Oracle’s AI Backlog Surges to $455 Billion

Oracle surprised Wall Street this week with a massive jump in its AI-related backlog, sending shares soaring nearly 29%. The company revealed that its “remaining performance obligations” (RPO) linked to AI infrastructure reached $455 billion in Q1, up sharply from $138 billion previously. This backlog, a measure of future contracted revenue, reflects soaring demand for AI-driven cloud services and server rentals.

While Oracle missed consensus expectations in some areas of cloud revenue, investors zeroed in on the AI surge. Analysts pointed out that enterprises are increasingly turning to Oracle’s infrastructure to host and train large AI models, a space long dominated by hyperscalers like Microsoft Azure and AWS. The jump suggests Oracle is carving out a durable niche in the global AI arms race.

For finance, this is more than a single-stock story. A backlog of this size signals multi-year AI investment commitments from corporates, a trend that will ripple across capex cycles, lending markets, and tech valuations. Oracle’s results show that AI demand is still outpacing even bullish forecasts, though questions remain about how much of this backlog will translate into realised revenue.

Goldman Sachs Warns of AI Capex Slowdown

Just as investors were digesting Oracle’s blockbuster results, Goldman Sachs delivered a colder note: AI spending may not be a one-way rocket ship. In a research note, the bank warned that capital expenditure growth in AI could slow sharply from late 2025 into 2026.

Goldman estimates that if AI spending growth drops back toward pre-2024 levels, it could trim S&P 500 sales forecasts by as much as 30%. The bank argues that while companies rushed to build data centres and secure GPU supply in 2024-2025, there is a natural ceiling to how much infrastructure can be deployed before supply exceeds demand.

The warning comes as valuations across Big Tech hover at historic highs. If the spending slowdown materialises, equity markets could face a period of painful multiple compression, especially for firms whose stock prices are predicated on uninterrupted AI-driven growth. For finance professionals, the message is clear: AI is not immune to the classic boom-and-bust dynamics of technology investment cycles.

Anthropic CEO Reignites Debate on White-Collar Job Losses

Anthropic’s CEO Dario Amodei re-upped one of the most controversial predictions in the AI debate: the widespread loss of entry-level white-collar jobs. In comments this week, Amodei warned that AI will automate large portions of roles in law, finance, consulting, and administration within the next five years.

The remarks have reignited discussions among corporate leaders and policymakers. For professional services firms, the risk is not just staff displacement, but the erosion of the traditional talent pipeline. If entry-level positions shrink dramatically, where will the next generation of partners, executives, or dealmakers come from?

Markets are also weighing the long-term productivity implications. On one hand, firms may see cost savings and efficiency gains. On the other hand, widespread displacement could dampen consumer spending and spark regulatory intervention. Amodei’s comments remind investors that while AI is often sold as an opportunity, its impact on the labour market, particularly white-collar finance roles, could be disruptive enough to reshape entire sectors.

Lazard Puts AI at the Heart of Its 2030 Strategy

Investment bank Lazard has laid out a long-term vision that puts AI front and centre. CEO Peter Orszag announced this week that AI will play a pivotal role in “Lazard 2030,” the firm’s roadmap to double returns over the next five years.

The plan includes embedding AI across advisory services, deal-making, and operations, alongside selective hiring of dealmakers and new leadership appointments. Lazard is betting that AI-augmented research, analytics, and client interaction can create a competitive edge in an industry still heavily reliant on human expertise.

For the wider financial services landscape, Lazard’s announcement is notable because it reframes AI not just as a back-office tool but as a strategic differentiator in front-office functions. If the experiment succeeds, other mid-tier advisory firms could follow suit, leading to an acceleration of AI adoption in M&A, restructuring, and capital markets advisory. It’s a sign that AI is no longer confined to tech balance sheets; Wall Street is now making it a core pillar of its growth strategies.

Robinhood CEO: AI Won’t Replace Human Traders

Finally, in a week dominated by bold AI headlines, Robinhood CEO Vlad Tenev struck a more cautious tone. Speaking to Business Insider, Tenev argued that while AI will transform trading and investing platforms, it will not replace human judgment.

Tenev stressed that trading is as much about emotion, conviction, and behavioural nuance as it is about data. He positioned AI as an augmentation layer, providing insights, speeding up execution, and personalising experiences, but not a substitute for human decision-making. Robinhood, he added, is developing new social features that allow users to share and follow trades, a direction that emphasises community alongside AI.

The comments serve as a reminder that not every player in finance sees AI as a wholesale replacement for human roles. For investors, it underscores a key thesis: platforms that strike the right balance between AI automation and human agency may be best positioned to capture long-term trust in retail trading.