Since yesterday was Star Trek Day, I felt compelled to reflect on where we really are with artificial intelligence. Star Trek has always inspired visions of the future, but it’s easy to forget how many of its “fantasies” quietly became platforms we now take for granted. The communicator badge, once pure science fiction, feels ordinary today because smartphones absorbed its function. What was once revolutionary became invisible infrastructure.

We’re living through a similar moment now with AI. It is the current platform everyone is building on, just like websites were for the internet and mobile apps were for the iPhone. And like those previous shifts, AI will eventually mature, standardize, and then fade into the background as the next great platform captures our collective imagination.

I’ve been telling people for months now that AI, as we know it today, is going away in about five years. Let me clarify before the pitchforks come out: Artificial Intelligence has existed for over 30 years and will continue existing for decades more. It’s not disappearing like cassette tapes or rotary phones. But the platform will evolve, just as sound recording evolved from analog to digital to streaming, and telecommunications evolved from landlines to mobile to whatever comes next.

Beam me up.

The Predictable Arc of Platform Evolution

Every central technology platform follows a predictable maturity curve, and AI is no exception. We’re currently in the first phase, the wild wild west, the chaotic first two years where nobody really understands what they’re dealing with. Companies are throwing everything at the wall to see what sticks. Investors are placing massive bets on technologies they don’t fully comprehend. Users are simultaneously amazed and frustrated by capabilities that feel both revolutionary and half-baked.

The next phase, years 3-5, will bring standardization. Industry standards will emerge. Companies will stop reinventing the wheel and start building genuine value on top of established AI foundations. We’ll see the equivalent of web development frameworks and mobile app stores pushing the infrastructure that transforms experimental technology into a reliable platform for innovation.

Years 6-10 mark the ubiquity phase. AI will become so integrated into our daily lives that we’ll stop hyping it, just like nobody today gets excited about mobile apps as a concept. Your car will have AI, your thermostat will have AI, and your coffee maker will probably have AI. It’ll be invisible infrastructure, not a selling point.

Finally, years 10-15 bring the next disruption. Innovation will begin happening again, new technology will be introduced, and a new platform will emerge for people to build on. The hype cycle will reset, and we’ll look back at AI the way we now look back at early websites.

What Makes AI Different (And Dangerous)

What’s changed with AI compared to previous platform shifts is the intoxication factor. The ease of use, accessibility, and personalization possibilities drive adoption. Where websites generated a wave of web designers and the iPhone generated a wave of app developers, AI can mainly be engaged with as a solo activity. And that’s addictive. Let’s not sugarcoat it, I think it’s genuinely addictive.

This individual engagement creates a stickiness that previous platforms lacked. You didn’t sit alone in your room having deep conversations with your website or developing emotional attachments to your mobile apps. AI offers something closer to a relationship, albeit a synthetic one. This changes the adoption curve and makes the platform shift more personal, more intimate, and potentially more disruptive to human behavior and society.

But despite how you use AI, despite how personal it feels, it doesn’t change the fundamental fact that once it integrates into our lives and becomes as standardized as phones or websites, something else will find its way into the technology stack and replace the AI platform as the primary focus of innovation and excitement.

The Five Prerequisites for Platform Transition

For this transition to happen in the next five years, several critical developments need to occur:

1. First, access must continue to be distributed. Currently, despite the solo accessibility of using AI, real innovation happens when more people can develop on the platform. We need the WordPress moment for AI, tools that democratize AI development the way WordPress democratized web publishing. We’re still a long way from that happening, but the trajectory is clear.
2. Second, offline AI must become a reality. Consider your Google Home or Alexa devices. Even though they’re connected to the cloud, they’re readily available in our homes, using our own data and personalization. Similarly, we need AI in our hands, not just AI apps on phones. This means that processing power, battery life, and model efficiency need significant improvements.
3. Third, security and privacy need major rework. The current model of sending all our data to remote servers for AI processing is unsustainable in the long term. People will demand control over their personal AI interactions, and regulatory pressure will compel the industry to adopt more privacy-preserving approaches.
4. Fourth, speed remains a crucial factor. When quantum computing becomes purchasable at Best Buy, everything changes. The processing limitations that currently constrain AI capabilities will evaporate, opening possibilities we can barely imagine today.
5. Fifth, we need proper multimodal integration. Current AI excels at text, is getting better at images and audio, but struggles with seamless integration across all human communication modes. The platform that succeeds AI will likely not distinguish between text, voice, video, gesture, and thought as separate input methods.

