Author: Wilhelm Friedrich
Edge computing has quietly become foundational infrastructure for manufacturing, retail, healthcare, and AI deployment. The architectural shift is producing real commercial value — largely without the hype around other transitions.
The space economy crossed $570 billion in 2024 and is on track for $1.8 trillion by 2035. Satellite services, launch, and orbital infrastructure are now strategic infrastructure with implications well beyond aerospace.
Quantum computing has been ten years away for two decades. But 2024–2025 progress on error correction has narrowed the gap. For most businesses, quantum isn’t yet operational. For specific industries, the time to engage has arrived.
The gig economy was meant to be temporary. Fifteen years later, it has institutionalised. For workforce strategy in the late 2020s, contingent work is no longer optional to plan for — it’s central.
AI companies are commanding 20–30x revenue multiples. Some are justified by genuine moats and market scale. Many are not. Distinguishing between the two is the most consequential investment question in technology right now.
The Strait of Hormuz carries 20% of global oil and all of Qatar’s LNG. Iran’s April 2026 tanker seizure pushed Brent above $105. The risk is permanent — and most businesses aren’t managing it.
As enterprises race to deploy AI agents across their operations, they are inadvertently creating a new class of security vulnerability that conventional cybersecurity frameworks were not designed to address. The hidden cost of AI deployment is not just compute and talent — it is an expanded attack surface that grows with every agent you add.
NVIDIA controls roughly 80 per cent of the AI accelerator market — a concentration that is now prompting the world’s largest technology companies to build their own silicon. The shift from monolithic GPU clusters to modular chiplet architectures is not a distant forecast: it is already reshaping enterprise procurement, investment strategy, and the competitive dynamics of AI at scale.
AI sovereignty has moved from the margins of technology policy into the boardroom agenda of every serious multinational. With 93 per cent of global executives calling it mission-critical and at least 34 countries enacting data localisation rules, the question is no longer whether to build a sovereign AI strategy — but how fast.
Global semiconductor revenue is set to exceed $1.3 trillion in 2026 — the highest growth rate in two decades — as DRAM prices surge 125% and NAND flash climbs 234% year-on-year. For business leaders outside the technology sector, the chip super-cycle is no longer a supply chain footnote: it is a balance-sheet emergency hiding in plain sight.