Crypto And Ai Policy Uncertainty As An Operational Constraint
Sources: 1 • Confidence: Medium • Updated: 2026-02-12 18:41
Key takeaways
- Copyright treatment for AI training—whether models may learn from copyrighted works without reproducing them—is a key upcoming policy issue.
- Goldman Sachs was the largest wholesale funder in the world 10 years ago and has since prioritized moving away from reliance on wholesale funding toward more stable sources.
- Goldman spent about $6B on technology last year but could not spend $8B without reducing returns, implying efficiency savings are needed to increase investment while maintaining performance.
- Geopolitics is tougher as the world shifts back toward multipolarity, increasing the risk of a geopolitical shock that slows growth compared to the post–Cold War era.
- Ongoing uncertainty and aggressiveness from the FTC, including toward smaller tech deals, could shift M&A toward IP-style transactions rather than traditional acquisitions.
Sections
Crypto And Ai Policy Uncertainty As An Operational Constraint
- Copyright treatment for AI training—whether models may learn from copyrighted works without reproducing them—is a key upcoming policy issue.
- The 'Clarity Act' is a pending crypto market-structure bill intended to define how different token types are classified under rules.
- Banning AI or restricting underlying mathematics would cause the U.S. to lose the AI race to China with long-term strategic consequences.
- Parts of the U.S. crypto industry were effectively banned by a prior U.S. administration via executive pressure rather than legislation or formal legal process, including the use of debanking tactics.
- A prior U.S. administration treated essentially all tokens and some NFTs as securities via enforcement actions described as extreme.
- A patchwork of 50 state-level AI laws would make it effectively impossible for new companies to comply and innovate.
Goldman Governance, Scale, And Funding Resilience
- Goldman Sachs was the largest wholesale funder in the world 10 years ago and has since prioritized moving away from reliance on wholesale funding toward more stable sources.
- Goldman Sachs shifted from having zero deposits 15 years ago to about $500B in total deposits, including a digital deposit platform with over $200B, funding roughly 40% of the firm with deposits.
- Goldman Sachs has maintained a partnership-like culture post-IPO, with roughly 450 partners whose compensation is correlated to overall enterprise performance.
- In mature financial services businesses, scale provides leverage and latitude during turbulence, making scale a central long-term strategic requirement for Goldman Sachs.
- Goldman Sachs leadership concluded that operating as a public company requires top-down strategic direction to make the organization’s parts add up to more than their sum.
- Goldman Sachs believes it must continue increasing balance-sheet scale over the next 5–15 years because it is currently far smaller than JPMorgan and organic scale-building is difficult in mature businesses.
Enterprise Ai Transformation: Tooling Distribution Vs Process Reengineering Under Regulatory Gating
- Goldman spent about $6B on technology last year but could not spend $8B without reducing returns, implying efficiency savings are needed to increase investment while maintaining performance.
- Goldman launched '1GS 3.0' to reimagine six firm processes; the capacity impact is described as very significant but not publicly quantified.
- Goldman’s first AI focus is distributing tools/models broadly to employees so they can experiment and discover productivity gains in client work.
- The more consequential AI opportunity is reimagining core enterprise operating processes for automation and efficiency, then reinvesting savings into growth areas.
- Large-scale process reimagination is difficult because it threatens existing organizational 'empires' and therefore must be driven top-down.
- Regulatory clearance requirements significantly slow Goldman’s ability to deploy AI tools compared with companies that can deploy without such gating.
Macro Drivers And Concentration Of Growth Inputs
- Geopolitics is tougher as the world shifts back toward multipolarity, increasing the risk of a geopolitical shock that slows growth compared to the post–Cold War era.
- A combination of fiscal stimulus, a rate-cutting cycle, a capital investment supercycle, and a deregulatory unwind makes the U.S. economy hard to slow.
- Last year, the four largest companies contributed about 1% to U.S. GDP growth through roughly $400B of spending.
- The current U.S. macro setup for investable and financial assets is the best 'sweet spot' seen in decades despite substantial global complexity.
Capital Markets Activity As A Function Of Regulatory Confidence
- Ongoing uncertainty and aggressiveness from the FTC, including toward smaller tech deals, could shift M&A toward IP-style transactions rather than traditional acquisitions.
- Capital markets activity is tied to confidence, and a tough regulatory environment suppresses confidence and therefore M&A, IPOs, and capital raising.
- Deal activity is expected to pick up significantly, and this year could be the biggest M&A year in history with a larger IPO year as confidence improves.
Watchlist
- Geopolitics is tougher as the world shifts back toward multipolarity, increasing the risk of a geopolitical shock that slows growth compared to the post–Cold War era.
- Ongoing uncertainty and aggressiveness from the FTC, including toward smaller tech deals, could shift M&A toward IP-style transactions rather than traditional acquisitions.
- The 'Clarity Act' is a pending crypto market-structure bill intended to define how different token types are classified under rules.
- Banning AI or restricting underlying mathematics would cause the U.S. to lose the AI race to China with long-term strategic consequences.
- Copyright treatment for AI training—whether models may learn from copyrighted works without reproducing them—is a key upcoming policy issue.
- Models trained on widely available information may not be able to produce differentiated investment outperformance.
Unknowns
- What are the current levels and trends of Goldman’s wholesale funding reliance versus deposit funding, including stability and cost of funds in stress scenarios?
- What specific six processes are included in '1GS 3.0', and what quantified outcomes (capacity, cycle time, error rates, headcount redeployment) have been achieved?
- What evidence supports the claim that some AI-era companies reached $100M to $1B+ in revenue in under a year, and how common is this across cohorts?
- Is the claim that Andreessen Horowitz raised about 18.3% of all U.S. venture capital in 2025 accurate, and what definition of 'U.S. venture capital raised' is being used?
- What specific regulatory actions or data substantiate or refute claims of debanking-driven crypto suppression and unusually broad securities classification of tokens/NFTs?