TOPIC: DURHAM
AI infrastructure under pressure: Outages, power demands and the race for resilience
1st November 2025The past few weeks brought a clear message from across the AI landscape: adoption is racing ahead, while the underlying infrastructure is working hard to keep up. A pair of major cloud outages in October offered a stark stress test, exposing just how deeply AI has become woven into daily services.
At the same time, there were significant shifts in hardware strategy, a wave of new tools for developers and creators and a changing playbook for how information is found online. There is progress on resilience and efficiency, yet the system is still bending under demand. Understanding where it held, where it creaked and where it is being reinforced sets the scene for what comes next.
Infrastructure Stress and Outages
The outages dominated early discussion. An AWS incident that lasted around 15 hours and disrupted more than a thousand services was followed nine days later by a global Azure failure. Each cascaded across systems that depend on them, illustrating how AI now amplifies the consequences of platform problems.
This was less about a single point of failure and more about the growing blast radius when connected services falter. The effect on productivity was visible too: a separate 10-hour ChatGPT downtime showed how fast outages of core AI tools now translate into lost work time.
Power Demand and Grid Strain
Behind the headlines sits a larger story about electricity, grids and planning. Data centres accounted for roughly 4% of US electricity use in 2024, about 183 TWh and the International Energy Agency projects around 945 TWh by 2030, with AI as a principal driver.
The averages conceal stark local effects. Wholesale prices near dense clusters have spiked by as much as 267% at times, household bills are rising by about $16–$18 per month in affected areas and capacity prices in the PJM market jumped from $28.92 per megawatt to $329.17. The US grid faces an upgrade bill of about $720 billion by 2030, yet permitting and build timelines are long, creating a bottleneck just as demand accelerates.
Technical Grid Issues
Technical realities on the grid add another layer of challenge. Fast load swings from AI clusters, harmonic distortions and degraded power quality are no longer theoretical concerns. A Virginia incident in which 60 data centres disconnected simultaneously did not trigger a collapse but did reveal the fragility introduced by concentrated high-performance compute.
Security and New Failure Modes
Security risks are evolving in parallel. Agentic systems that can plan, reason and call tools open new failure modes. AI-enabled spear phishing appears to be 350% more effective than traditional attempts and could be 50 times more profitable, a worrying backdrop when outages already have a clear link to lost productivity.
Security considerations now reach into the tools people use to access AI as well. New AI browsers attract attention, and with that comes scrutiny. OpenAI's Atlas and Perplexity's Comet launched with promising features, yet researchers flagged critical issues.
Comet is vulnerable to "CometJacking", a malicious URL hijack that enables data theft, while Atlas suffered a cross-site request forgery weakness that allowed persistent code injection into ChatGPT memory. Both products have been noted for assertive data collection.
Caution and good hygiene are prudent until the fixes and policies settle. It is a reminder that the convenience of integrating models directly into browsing comes with a new attack surface.
Efficiency and Mitigation Strategies
Industry responses are gathering pace. Efficiency remains the first lever. Hyperscalers now report power usage effectiveness around 1.08 to 1.09, compared with more typical figures of 1.5 to 1.6. Direct chip cooling can cut energy needs by up to 40%.
Grid-interactive operations and more work at the edge offer ways to smooth demand and reduce concentration risk, while new power partnerships hint at longer-term change. Microsoft's agreement with Constellation on nuclear power is one example of how compute providers are thinking beyond incremental efficiency gains.
An emerging pattern is becoming visible through these efforts. Proactive regional planning and rapid efficiency improvements could allow computational output to grow by an order of magnitude, while power use merely doubles. More distributed architectures are being explored to reduce the hazard of over-concentration.
A realistic outlook sets data centres at around 3% of global electricity use by 2030, which is notable but still smaller than anticipated growth from electric vehicles or air conditioning. If the $720 billion in grid investment materialises, it could add around 120 GW of capacity by 2030, as much as half of which would be absorbed by data centres. The resilience gap is real, but it appears to be narrowing, provided the sector moves quickly to apply lessons from each failure.
