Rudy Lai

AI @ Goldman Sachs

Investment banking and asset management
Industry
Last updated
July 3, 2025 at 10:44 AM

Summary

  • Goldman Sachs has progressively scaled AI adoption from early exploratory projects in 2020 to firmwide deployment by 2025, including launching a generative AI assistant used by 10,000 employees and piloting autonomous AI software engineers augmenting their 12,000 developers, with leadership like CIO Marco Argenti and CEO David Solomon actively driving AI integration.
  • Key outcomes reported include up to 27% increase in trading desk profitability, 40% faster coding productivity, and significant reductions in regulatory compliance workload, demonstrating strong ROI; however, macroeconomic impact on US GDP remains minimal as of early 2026 with productivity gains still emerging.
  • Innovation focus has shifted towards agentic AI with autonomous task execution (e.g., AI coder Devin), generative AI for content and process automation, and traditional AI for pattern recognition in trading and risk, emphasizing human-AI hybrid workforce models and robust governance to maximize benefits while managing risks.

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6 AI Use Cases at Goldman Sachs

Process Automation
2026
Traditional
Generative
Agentic
Outcome
Costs
Using AI agents such as Anthropic's Claude, Goldman Sachs automates trade accounting, client onboarding, and compliance tasks to accelerate workflows and reduce manual effort. [1]
Autonomous Coding
2025
Traditional
Generative
Agentic
Outcome
Revenue
Goldman Sachs piloted 'Devin', an autonomous AI software engineer capable of executing complex multi-step coding projects, augmenting 12,000 developers and boosting productivity by up to 3-4x. [1][2]
Trading Optimization
2025
Traditional
Generative
Agentic
Outcome
Revenue
Goldman Sachs uses AI models to analyze market data and execute trades more profitably, achieving a reported 27% intraday profitability increase on AI-powered trading desks. [1]
Regulatory Compliance
2025
Traditional
Generative
Agentic
Outcome
Risk
AI tools accelerate regulatory analysis, cutting review times from weeks to hours and reducing false positives by 35%, enhancing compliance efficiency. [1]
Employee Productivity
2025
Traditional
Generative
Agentic
Outcome
The GS AI Assistant helps employees summarize documents, draft content, and analyze data, increasing efficiency and enabling faster decision-making across the firm. [1][2]
Code Generation
2024
Traditional
Generative
Agentic
Outcome
Costs
The bank deployed generative AI tools to thousands of developers to accelerate software development, improving coding speed by 40% and onboarding by 25%, also reducing helpdesk queries by 18%. [1][2]

Timeline

2026 Q2

1 updates

Economist Elsie Peng highlighted AI agents' impact on labor markets, indicating a reduction of about 25,000 monthly payroll jobs attributable to AI substitution effects over the past year.

2026 Q1

1 updates

Expanded AI agent deployment with Anthropic's Claude to automate processes like trade accounting; however, noted minimal AI contribution to US GDP growth so far.

2025 Q4

2 updates

Focused on AI market valuations and investments, addressing concerns of an AI bubble; CEO David Solomon discusses AI's workforce impact and opportunities.

2025 Q3

2 updates

Piloted 'Devin', an autonomous AI software engineer that augments 12,000 developers by automating complex coding tasks, representing a leap toward agentic AI integration.

2025 Q2

2 updates

Reported AI use cases showed a 27% increase in intraday profitability, 40% faster coding, reduced onboarding times, and compliance efficiencies; introduced GS AI Assistant firmwide for enhanced employee productivity.

2025 Q1

1 updates

Launched a firmwide AI productivity optimization program; rolled out GS AI Assistant to ~10,000 employees; CEO David Solomon champions AI as a transformative force.

2024 Q4

1 updates

Focused on leveraging AI to enhance investment decision-making, emphasizing efficiency and improved outcomes.

2024 Q3

1 updates

Completed rollout of generative AI code generation tools; recognition of AI hype versus practical complexities in adoption.

2024 Q2

1 updates

Rolled out the first generative AI tool for code generation to thousands of developers across the firm; began critical evaluations of AI spend versus benefits.

2024 Q1: no updates

2023 Q4

1 updates

Goldman Sachs acknowledged rapid advancement of generative AI, preparing privacy and governance frameworks as a new AI wave emerges.

2023 Q3: no updates

2023 Q2: no updates

2023 Q1

1 updates

Goldman Sachs highlighted generative AI's potential to boost labor productivity growth by approximately 1.5 percentage points.

2022 Q4: no updates

2022 Q3: no updates

2022 Q2: no updates

2022 Q1: no updates

2021 Q4: no updates

2021 Q3: no updates

2021 Q2: no updates

2021 Q1: no updates

2020 Q4: no updates

2020 Q3: no updates

2020 Q2: no updates

2020 Q1

1 updates

Initial AI adoption targeted wealth management and cybersecurity with exploratory initiatives.