# The race for the 'Big Tech bank': how Nubank is restructuring its operation to be led by artificial intelligence

The financial sector is going through a structural transition that goes far beyond simply digitizing services.

- Section: Business
- Published: October 19, 2026
- Address: https://ceoone.com.br/en/article/the-race-for-the-big-tech-bank-how-nubank-is-restructuring-its-operation
- Em português: https://ceoone.com.br/artigo/a-corrida-pelo-banco-big-tech-como-o-nubank-reestrutura-sua-operacao-p.md

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## Key points

- Nubank trains researchers with MIT, ITA and Unicamp and combines OpenAI models with its own algorithms.
- About 98% of employees use generative AI tools in their daily work.
- Pix transfers can already be made by text message in the app, the interface Felipe Lamounier points to as the future of the sector.

The new frontier for leading institutions is turning their operations into organizations fully driven by Artificial Intelligence (AI). Leading this strategy at Nubank, Felipe Lamounier (the institution's strategist and founder of the startup Hyperplane, acquired by the bank in 2024) details the company's ambition: to turn the neobank's structure into an operating model similar to the research labs of the large global technology companies (big techs).

For executives, C-levels and board members in the corporate sector, Nubank's move signals a decisive paradigm shift: AI stops being just a back-office automation tool and becomes the central engine of product strategy, operational efficiency and customer retention.

## A research ecosystem and AI talent development

Inspired by Silicon Valley's innovation architecture, the bank set up strategic partnerships with leading academic and research centers, such as the Massachusetts Institute of Technology (MIT), the Aeronautics Institute of Technology (ITA) and the State University of Campinas (Unicamp). The initiative aims to train high-level researchers and create internship programs focused on developing proprietary solutions in machine learning and natural language processing.

In the view of senior leadership, securing sovereignty over technological development is the key to creating sustainable competitive advantages. In the model the bank has adopted, the infrastructure combines market language models, such as those provided by OpenAI, with algorithms developed in-house, ensuring flexibility, scale and protection for the institution's data.

## Internal productivity and the interface of the future in retail finance

The results of this transformation already show in the institution's efficiency indicators and internal culture. Today, about 98% of Nubank's employees use generative AI tools in their daily work. Mass adoption of the technology has made it possible to improve customer service channels, optimize internal budget management and offer financial products and services at a lower operating cost.

In the direct relationship with consumers, the big bet is on radically simplifying the user experience. The bank already offers Pix transfers made directly through text messages inside the app, a mode Lamounier points to as the interface of the future in the financial sector. By replacing complex menus and long journeys with natural-language interactions, the institution is redefining engagement standards in retail banking.

## Leadership lessons and corporate impact

Nubank's path toward an operation strongly anchored in artificial intelligence offers valuable, practical lessons for decision-makers across the economy. First, the open innovation model highlights the importance of building direct bridges with academia; partnerships with leading institutions such as MIT, ITA and Unicamp secure priority access to qualified talent and applied scientific knowledge. In addition, the institution's technological acculturation shows that reaching 98% of the workforce using generative AI requires continuous investment in training and fostering a productivity-oriented culture.

From an architecture and governance standpoint, the bank takes a hybrid algorithm strategy that combines large market models, such as OpenAI's, with proprietary solutions, ensuring operational efficiency without giving up strategic control of its data. Finally, AI-driven automation redefines value delivery to customers by reducing the cost to serve, allowing efficiency gains to be passed on as cheaper, more accessible and highly personalized products.

## Strategic matrix: operational transformation through AI

| Strategic pillar | The institution's practical action | Business impact | Lesson for corporate leaders |
| --- | --- | --- | --- |
| R&D and talent | Partnerships with MIT, ITA and Unicamp | Development of specialized workforce and cutting-edge research | Build strategic bridges with academic centers of excellence. |
| Corporate culture | 98% of employees using generative AI | Productivity gains in customer service and budget management | Make AI tools available across every area of the company. |
| User interface | Pix transfers by text message | Simpler customer journey and greater engagement | Reduce friction in the customer experience with natural language. |
| Model architecture | Hybrid use (OpenAI + proprietary models) | Lower cost to serve and data security | Don't depend exclusively on external technology suppliers. |

## Sources and editorial notes

- Reference reporting: O Estado de S. Paulo (September 30, 2026 edition, Business section, interview with Felipe Lamounier by O Estado de S. Paulo).
- Market and leadership analysis: Content and analytical context developed by the CEO ONE portal for decision-makers and C-level executives.

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