Regional and Policy Responses
Regional policies are starting to encourage resilience too. Oregon's POWER Act asks operators to contribute to grid robustness, Singapore's tight focus on efficiency has delivered around a 30% power reduction even as capacity expands and a moratorium in Dublin has pushed growth into more distributed build-outs. On the U.S. federal government side, the Department of Homeland Security updated frameworks after a 2024 watchdog warning, with AI risk programmes now in place for 15 of the 16 critical infrastructure sectors.
Hardware Competition and Strategy
Competition is sharpening. Anthropic deepened its partnership with Google Cloud to train on TPUs, a move that challenges Nvidia's dominance and signals a broader rebalancing in AI hardware. Nvidia's chief executive has acknowledged TPUs as robust competition.
Another fresh entry came from Extropic, which unveiled thermodynamic sampling units, a probabilistic chip design that claims up to 10,000-fold lower energy use than GPUs for AI workloads. Development kits are shipping and a Z-1 chip is planned for next year, yet as with any radical architecture, proof at scale will take time.
Nvidia, meanwhile, presented an ambitious outlook, targeting $500 billion in chip revenue by 2026 through its Blackwell and Rubin lines. The US Department of Energy plans seven supercomputers comprising more than 100,000 Blackwell GPUs and the company announced partnerships spanning pharmaceuticals, industrials and consumer platforms.
A $1 billion investment in Nokia hints at the importance of AI-centric networks. New open-source models and datasets accompanied the announcements, and the company's share price surged to a record.
Corporate Restructuring
Corporate strategy and hardware choices also entered a new phase. OpenAI completed its restructuring into a public benefit corporation, with a rebranded OpenAI Foundation holding around $130 billion in equity and allocating $25 billion to health and AI resilience. Microsoft's stake now sits at about 27% and is worth roughly $135 billion, with technology rights retained through 2032. Both parties have scope to work with other partners. OpenAI committed around $250 billion to Azure yet retains the ability to use other compute providers. An independent panel will verify claims of artificial general intelligence, an unusual governance step that will be watched closely.
Search and Discovery Evolution
Away from infrastructure, the way audiences find and trust information is shifting. Search is moving from the old aim of ranking for clicks to answer engine optimisation, where the goal is to be quoted by systems such as ChatGPT, Claude or Perplexity.
The numbers explain why. Google handled more than five trillion queries in 2024, while generative platforms now process around 37.5 million prompt-like searches per day. Google's AI Overviews, which surface summary answers above organic results, have reshaped click behaviour.
Independent analyses report top-ranking pages seeing click-through rates fall by roughly a third where Overviews appear, with some keywords faring worse, and a Pew study finds overall clicks on such results dropping from 15% to 8%. Zero-click searches rose from around 56% to 69% between May 2024 and May 2025.
Chegg's non-subscriber traffic fell by 49% in this period, part of an ongoing dispute with Google. Google counters that total engagement in covered queries has risen by about 10%. Whichever way that one reads the data, the direction is clear: visibility is less about rank position and more about being cited by a summarising engine.
In practice, that means structuring content, so a model can parse, trust and attribute it. Clear Q&A-style sections with direct answers, followed by context and cited evidence, help models extract usable statements. Schema markup for FAQs and how-to content improves machine readability.
Measuring success also changes. Traditional analytics rarely show when an LLM quotes a source, so teams are turning to tools that track citations in AI outputs and tying those to conversion quality, branded search volume and more in-depth engagement with pricing or documentation. It is not a replacement for SEO so much as a layer that reinforces it in an AI-first environment.
Developer Tools and Agentic Workflows
On the tools front, developers saw an acceleration in agent-centred workflows. Cursor launched its first in-house coding model, Composer, which aims for near-frontier quality while generating code around four times faster, often in under 30 seconds.
The broader Cursor 2.0 update added multi-agent capabilities, with as many as eight assistants able to work in parallel, alongside browsing, a test browser and voice controls. The direction of travel is away from single-shot completions and towards orchestration and review. Tutorials are following suit, demonstrating how to scaffold tasks such as a Next.js to-do application using planning files, parallel agent tasks and quick integration, with voice prompts in the loop.
