Published on Wednesday 2 July, 2025, via incontext.digital
TLDR
- Platform shifts are fundamentally about new tech becoming reliably available at a predictable, accessible cost; fostering trust and experimentation
- AI is unique in that it constitutes two platform shifts
- The first platform shift is technological; commoditising natural language as a building block. Thus making it easier to integrate with the ‘fuzzy’ real world. Thus holding the potential to transform virtually every service, applications and business.
- The second shift is societal in nature; getting used to machines doing what we previously (proudly) did not imagine a machine capable of doing
“AI is a radical platform shift”. We have been hearing this for a decade. A lot more these last three years. And so much more the last three months.
Yet, with so much talk about ‘shift’, I’m often confused as to what that means. What constitutes a platform shift? Hell, what does ‘platform’ even mean?
Start with the foundation
"Platform" is one of those wonderfully vague words. You can stretch it to fit almost anything – the internet, an OS, an online marketplace like Uber. For me, when I cut through the noise, a ‘platform’ is simply a foundation. It's something stable and predictable enough that you can rely on it to build something else on top. Think of the electric grid: you plug in an appliance trusting the power will be there, consistent and reliable, without a second thought. That’s a platform – a bedrock you can build upon.
Consider the telegram. Not the messaging app, the old-fashioned “analogue” messaging service. This wasn't a single invention but a stack of innovations, big and small, from understanding electromagnetism to the operational know-how of amplifying signals. The telegram itself was built upon the earlier platform shift of widely available electricity. And what did the ‘platform’ of the telegram enable? Messages at virtually zero marginal cost, zipping across the country almost instantly. It famously bankrupted the Pony Express in what felt like a week. More profoundly, these cheap, fast messages supercharged commerce by enabling businesses to coordinate activities across vast distances, accelerated the spread of news which shaped public opinion, and allowed for the management of larger, more complex organizations. It was a catalyst.
The platform shift of the telegram was about the consistently predictable price and availability of service. It became something you could reliably use, a dependable tool at your disposal.
And this is what a platform shift is truly about: economic viability and accessibility, fostering enough trust that others view the new technology as a reliable tool. New tech gets invented all the time. Brilliant ideas often simmer for years. But the shift? That only happens when the cost of using that technology drops, when it moves from the R&D labs and the hands of a few into the grasp of many. It’s when it stops being a precious, prohibitively expensive artifact and starts becoming a tool – something to experiment with, something you can even afford to ‘waste’ a bit, to play around with, without betting the entire farm.
Platform shifts, therefore, are about unleashing experimentation. They mark the transition from "Can I even touch this?" to "What if I could…?". A platform shift in itself doesn’t hold intrinsic value; it holds potential for value creation. It’s like a powerful new drill in a workshop; the excitement isn’t just the drill itself, but what we can now build with it because the technology has become cheap enough, and consistent enough, to take that leap of faith.
The AI shift is different
Which brings me to AI. It feels different. The buzz around this is louder, more persistent. What explains this?
Like any ‘platform’ that came before it – PCs, the internet, cloud, mobile – AI is built on a stack of pre-existing technologies and innovations. It relies on the vast datasets from the internet, our collective digital literacy (we’re all comfortable with chat apps, aren't we?), and countless innovations in machine learning and chip design. And AI, like its predecessors, holds the promise of enabling vastly new tools, services, and businesses.
But that alone doesn’t explain the persistent, almost feverish buzz that has surrounded AI for years, a hum that seems to grow louder by the day. I believe that extraordinary energy comes from the human-ness we instinctively ascribe to current AI, particularly language models. Using ChatGPT feels uncannily human. We see its outputs and attribute to it human-like abilities, creativity, even understanding. And in turn, we affirm our own amazement with what we perceive as its creative power. We are rapidly getting used to a technology that feels human, even though we intellectually know it is not.
It is this anthropomorphism that explains the buzz, I believe. It is the continuing amazement at creativity that fuels inspiration and concern. It is these human-like abilities we don’t quite know how to make sense of. And therefor it is these abilities that keep us circling back to the potential disruption of AI. Especially for us technologists.
It’s a more philosophical fascination, and it’s this abstract quality that can also make the conversation feel a bit unmoored. Because for all the exciting experiments and breathless talk, we are still in the early days of seeing how AI will fundamentally reshape the fabric of our daily lives and work. I, for one, am incredibly excited to find out.
The two platform shifts
And this is why AI, I believe, constitutes two platform shifts rolled into one.
The first shift is purely technical, fitting the classic model. It’s about the underlying technology and the new potential it unlocks. Large Language Models are making language itself a programmable, malleable material. This allows us to bypass traditional complexities in software development – often skipping the need for intricate data integration scripts or complex user interfaces for a whole range of tasks. Because language is so fundamental to nearly everything we do, the applicability of this technical shift is almost boundless, promising disruption and innovation across countless domains.
The second platform shift is driven by this anthropomorphism. Perhaps "paradigm shift" is a more accurate term here, as it’s more about a change in our societal relationship with technology. It’s about us getting used to the idea of machines performing tasks – logical, creative, conversational – that we once considered uniquely human. Remember the Mechanical Turk in the 18th century? Though ultimately a clever hoax, its illusion of a chess-playing automaton captivated imaginations. It wasn't about the reality of that specific machine, but about the idea it sparked – what if machines could reason, strategize, create? That captivation, that speculative wonder, is mirrored today with AI. Our amazement at what AI appears to do fuels an immense creative and speculative energy, even if we're still figuring out its true nature and limits.
It is this second, more paradigm-shifting aspect – our continued amazement at machines doing what we previously thought only humans could – that fuels so much of the intensity in today’s ‘platform shift’ discussions.
Personally, I’m extremely excited about how the ‘technological commoditization’ of natural language via AI can disrupt services, applications, and fundamentally change how we interact with information and systems. But I confess, I am perhaps even more excited by the sheer energy, creativity, and boundless curiosity that this era of increasingly anthropomorphized tech inspires.