Big banks and how they're thinking about AI

2026-07-16 · Source: Constellation Research · Field: Finance & Economics — Banking & Financial Services, FinTech & Digital Financial Services · Depth: Fundamental Awareness, quick

Summary

Published July 17, 2026, major Wall Street banks are actively integrating AI, leveraging unique characteristics like internal build capabilities, extensive data, and engineering talent. Citigroup CFO Gonzalo Luchetti reported mapping over 100 processes for AI-driven automation to reduce structural costs, with weekly C-suite reviews. JPMorgan Chase CEO Jamie Dimon emphasized that AI benefits customers primarily, not just margins, noting nearly 1,000 use cases with 50 deemed critical. JPMorgan Chase CFO Jeremy Barnum highlighted the bank's \$700 million AI spending this year, with trivial token expenses, focusing on sophisticated model usage. Goldman Sachs CEO David Solomon affirmed AI's role in expanding talent capabilities and driving commercial impact, asserting it will not replace the firm's relationship-driven business or its "extraordinary people."

Key takeaway

For Directors of AI/ML evaluating enterprise AI adoption, recognize that leading financial institutions prioritize internal AI development and architectural control over vendor reliance. Your strategy should focus on identifying specific, high-impact use cases, like JPMorgan Chase's 50 critical applications from 1,000, and rigorously mapping processes for automation. This approach ensures AI drives both efficiency and customer value, rather than merely boosting margins, while preserving human-centric relationship aspects.

Key insights

Big banks view AI as a strategic asset for efficiency and customer value, leveraging internal capabilities and significant investment.

Principles

• AI benefits customers, not just margins.
• Internal AI builds offer architectural control.
• AI expands human talent capabilities.

Method

Citigroup maps 100+ processes end-to-end for automation opportunities, with weekly C-suite progress checks.

In practice

• Map processes for automation opportunities.
• Prioritize critical AI use cases (e.g., 50 from 1,000).
• Monitor AI value creation closely.

Topics

• Enterprise AI Strategy
• Financial Services
• AI Automation
• JPMorgan Chase
• Citigroup
• Goldman Sachs

Best for: Investor, CTO, VP of Engineering/Data, Executive, Director of AI/ML, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by Constellation Research.