Open-source and enterprise ecosystems continue to expand. GitHub introduced Agent HQ for coordinating coding agents, Google released Pomelli to generate marketing campaigns and IBM's Granite 4.0 Nano models brought larger on-device options in the 350 million to 1.5 billion parameter range.
FlowithOS reported strong scores on agentic web tasks, while Mozilla announced an open speech dataset initiative, and Kilo Code, Hailuo 2.3 and other projects broadened choice across coding and video. Grammarly rebranded as Superhuman, adding "Superhuman Go" agents to speed up writing tasks.
Creative Tools and Partnerships
Creative workflows are evolving quickly, too. Adobe used its MAX event to add AI assistants to Photoshop and Express, previewed an agent called Project Moonlight, and upgraded Firefly with conversational "Prompt to Edit" controls, custom image models and new video features including soundtracks and voiceovers. Partnerships mean Gemini, Veo and Imagen will sit inside Adobe tools, and Premiere's editing capabilities now extend to YouTube Shorts.
Figma acquired Weavy and rebranded it as Figma Weave for richer creative collaboration, and Canva unveiled its own foundation "Design Model" alongside a Creative Operating System meant to produce fully editable, AI-generated designs. New Canva features take in a revised video suite, forms, data connectors, email design, a 3D generator and an ad creation and performance tool called Grow, while Affinity is relaunching as a free, integrated professional app. Other entrants are trying to blend model strengths: one agent was trailed with Sora 2 clip stitching, Veo 3.1 visuals and multimodel blending for faster design output.
Music rights and AI found a new footing. Universal Music Group settled a lawsuit with Udio, the AI music generator, and the two will form a joint venture to launch a licensed platform in 2026. Artists who opt in will be paid both for training models on their catalogues and for remixes. Udio disabled song downloads following the deal, which annoyed some users, and UMG also announced a "responsible AI" alliance with Stability AI to build tools for artists. These arrangements suggest a path towards sanctioned use of style and catalogue, with compensation built in from the start.
Research and Introspection
Research and science updates added depth. Anthropic reported that its Claude system shows limited introspection, detecting planted concepts only about 20% of the time, separating injected "thoughts" from text and modulating its internal focus. That highlights both the promise and limits of transparency techniques, and the potential for models to conceal or fail to surface certain internal states.
UC Berkeley researchers demonstrated an AI-driven load balancing algorithm with around 30% efficiency improvements, a result that could ripple through cloud performance. IBM ran quantum algorithms on AMD FPGAs, pointing to progress in hybrid quantum-classical systems.
OpenAI launched an AI-integrated web browser positioned as a challenger to incumbents, Perplexity released a natural-language patents search and OpenAI's Aardvark, a GPT-5-based security agent, entered private beta.
Anthropic opened a Tokyo office and signed a cooperation pact with Japan's AI Safety Institute. Tether released QVAC Genesis I, a large open STEM dataset of more than one million data points and a local workbench app aimed at making development more private and less dependent on big platforms.
Age Restrictions and Policy
Meanwhile, policy considerations are reaching consumer platforms. Character AI will restrict users under 18 from open-ended chatbot conversations from late November, replacing them with creative tools and adding behaviour-based age detection, a response to pressure and proposals such as the GUARD Act.
Takeaways
Put together, the picture is one of rapid interdependence and swift correction. The infrastructure is not breaking, but it is being stretched, and recent failures have usefully mapped the weak points. If the sector continues to learn quickly from its own missteps, the resilience gap will continue to narrow, and the next round of outages will be less disruptive than the last.
Investment is flowing into grids and cooling, policy is nudging towards resilience, and compute providers are hedging hardware bets by searching for efficiency and supply assurance. On the application layer, agents are becoming a primary interface for work, creative tools are converging around editability and control, and discovery is shifting towards being quoted by machines rather than clicked by humans.
Security lapses at the interface are a reminder that novelty often arrives before maturity. The most likely path from here is uneven but forward: data centre power may rise, yet efficiency and distribution can blunt the impact; answer engines may compress clicks, yet they can send higher intent visitors to clear, well-structured sources; hardware competition may fragment the stack, yet it can also reduce concentration risk.