Call it lazy. Call it an obsession. Call it a lazy obsession. For the past couple of years, everyone with a keyboard, the X app and half an opinion, insisted Apple was “behind” on artificial intelligence (AI). Apparently, barometers of success include having a frontier model to chest thump about, a founder or CEO doing the podcast circuit to explain why artificial general intelligence is just five minutes away, hyperscale capex flex, as well as dramatic product demos videos. Apparently, Apple was behind. Apple had missed the moment, we were told.. It turns out that Apple didn’t “lose” the AI race. (Reuters). Microsoft pumped billions into OpenAI. Google scrambled to embed Gemini into every app they have. Nvidia’s market cap went vertical for a while as every Silicon Valley startup fought for H100s like they were the last bottles of water in a desert (it was, as the cool kids call it, FOMO or the fear of missing out). Through it all, Apple simply sat. They talked about things that weren’t as cool, such as Machine Learning. The experts on X told the world Tim Cook had missed the greatest shift in computing history. But as we stand here in 2026, the dust settling, and a clearer picture that’s emerging looks a whole lot different.. Also Read: Tech Tonic | Apple MacBook Neo is something Windows PCs may never be. It turns out that Apple didn’t “lose” the AI race. They played a patient, waiting game (something most don’t really understand), letting AI companies clear the landmines, make the roads and discover the complexities of costs and regulation while at it. And now, Apple is free to drive in, and it is their choice whether they insist on doing that in a tank, or a Ferrari Purosangue. That being said, there is a need to speed up Apple Intelligence development, something they’ve been consistently doing—for instance, expanded language support announced last year.. But Apple must play the optics game too, particularly with Gemini being so nicely integrated in Android, for a while now. One could perhaps argue the patience element stretched on a bit longer than perhaps ideal, also because of the Android context. Apple and Google will now build the next generation of Apple Foundation Models, based on Google’s Gemini models, and these arrive later in the year. This will be a pivotal moment.. The biggest misconception about the AI race was that you simply had to build the biggest model to win. For two years, Nvidia, Microsoft, OpenAI, Oracle, Alphabet, Meta, Amazon, Tesla and dozens of unicorns collectively burned trillions of dollars (and counting) on research and development, data centres, and eye-watering energy bills required to train Large Language Models (LLMs). Though Chinese AI company DeepSeek did provide a timely context, early last year.. Analysts J.P. Morgan’s 2026 Outlook specifically cited that the hyperscalers (Microsoft, Google, Meta, and Amazon) had crossed the $1.3–$1.4 trillion mark in combined R&D and AI
