Investment Outlook: Show me the money – the AI edition

In the 1990s movie Jerry Maguire, the famous line “Show me the money” wasn’t just about cash - it was about proving commitment and having the courage to back what you believe in. Today, that same expectation echoes across Wall Street, as investors look for evidence that the money poured into AI is worth it. They are also watching the risks tied to funding the AI infrastructure boom, as evidence by the recent rising borrowing costs (i.e. corporate bond spreads) of large-cap AI names. We consider the drivers and risk of AI below.

It is difficult to know for certain whether AI can significantly enhance company profitability. However, an academic paper published by Cornell University in October, provides some evidence to support this. Unlike most Generative AI research that focuses on making work more efficient, the authors examined demand to assess GenAI’s impact on revenues. Using data from one of the world’s largest cross-border online retail platforms, the study provides large-scale, real-world evidence on GenAI’s impact on productivity. It shows that value comes from interconnected routines and highlights GenAI’s role in boosting revenue by influencing consumer behaviour.

In 2023-24, the researchers conducted randomised field experiments, involving millions of users to test GenAI integration across seven consumer workflows on an e-commerce platform. Four of these workflows produced significant revenue gains. The most impactful was AI-powered pre-sale chatbots, which provided automated, real-time support to customer queries and drove a 16% increase in sales¹. AI improvements included refining search queries to match consumer intent, generate tailored product descriptions and crafting targeted marketing messages.

Revenue improvements from AI were primarily driven by a stronger consumer experience and fewer market frictions, with up to 22% more browsers converting into buyers. The gains were especially evident among smaller sellers and less experienced buyers². This underscores GenAI’s potential to close capability gaps in companies and help under-resourced businesses compete in digital marketplaces, while expanding their customer base.

Introducing AI into the real economy is a delicate balancing act. It can boost company profits, but it also poses risks to jobs. If AI replaces workers, a larger share of income flows to back into the business, rather than to employees, widening the gap between profits and worker compensation. The challenge is whether this imbalance can persist without destabilising the economy. Broadly speaking, the possible outcomes are binary.

A bearish outcome: AI rapidly transforms production by replacing labour but productivity gains are short-lived. Unemployment increases, reducing consumption, triggering a cyclical downturn. This could lead to a US recession with stock markets likely to fall on expectations of lower future growth. AI-related companies particularly suffer due to elevated valuations and cuts on capital spending.

A bullish, sustainable outcome: A longer capital expenditure cycle with sustained productivity gains allows the economy to adjust gradually, supporting both job creation and wage growth. This aligns with historical innovation patterns and suggests a healthier balance between capital investment and labour market stability. In this case, AI-driven growth is more likely to be inclusive and durable, with tech reinvestment fuelling broader GDP expansion. Continued economic growth should allow stock valuations to rise, albeit from elevated levels, and drive further equity gains.

From the available data, the bullish outcome appears more likely. Gradual AI integration, combined with reinvestment and sustained productivity gains, supports a multi-year growth cycle. AI firms are already profitable, and micro-level evidence shows adoption lifts margins, pointing to stronger earnings and rising valuations.

With infrastructure costs soaring into the hundreds of billions, tech giants are turning to innovative financing models that allow them to scale up investment without overloading balance sheets with debt. Meta Platforms offers a prime example. In October, the tech giant raised $60 billion for AI infrastructure, split evenly between a $30 billion corporate bond issuance and a $30 billion off-balance-sheet deal with Blue Owl Capital³. The latter was structured through a Special Purpose Vehicle (SPV) to fund the $27 billion Hyperion data centre in Louisiana⁴. Meta Platforms retains operational control and a minority equity stake, but avoids taking on the debt directly. This allows the company to preserve its investment-grade rating while accelerating expansion.

OpenAI (the creator of ChatGPT, an AI language model that understands and generates human-like text) is pursuing an even more ambitious path and has committed over $1.4 trillion investment in AI infrastructure over the next eight years⁵. Its strategy leans heavily on capital injections from Microsoft, SoftBank, and Oracle, alongside partnership-based deals with cloud companies, such as CoreWeave and Amazon Web Services. Despite speculation, OpenAI has ruled out a public listing for now, focusing instead on monetising AI through enterprise tools, cloud services and future consumer applications.

Off-balance sheet financing is gaining traction because it offers clear advantages. It preserves a company’s credit quality by keeping debt off the books, enables companies to scale faster without impacting leverage ratios (and possibly credit ratings) and attracts private credit investors seeking high-yield, asset-backed returns.

Yet these structures carry risks. They are complex and can obscure true financial exposure. The structure relies on long-term cash flows which create refinancing risks if AI monetisation lags. Investors will be especially sensitive to the news flow from AI financing over the coming quarters and years. After OpenAI CEO Sam Altman denied seeking U.S. government loan guarantees for infrastructure investments, AI stocks experienced heightened volatility in November.

The AI revolution is reshaping corporate finance and productivity. Early evidence shows GenAI can deliver real revenue gains. Yet, risks are building, including changes to business practices, opaque financing structures and workforce disruption. For investors, the mantra remains the same as in Jerry Maguire: “Show me the money.” In the coming quarters, that proof will be more critical than ever.

1,2 Cornell University, Generative AI and Firm Productivity: Field Experiments in Online Retail, 10 October 2025

3,4 Techstartups.com, The hidden debt behind the AI boom: How Meta and xAI are quietly raising billions to finance AI investments, October 2025

5 The Tech Buzz, OpenAI hits $20B ARR, commits $1.4T for AI infrastructure, November 2025