Europe may be SAP’s home, but it is no longer the place where its future will be decided. That future is shaped elsewhere — in the boardrooms of American multinationals, in the industrial corridors of Asia and in innovation hubs stretching from Silicon Valley to Bangalore. For a company born in Walldorf, Germany, global presence is no longer a strategic option. It is an existential condition.
Altair Worldwide
Global reporting on geopolitics, economics and innovation—from Washington to Beijing.
Under Allison Kirkby, British Telecom is no longer the BT it once was. What began as a domestic restructuring has evolved into something far more consequential: a redefinition of how connectivity itself is organised, governed and valued. Nowhere is this shift more visible than within BT Worldwide.
For decades, Silicon Valley defined the global technology narrative. Startups, venture capital and rapid software innovation drew the world’s attention. Today, a quieter but far more consequential shift is underway. A new configuration is emerging — a triangle connecting the Netherlands, Dallas–Fort Worth in Texas and Bengaluru in India — that is quietly defining the future of deep technology.
Artificial intelligence is no longer a question of if, but of how it will shape the global order. By 2030, AI will underpin economic growth, national security and everyday life. Yet the future is not predetermined. The trajectory of AI depends on political choices, market dynamics and societal values that are unfolding today. Three plausible scenarios illustrate how different paths could lead to very different AI worlds.
Artificial intelligence evolves across three interconnected layers: the geopolitical macro level, the infrastructural meso level and the experiential micro level. Each has its own logic, priorities and constraints. But AI does not develop neatly within these boundaries; instead, the layers collide, creating systemic tensions that shape the trajectory of the technology. These frictions explain why AI policy is difficult, why infrastructure is contested and why everyday adoption is often uneven or unpredictable.
Artificial intelligence may feel abstract, but its impact depends entirely on physical infrastructure. Models run on chips that must be manufactured, trained in datacenters that consume vast amounts of electricity and delivered through global cloud networks that function as the arteries of the digital economy. At the meso level, AI becomes tangible: it lives in server racks, transmission lines, subsea cables and industrial supply chains. This is the layer where strategy, economics and engineering intersect—quietly shaping which nations and companies can compete.
