Money never sleeps, but it is learning to think. At 200 West Street, the traditional power corridors of Goldman Sachs are vibrating with a new kind of energy. It is not the frantic shouting of the trading floor. It is the hum of server farms. On November 14, 2025, the firm closed the week with its stock priced at $787.01, a figure that masks a deeper transformation. David Solomon is no longer just running a bank. He is presiding over a decade-long pivot where capital is being pulled from human intuition and poured into silicon.
The Billion Dollar Infrastructure Bet
Goldman is following the money into the ground. Literally. Recent reports indicate the firm is raising massive debt and equity to develop private power campuses in South Dallas. These are not standard office buildings. They are modular, natural-gas-fired power plants designed to feed the insatiable appetite of AI data centers. This is the hardware reality of the 10-year playbook. The bank has realized that owning the algorithm is useless if you do not control the electricity that runs it. By moving into AI infrastructure, Goldman is hedging against the very energy volatility that its own analysts predict for 2026.
Efficiency Gains and the Death of the Pitchbook
The junior analyst is an endangered species. Inside the investment banking division, the 10-year strategy is already cannibalizing manual labor. Tasks that once required forty hours of spreadsheet modeling and pitchbook formatting are now being compressed into minutes. This is not just a marginal improvement. It is a fundamental shift in the cost of doing business. During the Q3 2025 earnings call, the firm reported total net revenues of $15.18 billion, a 20 percent jump from the previous year. More importantly, net interest income surged 64 percent to $3.85 billion. The efficiency ratio is improving because the bank is replacing high-cost human capital with scalable, low-cost AI agents. The risk is no longer about human error in a formula. It is about the black box of the model itself.
Navigating the Regulatory Minefield
Regulators are watching the machines closely. The Securities and Exchange Commission is currently aggressive in its pursuit of what Chair Atkins calls AI washing. This refers to firms making inflated claims about their machine learning capabilities to pump stock prices. Goldman has stayed ahead of the curve by integrating AI into its core risk management systems, yet the SEC’s proposed rules on predictive data analytics create a new hurdle. If a model prioritizes the bank’s profit over a client’s interest during an automated trade, the legal fallout could be catastrophic. The reward of hyper-efficiency comes with the risk of systemic algorithmic bias that no compliance officer can fully audit in real time.
| Metric | Q3 2024 | Q3 2025 | Change (%) |
|---|---|---|---|
| Net Revenue | $12.65B | $15.18B | +20% |
| Net Interest Income | $2.35B | $3.85B | +64% |
| Earnings Per Share (EPS) | $8.40 | $12.25 | +46% |
The Wealth Management Arms Race
Personalization is the new battleground. Goldman’s 10-year playbook isn’t just for the institutional giants. It targets the high-net-worth individual. By leveraging the same predictive models used in its trading pods, the firm is offering tailored wealth advice that traditional advisors cannot match. This creates a winner-take-all dynamic. Smaller firms that cannot afford the multi-billion dollar R&D costs associated with proprietary AI platforms are being squeezed out. According to Yahoo Finance data, institutional investors are increasingly valuing Goldman not as a bank, but as a technology platform with a banking license. The valuation multiple is starting to reflect this tech-heavy identity, moving away from the cyclical baggage of traditional finance.
The next major milestone for this strategy arrives on March 12, 2026. This is the date of the scheduled Investor Day where David Solomon is expected to reveal the first audited ROI figures from the South Dallas power campus initiative. Analysts are looking for one specific data point: whether the AI infrastructure can lower the firm’s cost of capital by at least 50 basis points. If the bank hits that target, the 10-year playbook will cease to be a strategy and will become the new industry standard.
