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How Goldman Is Scaling AI to Transform Its Business Operations
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Key Takeaways
Goldman's OneGS 3.0 embeds generative and predictive AI across trading, banking and asset management.
GS reorganized TMT banking to target AI-driven dealmaking tied to data centers and semiconductors.
Goldman is leaning into higher-fee, data-driven businesses as OneGS 3.0 supports operating leverage.
The Goldman Sachs Group ((GS - Free Report) ) is executing a firmwide artificial intelligence (AI) transformation that spans trading, investment banking, asset management, and internal productivity, with a clear objective — to lift fee income and expand operating leverage over the coming years. At the center of this effort are the “One Goldman Sachs 3.0 (OneGS 3.0)” transformation and the “GS AI Assistant” program, both designed to embed generative and predictive AI into nearly every major workflow across the firm.
At the 2025 Goldman Global Conference, CFO Denis Coleman described OneGS 3.0 as a multi-year overhaul of Goldman’s operating model, positioning AI as a foundational capability rather than a standalone tool. The initiative focuses on simplifying processes, improving productivity, and enabling scalable growth across divisions. Coleman emphasized that high-quality data, shared platforms, and modern infrastructure are critical enablers, allowing AI to deliver reliable insights while meeting the firm’s stringent regulatory and risk-management requirements.
Goldman is also reshaping its front-office strategy to align with AI-driven market demand. The firm recently reorganized its Technology, Media, and Telecom (“TMT”) investment banking division to focus more directly on digital infrastructure and artificial intelligence-related dealmaking, according to a Reuters report published on MSN. Management framed the move as a response to shifting client needs, where activity is increasingly concentrated in AI-enabling assets such as data centers, semiconductors, connectivity, and core software platforms. By sharpening sector specialization, Goldman aims to deepen client coverage and capture a greater share of high-growth, technology-driven advisory opportunities.
Beyond operations and advisory, Goldman’s AI push is contributing to a broader evolution in its revenue mix. The company is increasingly emphasizing higher-fee, data-driven businesses over more balance-sheet-intensive activities. The planned acquisition of Industry Ventures fits into this strategy, as Goldman seeks to apply advanced analytics and AI to improve startup valuation, risk assessment, and portfolio construction in private markets.
Taken together, Goldman’s AI strategy marks a structural shift in how the firm operates, advises clients, and generates revenues. Rather than a cost-cutting tool, AI is positioned as a long-term growth engine strengthening Goldman’s operating leverage and competitiveness.
How AI Is Impacting Productivity at Other Finance Firms
The largest U.S. banks, including JPMorgan ((JPM - Free Report) ) and Bank of America ((BAC - Free Report) ), are investing billions of dollars in AI to boost productivity and meet clients' evolving financial needs.
JPMorgan’s CFO, Marianne Lake, emphasizes that AI has doubled the bank’s productivity impact from roughly 3-6% and highlighted especially significant gains for operations specialists, potentially 40-50% increases as tasks become more automated and AI-assisted. JPMorgan’s broader tech commitment remains substantial (approximately $18 billion annual technology budget). CEO Jamie Dimon has pointed to a $2-billion AI investment delivering similar magnitude savings, evidence of a focus on measurable ROI, not just experimentation.
Bank of America has been among the most explicit on spending and adoption. Management has noted investing $4 billion of its roughly $13-billion technology budget in AI and related new tech initiatives, and has tied this to tangible productivity outcomes in both frontline and tech teams. Bank of America’s long-running virtual assistant, Erica, also illustrates how AI can absorb high-volume service interactions, freeing humans for complex requests, an operating model that can raise service levels without hiring at the same pace.
GS shares have gained 56.6% in the past year compared with the industry’s growth of 36.9%.
Price Performance
Image Source: Zacks Investment Research
From a valuation standpoint, Goldman trades at a forward price-to-earnings (P/E) ratio of 16.25X, above the industry’s average of 15.09X.
Price-to-Earnings F12M
Image Source: Zacks Investment Research
The Zacks Consensus Estimate for GS’s 2025 and 2026 earnings implies year-over-year rallies of 20.8% and 12.6%, respectively. The estimates for both years have been revised upward over the past 30 days.
