Big Tech Spends Big on AI

Microsoft, Meta, Amazon, and Alphabet began Q2 with aggressive capital investments into AI. Microsoft boosted CapEx by 78% YoY to nearly $22.6 billion, citing Azure and cloud AI services growth. Amazon invested around $16.5 billion, and analysts expect its fiscal 2025 total CapEx to top $60 billion, mainly for AI-centric AWS expansion. Meta spent approximately $8.5 billion, including upgrades to its datacenter footprint and AI capacity, and Google (Alphabet) increased capital spending by 91% YoY to $13.2 billion, driven by new cloud regions, TPUs, and scalable infrastructure.

While these investments boosted investor confidence, pushing Microsoft near a $4 trillion valuation and expanding market share for others, not all earnings reports were positive. Amazon’s AWS growth stagnated due to capacity constraints and shrinking margins despite the CapEx surge, and Microsoft’s Intelligent Cloud fell short of revenue expectations, signalling that capacity isn’t delivery until it’s lit up and monetised.

Financial services professionals see the scale of these AI investments and hear "innovation," but we need to be asking: what’s the return on this spend? For asset managers and ESG teams, the equivalent value comes from sharper compliance, faster reporting, and smarter insights, not from the size of model logs or GPU farms.

OpenAI Builds Its First European AI Data Centre in Norway

OpenAI, in partnership with Aker ASA and Nscale Global, has broken ground on “Stargate Norway”, its first European AI hyper-scale facility near Narvik. Initially powered by renewable hydropower, the centre will house 100,000 Nvidia GPUs by late 2026 and may scale up to one million GPUs, consuming up to 520 MW. The facility includes liquid cooling and excess heat recovery for local industry. Designed for regional data sovereignty compliance, low-latency AI delivery, and sustainable operations, Stargate Norway marks OpenAI’s broader plan to build hyperscale compute in the UAE and the US.

The project has drawn mixed reactions domestically: whilst hailed as transformative for European AI independence, critics cite concerns over power grid strain and local environmental impact. Nevertheless, the Norwegian government has supported it for long-term economic and digital infrastructure benefits.

Hosting AI infrastructure locally matters for regulated sectors such as finance and ESG compliance, and local data centres reduce latency and boost trust through clear jurisdictional governance. At GaiaLens, we see this infrastructure shift as a tangible movement toward greater accountability, and a reminder that AI isn’t just about models, but also responsible operations.

Italy Investigates Meta Over WhatsApp AI Assistant Integration

Italy’s competition watchdog AGCM has launched an investigation into Meta over its decision to integrate the Meta AI chatbot directly into WhatsApp’s search bar, without user consent. Regulators allege that Meta is leveraging its dominance to steer users into its AI assistant by default, potentially violating EU competition laws around bundled services. These moves included raids on Meta’s Milan offices by the Guardia di Finanza.

Meta defends the integration as “free access” to AI for billions of users, but critics counter that automatic placement undermines choice, limits rival AI platforms, and could form a basis for future monetisation via forced defaults. Italy’s probe mirrors broader EU concerns about self-preferencing and ecosystem control.

When AI starts to auto-inject into products, regulators take notice. Financial firms integrating AI into investment platforms should heed this; embedding AI features without transparent user opt-ins can trigger legal risk. Compliance isn’t just technical, it’s also regulatory and ethical. Meta’s investigation is a warning: AI integrations in finance must be designed with user consent and openness from day one.

EU Issues Guidelines for High-Risk AI Under the AI Act

The European Commission has published operational guidance for AI systems deemed “high‑risk” under the upcoming AI Act, which kicks in starting August 2025. This includes models from providers like OpenAI, Google, Meta, and Anthropic. Entities must now undergo risk assessments, adversarial testing, incident logging, energy-efficiency reporting, and bias mitigation checks. Transparency requirements also mandate detailed technical documentation, training data summaries, and governance protocols. Failure to comply could result in fines up to €35 million or 7% of global turnover, and regulators are emphasising the need for systematic controls well before deployment.

This is not a future risk; it’s happening now. AI models used in finance or ESG that carry systemic impact must be auditable, robust, and transparent by regulation, not by marketing. At GaiaLens, we believe ESG tools must treat transparency as foundational, not optional. If your platform or compliance workflow can’t generate incident logs, energy reports, or risk assessments, you’re running blind, and regulators now expect that visibility.

EU Commits €30B to Build Gigawatt AI Data Centres

The European Commission has pledged €30 billion to build a network of gigawatt-scale AI data centres across the European Union by 2025-2026. The initiative aims to match US and Chinese compute capacity, with the first phase committing €10 billion toward 13 proposed sites in 16 member states, with each centre being capable of housing over 100,000 GPUs and scaling further. The bid is part of broader infrastructure programmes like InvestAI and EuroHPC, seeking to enhance European AI sovereignty and support domestic innovation. Although plans have drawn interest from 76 bidders, concerns persist around energy demand, operational feasibility, and integration with local grid systems.

Massive compute capacity may power future breakthroughs, but insight demands efficiency too. In finance, the key lies in models that deliver relevance, not raw horsepower. Scaling AI infrastructure is necessary, but not sufficient. At GaiaLens, we build for precision: lean, explainable, and tailored intelligence, not unnecessary scale.