Factories and governments are embedding AI into real workflows—from robotics in manufacturing to coding assistants in UK departments. Big tech is doubling down on infrastructure, with Microsoft pledging £22B for UK supercomputing. Energy use and CO₂ emissions rise alongside growth, while adoption slows slightly as ROI and fatigue set in. AI is no longer optional—it’s becoming core infrastructure and workflow.
Global shipping companies are turning to AI to prevent fires caused by mis-declared hazardous goods like lithium batteries. New systems now scan cargo bookings in real time, flagging suspicious or incomplete entries before containers are loaded.
The initiative, backed by major insurers and freight organisations, comes after a sharp rise in shipboard fires tied to undeclared dangerous cargo. Fires at sea are among the costliest and deadliest risks in global logistics, often causing billion-dollar losses and endangering crews.
Why it matters: Shipping moves ~90% of global trade, and even small safety gains have huge ripple effects. AI here isn’t flashy—it’s practical, preventive, and life-saving. By embedding risk detection into booking systems, the industry may avoid catastrophic accidents while insurers push for safer compliance worldwide.
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Manufacturing automation growing fast
Factories worldwide are adopting AI-driven robotics for assembly, quality checks, and predictive maintenance. Examples range from shampoo bottling to advanced battery production. The pitch: fewer breakdowns, faster throughput, and improved safety. Adoption is accelerating in Asia and Europe, with US firms catching up to stay globally competitive.UK Govt Trial of AI Coding Assistants
Over 1,000 tech staff in 50 UK government departments tested tools like GitHub Copilot and Google Gemini Code Assist between Nov 24–Feb 25. Developers saved ~1 hour/day on average, but only ~15% of auto-generated code was usable without edits.CO₂ Emissions from Google’s New Essex Datacentre
Google’s planned hyperscale data centre in Thurrock, Essex (52 hectares) would emit ~568,727 tonnes CO₂/year—around 500 short-haul flights weekly. It raises environmental, power-use, and sustainability questions as AI infrastructure expands.£22B Microsoft Investment in UK AI Supercomputing
Microsoft pledged £22bn over 4 years for supercomputing and data centres in the UK using ~23,000 Nvidia chips. This is part of a larger £31B wave of big-tech investment tied to the UK-US “Tech Prosperity Deal.” It underscores how compute power is now strategic infrastructure.Big Tech Deals (£31B) Focused on AI, Not Crypto
In recent UK-US partnerships, while AI and compute got huge investment (£31B+), crypto policy was explicitly de-emphasized. The moves show governments prioritising infrastructure, standards, and sovereignty in AI over speculative / volatile sectors.AI spending forecast
Gartner projects global AI spending will reach $1.5 trillion in 2025, up nearly 25% year-over-year. Growth is led by cloud AI infrastructure, enterprise agents, and customer support automation. Notably, small and midsized businesses are catching up, prioritizing low-cost, specialized AI tools rather than giant general-purpose models.AI adoption dipping among large firms
Despite the spending surge, U.S. Census Bureau data shows AI use among large companies has dipped slightly, from 13.5% to about 12%. Analysts suggest “pilot fatigue,” rising costs, and unclear ROI are to blame. Enterprises want proof of value before scaling further, signaling a more cautious phase.
🛠️ Tool of the Week
Agentic AI & Autonomous Agents
Workday’s agents (for HR, recruiting etc.) are a good case study of what is meant by “agentic AI” — systems that take goals and act semi-autonomously rather than just returning predictions.
Benefit: can automate repetitive workflows, free up human time, speed up decisions.
Risk/Challenges: oversight, alignment (does the agent do what we intend), bias, transparency, cost of errors.