337 Imagine, for a moment, how different your next week would look if there were no internet. Every facet of modern life – how we work, how we communicate, how we govern, and more – would likely be turned on its head. The internet has been woven into so many facets of life, big and small, that – for many – it is difficult to imagine a world without it. In the next decade or two, imagining a world without AI will likely feel the same. Artificial intelligence is reshaping the modern landscape at breakneck speed. What began as research has scaled into emerging core infrastructure across industries – powering everything from customer support to software development, scientific discovery, education, and manufacturing. This document has aimed to map the pace and breadth of AI’s expansion, with particular focus on usage trends, cost dynamics, infrastructure buildout, and early monetization models. The through-line is clear: AI is accelerating, touching more domains, and becoming more embedded in how work gets done. Catalyzing this growth is the global availability of easy-to-use multimodal AI tools (like ChatGPT) on pervasive mobile devices, augmented by a steep decline in inference costs and an explosion in model availability. Both closed and open-source tools are now widely accessible and increasingly capable, enabling solo developers, startups, and enterprises alike to experiment and deploy with minimal friction. Meanwhile, large tech incumbents are weaving AI deeper into their products – rolling out copilots, assistants, and even agents that reframe how users engage with technology. Whether through embedded intelligence in SaaS or agentic workflows in consumer apps, the interface layer is being rewritten in real time. On the compute side, investment continues to scale dramatically. Capital expenditures across major cloud providers, chipmakers, and hyperscalers have hit new highs, driven by the race to enable real-time, high-volume inference at scale. The investment is not just in chips, but also in new data centers, networking infrastructure, and energy systems to support growing demand. Whether this level of capital expenditure persists remains to be seen, but as AI moves closer to the edge – in vehicles, farms, labs, and homes – the distinction between digital and physical infrastructure continues to blur. The global race to build and deploy frontier AI systems is increasingly defined by the strategic rivalry between the United States and China. While USA companies have led the charge in model innovation, custom silicon, and cloud-scale deployment to-date, China is advancing quickly in open-source development, national infrastructure, and state-backed coordination. Both nations view AI not only as an economic tailwind but also as a lever of geopolitical influence. These competing AI ecosystems are amplifying the urgency for sovereignty, security, and speed… Summary…