Image: Bigstock
How Goldman Is Scaling AI to Transform Its Business Operations
Key Takeaways
The Goldman Sachs Group ((GS - Free Report) ) is executing a firmwide artificial intelligence (AI) transformation that spans trading, investment banking, asset management, and internal productivity, with a clear objective — to lift fee income and expand operating leverage over the coming years. At the center of this effort are the “One Goldman Sachs 3.0 (OneGS 3.0)” transformation and the “GS AI Assistant” program, both designed to embed generative and predictive AI into nearly every major workflow across the firm.
At the 2025 Goldman Global Conference, CFO Denis Coleman described OneGS 3.0 as a multi-year overhaul of Goldman’s operating model, positioning AI as a foundational capability rather than a standalone tool. The initiative focuses on simplifying processes, improving productivity, and enabling scalable growth across divisions. Coleman emphasized that high-quality data, shared platforms, and modern infrastructure are critical enablers, allowing AI to deliver reliable insights while meeting the firm’s stringent regulatory and risk-management requirements.
Goldman is also reshaping its front-office strategy to align with AI-driven market demand. The firm recently reorganized its Technology, Media, and Telecom (“TMT”) investment banking division to focus more directly on digital infrastructure and artificial intelligence-related dealmaking, according to a Reuters report published on MSN. Management framed the move as a response to shifting client needs, where activity is increasingly concentrated in AI-enabling assets such as data centers, semiconductors, connectivity, and core software platforms. By sharpening sector specialization, Goldman aims to deepen client coverage and capture a greater share of high-growth, technology-driven advisory opportunities.
Beyond operations and advisory, Goldman’s AI push is contributing to a broader evolution in its revenue mix. The company is increasingly emphasizing higher-fee, data-driven businesses over more balance-sheet-intensive activities. The planned acquisition of Industry Ventures fits into this strategy, as Goldman seeks to apply advanced analytics and AI to improve startup valuation, risk assessment, and portfolio construction in private markets.
Taken together, Goldman’s AI strategy marks a structural shift in how the firm operates, advises clients, and generates revenues. Rather than a cost-cutting tool, AI is positioned as a long-term growth engine strengthening Goldman’s operating leverage and competitiveness.
How AI Is Impacting Productivity at Other Finance Firms
The largest U.S. banks, including JPMorgan ((JPM - Free Report) ) and Bank of America ((BAC - Free Report) ), are investing billions of dollars in AI to boost productivity and meet clients' evolving financial needs.
JPMorgan’s CFO, Marianne Lake, emphasizes that AI has doubled the bank’s productivity impact from roughly 3-6% and highlighted especially significant gains for operations specialists, potentially 40-50% increases as tasks become more automated and AI-assisted. JPMorgan’s broader tech commitment remains substantial (approximately $18 billion annual technology budget). CEO Jamie Dimon has pointed to a $2-billion AI investment delivering similar magnitude savings, evidence of a focus on measurable ROI, not just experimentation.
Bank of America has been among the most explicit on spending and adoption. Management has noted investing $4 billion of its roughly $13-billion technology budget in AI and related new tech initiatives, and has tied this to tangible productivity outcomes in both frontline and tech teams. Bank of America’s long-running virtual assistant, Erica, also illustrates how AI can absorb high-volume service interactions, freeing humans for complex requests, an operating model that can raise service levels without hiring at the same pace.
Goldman’s Price Performance, Valuation & Estimates
GS shares have gained 56.6% in the past year compared with the industry’s growth of 36.9%.
Price Performance
Image Source: Zacks Investment Research
From a valuation standpoint, Goldman trades at a forward price-to-earnings (P/E) ratio of 16.25X, above the industry’s average of 15.09X.
Price-to-Earnings F12M
Image Source: Zacks Investment Research
The Zacks Consensus Estimate for GS’s 2025 and 2026 earnings implies year-over-year rallies of 20.8% and 12.6%, respectively. The estimates for both years have been revised upward over the past 30 days.
Estimate Revision Trend
Image Source: Zacks Investment Research
Goldman currently carries a Zacks Rank #3 (Hold). You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.