to full fledged dependency. You can go back to those early Internet days and follow the Dependency Model with your own experience and it will make perfect sense. That television you purchased just 10 years ago with Internet capability was an appreciation, a nice to have feature, today you’re dependent on it. That coffee shop you once appreciated 20 years ago for its Internet service was far superior to yours is now a dependency. Can you imagine walking into a coffee shop or hotel and finding out there is no Internet? The horror!

The same is happening with AI, but one significant difference, it is happening? on a faster, more intense scale. That 20-30 year timeline? I believe we are looking at in general AI utilization terms 3-10 years, perhaps even sooner.?

Think about this? for a second—where do you think we are in these stages right now? Do you notice the same shifts in your own experience with AI? Is it a cool tech, or is it already something you anticipate, expect, or even depend on? (one can argue that some people are already dependent on ChaGPT)

I’ve run across people who still don’t use it or even intend to do anything with it, to people who already moved through all the stages and are dependent on it, and I find that fascinating.

A New Take on the Amara Law

This is where things get interesting. You might have heard of Amara’s Law. It basically says people overestimate the short-term impact of technology and underestimate its long-term impact. Bill Gates popularized a version of this, too, saying we tend to overestimate what will happen in two years but underestimate what happens in ten. Not paying attention to Amara law can get one in trouble, remember the Blackberry? The? Nokia phone??

But here’s the thing—Amara’s Law was based on old-school innovation cycles, like Moore’s Law, where? processing power would double every 18 months. A linear cycle. You could plan on, and forecast the 18 month cycle. The exponential innovation pace of AI development changes everything. My gut says that with the? Amara law of 2–10 years is now happening in a matter of 6 months to 3 years. Call it Zards' Law if you like, What new case studies that will rival Blackberry and Nokia? Only time will tell, and with AI’s rapid evolution we won’t have to wait too long.

What’s the Point?

Here’s the takeaway: If we’re focusing too much on the immediate impact of AI, we might miss the bigger picture. And the bigger picture is not 10,20,30 years away. The bigger picture is now only months. The AI Dependency Model gives a mental check-in. Where are we in our adoption of AI? What stage are we in? What decisions will we make knowing that the next stage is months away, not years? For example, if your organization is building an AI tool and you're still in the “Appreciation” stage, know that things will shift quickly,? very quickly. All the old business rules and experience that tells you you’ll have time no longer apply. Waiting for that fear and anxiety to subside until you make your next move will never happen. Rules no longer exist. Don’t wait for the rules, create them. Before you know it, AI will be an expectation, if not a full-blown dependency. And that shift will? change the decisions you make? today.

The Real Challenge: Navigating AI Fear and Anxiety

The reality is, there’s a lot? fear out there—people feeling like they’re playing catch-up with AI. This short-term fear clouds the long-term vision. It’s pushing us into two extremes: Either we’re stuck worrying about immediate, short-term survival, or we’re jumping straight to the endgame—becoming AI-controlled cyborgs or ruled by an AI overlord (take your pick).

The truth is somewhere in between. By understanding where we are in the AI Dependency Model, we can make smarter decisions now and be better prepared for what’s coming. It’s not about panicking; it’s about being aware and strategic in how we embrace AI—so we can ensure it helps us evolve rather than just overwhelm us. It’s taking a new approach to fear and anxiety and embracing it as the new norm. Risk taking is mandatory.

The model shows us a reminder of? what will happen, like it not.? Individuals and organizations will quickly move through the stages and eventually become dependent on AI at some level. The critical piece is that it will happen at a rate that's unheard of. While Henry Ford might have envisioned humans to be dependent on cars over a timespan of a 100 years, and the Internet dependency took 30, the timeline for AI you can count on one hand. So buckle up, don’t wait, and fight through that fear and anxiety and adopt AI. You’ll depend on it.

Beyond the Model: Real-World AI Integration?

Let's get practical for a moment. I'm seeing organizations tackle AI integration in fascinating ways. Take the legal industry—what started as an appreciation for AI's potential in document review has quickly moved to dependency, with firms now expecting AI-powered contract analysis. Or look at customer service: chatbots went from novelty to necessity in what felt like minutes. Even creative industries, which many thought would be immune, are now seeing AI as indispensable for initial concept work and workflow optimization.

But here's the kicker—successful integration isn't just about throwing AI at everything. I'm watching organizations succeed by following what I call the "Strategic Speed" approach:

Start Small, Scale Fast: Begin with one clear AI implementation that solves a specific pain point. Maybe it's using AI for email management or content creation. Master that, then expand rapidly.

Build Your AI Muscle: Create a dedicated team or assign champions who understand both your business and AI capabilities. This isn't just about technical skills—it's about understanding how AI fits into your organizational DNA.

Measure Everything: Track not just the obvious metrics like time saved or cost reduction, but also the? shifts in how your team works and thinks. Are they becoming more strategic? More creative? These insights will guide your next moves. (A brilliant term I recently learned from Gartner suggests ROE (return on employee) , a measurement which focuses on the benefits accrued when employees are empowered? with new tools and improved digital dexterity.)

The Integration Roadmap For those wondering how to navigate these stages practically, here's what I'm seeing work:

Appreciation Stage:

• Start experimenting with AI tools personally
• Identify three specific problems AI could solve in your organization
• Begin building AI literacy across your team

Anticipation Stage:

• Create your AI integration strategy
• Pilot small projects with clear success metrics
• Build partnerships with AI providers and experts

Expectation Stage:

• Scale successful pilots across departments
• Integrate AI into your core processes
• Develop AI governance frameworks

Dependency Stage:

• Ensure redundancy and reliability
• Continue evolving your AI capabilities
• Foster innovation in AI applications

A Word About Resistance?

Something I'm seeing more and more—smart resistance. Not all hesitation comes from fear. Some organizations are asking brilliant questions about AI integration: How do we maintain control over critical decisions? What happens when AI systems conflict? How do we ensure our competitive advantage isn't just based on the same AI tools everyone else is using?

These aren't barriers to adoption—they're crucial considerations that make your AI integration more robust. The key is to address them while moving forward, not using them as reasons to stay still.

The New Normal: Continuous Evolution?

Here's something that keeps me up at night: We're not just moving through these stages once. As AI capabilities evolve, we'll cycle through them repeatedly with each new advancement. The organizations that thrive will be those that build adaptability into their DNA.

Remember the coffee shop internet example? Soon, we'll have the same reaction to businesses not using AI effectively: "What do you mean your customer service doesn't have AI assistance?" or "Your strategy isn't informed by AI analysis?"

The Power of Now

One final thought that I can't stress enough: The timeline compression I mentioned earlier means your window for competitive advantage is shorter than ever. While the Internet gave you years to adapt, AI is giving you months, maybe weeks. Every day of waiting is a day your competitors are moving forward.

Your Next Move?

So here's my challenge to you: Look at where you are in the AI Dependency Model and jump forward one stage. If you're in Appreciation, start building Anticipation by identifying specific AI implementations. If you're in Anticipation, create Expectation by making AI central to one core process.

The future isn't coming—it's being created right now, at this moment, by those who understand that AI dependency isn't just another tech trend. It's the new foundation of competitive advantage.

Where will you be six months from now? Still appreciating the potential, or already creating new possibilities with AI as your partner?

So, where do you think you’re at? And how do you plan to adapt as AI continues its march toward deeper integration into everything we do?