New Constructs warns investors to focus on AI profitability over compute capacity

NASHVILLE, Tenn., As major cloud operators prepare to invest $1.2 trillion in artificial intelligence (AI) infrastructure by 2027, financial technology firm New Constructs warns investors to focus on the economic value and profitability of AI, rather than just the amount of compute capacity a company owns.

According to Morgan Stanley, a small group of the world's largest cloud operators is expected to allocate significant resources to AI infrastructure next year. However, New Constructs CEO David Trainer emphasizes that the true measure of success lies in the proprietary data and workflows that can convert that investment into measurable profits.

"AI infrastructure is an input, not a moat," Trainer stated. "Investors should focus on whether a company can create an advantage that competitors cannot replicate and whether that advantage generates returns above the cost of capital."

Trainer argues that simply building AI capacity does not automatically translate into pricing power, customer value, or economic profitability. The investment community must evaluate whether AI deployments are producing tangible results, such as differentiated research outcomes, cost savings, improved margins, or increased revenue.

"Without showing these results, the market may be overpaying for AI capacity before knowing if adequate future cash flows will materialize," Trainer explained.

While access to foundational models is essential for AI adoption, the real value lies in the "harness" and application layers that utilize proprietary data and workflows. New Constructs cites examples like Hims & Hers CEO Andrew Dudum and investor Chamath Palihapitiya, who argue that the ability to apply proprietary data to specialized problems can create a more durable source of differentiation.

"Public models learn from information everyone can access," Trainer said. "The data that nobody else has is where a company can create an edge. Giving it away can mean giving away the business model."

New Constructs highlights the example of Palantir, a data analytics company that has structured its business around proprietary customer data. Its $10 billion Army software and data contract illustrates the demand for systems that can structure and apply AI tools to create value with proprietary information.

However, even with high demand, the valuation question remains. As of August 29, 2022, Palantir's stock price of $187 per share implies profit growth of approximately 20% compounded annually for more than 30 years, or 35% compounded annually for more than 15 years. Trainer noted, "The right question is not whether a company is good. The question is what the market is already pricing in. A strong business can still be a bad stock when the expectations embedded in its price are too difficult to meet."

FinSights, a collaboration between New Constructs and Google Cloud, demonstrates how AI can support investment analysis when grounded in trusted, auditable data. By integrating Google Cloud technology, FinSights provides a delivery layer for New Constructs' proprietary investment research data.

Trainer sees AI following a similar path to electricity: essential to society, but not necessarily a profit pool captured by the companies that build the underlying infrastructure. "For investors, the question is not whether AI will be widely used. It is whether a company can turn AI into services, workflows, or insights customers will pay for at margins that justify the investment," Trainer said. "Trillions of dollars in AI spending are not profits. They are costs that still must be earned back. The winner is not whoever spends the most. It is whoever can turn proprietary data into services competitors cannot easily replicate."

New Constructs, an independent financial technology firm, combines forensic accounting expertise with patented AI technology to analyze SEC filings and financial disclosures. The firm's research drives live-traded indices that dramatically outperform the S&P 500 and automates financial modeling and investment ratings across more than 10,000 securities.