Goldman Sachs’ Q3 2025 earnings took a back seat to something far bigger — a full-scale reinvention of how the firm operates.
On Tuesday (Oct. 14), the investment bank unveiled “One Goldman Sachs 3.0”, a centralized, AI-driven operating model designed to automate workflows, streamline client onboarding, and improve regulatory reporting and risk control.
“Propelled by AI, this is a new, more centralized operating model that we expect to drive efficiencies and create capacity for future growth,” said CEO David Solomon, marking the announcement as a defining step for the bank’s long-term transformation.
Inside “Goldman 3.0” — AI at the Core
The new model is not about restructuring departments, but reengineering processes. The initiative targets multiple high-value areas:
| Process Area | AI/Automation Focus |
|---|---|
| Client Onboarding | Intelligent document parsing and verification |
| Sales Enablement | Predictive analytics and automation for deal pipelines |
| Lending & Credit | Algorithmic underwriting and risk scoring |
| Vendor Management | Centralized AI workflows for compliance and performance tracking |
| Regulatory Reporting | Automated reconciliation and anomaly detection |
| Operational Risk | Predictive monitoring and real-time alerting |
Solomon emphasized that “3.0 isn’t a turnaround plan—it’s a technology-driven redesign.” The model aims to shift talent and capital from administrative functions toward growth opportunities in asset management, advisory, and financing.
Six Key Metrics for Goldman 3.0
CFO Denis Coleman outlined six measurable goals that will guide the program’s rollout over the next two quarters:
| Performance Metric | Objective |
|---|---|
| Client Experience | Reduce onboarding time and improve service personalization |
| Profitability | Improve efficiency ratio via automation savings |
| Productivity | Free capacity for front-office growth |
| Resilience & Scale | Build systems that adapt to volatility |
| Employee Experience | Reduce manual work and improve data accessibility |
| Risk Management | Embed proactive risk analytics and AI oversight |
The firm plans to release progress markers on these dimensions during its January 2026 earnings call.
Market Context: A Cautious View Amid AI Euphoria
Solomon used the announcement to warn that “many assets look like they are entering bubble territory,” noting that much of the current exuberance in equities and venture capital is “fueled by investment in AI infrastructure.”
Despite the optimism around AI, he cautioned investors that risk management must remain disciplined as markets price in aggressive growth assumptions.
“AI will help us reimagine our operating model,” Solomon said, “but it won’t change the fundamentals of responsible growth.”
Financial Highlights Provide Context
While AI stole the spotlight, Goldman’s fundamentals remained solid.
| Financial Metric (Q3 2025) | Result |
|---|---|
| Net Revenue | $15.18 billion |
| Earnings Per Share (EPS) | $12.25 |
| Return on Equity (ROE) | 14.2% |
| Provision for Credit Losses | $339 million (down sequentially) |
| Platform Solutions Revenue | $670 million |
| Shareholder Returns | $3.25 billion (incl. $2 billion buybacks) |
| Dividend | $4 per share |
| Assets Under Supervision | Record $3.5 trillion |
| Long-Term Net Inflows | $56 billion |
Coleman confirmed that the firm expects to raise about $100 billion in alternatives by year-end, continuing its pivot toward more stable, fee-based revenue streams.
Strategic Refocus: B2B Over Consumer
Goldman continues to reduce exposure to mass-market consumer credit.
- The GM card program has been fully exited.
- The Apple Card partnership remains under evaluation, with no announced timeline for further expansion.
- The credit card portfolio remains a drag due to charge-offs, but credit normalization is progressing.
Instead, Goldman is leaning into payments-adjacent B2B activities and digital financial services infrastructure, positioning itself as an institutional AI-driven financial platform rather than a consumer lender.
Expert Takeaways
1. Industry Perspective — “AI as a Financial Engine”
Analysts at PYMNTS Intelligence noted that Goldman’s approach signals “a shift from experimentation to enterprise AI,” leveraging its data-rich operations for scalable automation.
2. Risk Insight — “A Controlled Evolution”
According to market analyst Daniel Ives, “Solomon’s caution around AI exuberance shows Goldman wants to lead the next wave of financial automation — but without repeating the excesses of past cycles.”
3. Workforce Transition — “Efficiency Meets Human Expertise”
A former Goldman executive observed that “AI isn’t replacing analysts; it’s optimizing the repetitive 40% of their work so they can focus on the 60% that matters — relationships and risk judgment.”
Why It Matters?
Goldman Sachs 3.0 represents one of Wall Street’s clearest declarations that AI is no longer a pilot project — it’s a foundation.
The move reinforces a broader shift across financial institutions, where machine reasoning and automation are seen as the path to resilience, compliance, and long-term growth.
By blending generative reasoning with real-time data from risk, sales, and operations systems, Goldman aims to position itself as the first truly AI-native investment bank — a model others are likely to emulate.
FAQs
1. What is “Goldman Sachs 3.0”?
It’s a new, firmwide AI-driven operating model designed to reengineer workflows, improve efficiency, and centralize risk management across the company.
2. How will AI change Goldman’s operations?
AI will automate onboarding, sales, and regulatory reporting while improving decision-making through predictive analytics and real-time monitoring.
3. Is Goldman exiting consumer banking?
Goldman is reducing its exposure to mass-market consumer credit (like the GM card) and focusing on institutional and B2B payment platforms.
4. When will investors see measurable progress?
Management said performance metrics tied to AI efficiency and profitability will be shared during the January 2026 earnings call.
5. How does this affect employees?
The new system aims to reduce repetitive tasks and increase productivity — not replace workers, but allow them to focus on higher-value analysis and client service.
6. How does this compare to competitors?
Goldman joins peers like JPMorgan and Citi in embedding AI across their operations, but its top-down integration and explicit performance tracking make it one of the most comprehensive efforts on Wall Street.