Four Possible Next Platforms

While predicting the future is notoriously difficult, we can make educated guesses about what might replace AI as the dominant platform based on current technological trends and human needs:

Brain-Computer Interfaces (BCIs) are the “Thought Platform.” The most obvious candidate is direct neural interface technology. Instead of typing prompts or speaking commands, we’ll think our intentions directly to our devices. Early versions already exist for medical applications, but consumer BCIs could fundamentally change how we interact with information. Imagine developing applications not through code or conversation, but through pure thought and intention. The platform shift would be about eliminating the interface between human cognition and digital systems. This could make AI feel as clunky as typing on a physical keyboard feels today.

Quantum-Biological Computing as the “Living Platform”: The convergence of quantum computing and biological systems may create something entirely unprecedented, such as computing platforms that grow, evolve, and adapt like living organisms. Instead of training AI models, we might cultivate digital ecosystems that develop their own capabilities organically. These systems wouldn’t just process information; they’d metabolize it, reproduce successful patterns, and evolve in ways their creators never anticipated. The platform shift would move from “programming” to something more like “digital agriculture” or “computational ecology.”

Ambient Reality as the “Environmental Platform” Perhaps the next platform won’t be a device at all, but our entire environment becoming programmable. Beyond AR/VR, this would mean every surface, every space, every object becoming a potential interface and computing resource. Smart matter, programmable environments, and ambient intelligence could make the distinction between “digital” and “physical” completely obsolete. Instead of building apps for devices, we’d be designing experiences for spaces, manipulating reality itself as the development medium.

Portable AI Devices as the “Personal Intelligence Platform”, or more realistically, it’s probably a dedicated AI device. Despite what OpenAI and others claim to be working on, we still have significant areas to solve before we get to truly wearable AI. But logically, that’s the next step. If websites are online marketing and mobile apps are offline, personalized marketing, AI is our online data, so that the natural evolution would be offline, customized data.

Think of it as the progression: we went from accessing information online to carrying personalized tools in our pockets. Now we access AI intelligence online, but the next leap is carrying personalized AI intelligence that works entirely offline, knows us intimately, and operates independently of cloud connectivity.

I spoke about a wearable AI dating tool about 4 years ago, which would be your wingman and connect you with people nearby who have similar devices. Think Bluetooth, dating profile, matchmaker, all in one wearable apparatus.

Think the Star Trek communicator badge.

Whatever it is, it must be a dedicated device designed solely for AI interaction, with the processing power, battery life, and privacy architecture to make it truly personal and truly portable.

The Inevitable Next Platform

What excites me about this perspective isn’t the technology itself, but the reminder that we’re part of an ongoing story of human innovation. Every generation thinks its platform shift is the final one, the technology that will define the future forever. The internet felt permanent. Mobile felt like the ultimate personal computing paradigm. AI feels like artificial general intelligence is the end goal of all human technological development.

But history suggests otherwise. In 10-15 years, we’ll be building on something that makes today’s AI look as quaint as early websites or first-generation mobile apps. Whether it’s direct neural interfaces, quantum-biological systems, ambient reality, or something we haven’t even conceived of yet, the question becomes what we’ll build during AI’s peak years that will serve as the foundation for whatever comes next.

The intoxication will fade. The standards will emerge. The technology will become invisible. And then, inevitably, the next significant platform shift will capture our collective imagination, and the cycle will begin anew. The only constant in technology is that nothing stays constant for long.

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Chris Hood is an AI strategist and author of the #1 Amazon Best Seller “Infailible” and “Customer Transformation,” and has been recognized as one of the Top 40 Global Gurus for Customer Experience.