Cloud with AI: Why migrating without a strategy has become costly?

Cloud with AI has evolved from a mere infrastructure step to the center of a data-driven transformation, automation, and artificial intelligence. This is the vision presented by Stefanini Technology, a unit of the Stefanini Group that leads modernization projects for banks, industrial companies, and financial service groups in Latin America.

In a statement released in Buenos Aires on August 13, 2026, the company argues that the next phase of digital transformation will not be defined solely by the transfer of systems to external servers. Now, the challenge involves modernizing applications, organizing data, enhancing security, and preparing the entire architecture to operate with artificial intelligence at scale.

Cloud with AI changes the role of infrastructure

For years, many companies treated the cloud as a migration project. In this model, the main objective was to move applications and databases from local environments to public or private providers. However, the accelerated adoption of AI has changed this logic.

According to the AI-First strategy of the Stefanini Group, the cloud needs to act as a business platform. Therefore, it must organize data, support governance models, integrate systems, and enable artificial intelligence agents to perform critical tasks securely.

This shift also alters how return on investment is calculated. Infrastructure savings remain relevant, but they no longer represent the sole indicator. Additionally, companies are beginning to measure productivity, development speed, risk reduction, scalability, and the ability to launch new services.

AI agents enter the banking back office

One of the projects cited by Stefanini Technology takes place at one of the largest banks in Latin America. The initiative uses artificial intelligence agents to analyze checklists, standards, and operational requirements that previously required a heavy manual workload.

The project integrates the agents into the institution's internal systems and modernizes the digital development flow. At the same time, the team applies an agile delivery model and creates accelerators for repetitive or documentation tasks.

According to Stefanini, the technology has generated performance gains of over 200% in analysis and execution activities. Thus, the bank can free back office professionals for higher-value decisions while AI processes large volumes of rules and documents.

However, automation in a regulated sector requires clear controls. Agents need to operate with defined permissions, audit trails, human validation, and security policies. Otherwise, speed may amplify errors instead of reducing costs.

Steel industry modernizes legacy systems

In the industrial sector, Stefanini Technology is leading the modernization of the infrastructure and applications of a large steel company. The work combines cloud adoption with the upgrade of legacy systems, which often concentrate essential processes and integrations built over decades.

The initiative included redesigning the architecture, a structured migration, and implementing a data governance model. This way, the company can reduce technical dependencies, improve integration between systems, and create a more suitable foundation for analytics and artificial intelligence.

Modernizing legacy systems, however, does not mean simply discarding everything that already exists. In many cases, the most efficient strategy combines code refactoring, gradual replacement of components, and preservation of applications that still deliver value.

Financial services advance towards structured migration

Another project involves a significant group from the consortium and financial services sectors. The operation is in the final phase of a structured migration to the cloud, focusing on regulatory compliance, application modernization, and preparing the infrastructure for business growth.

In such an environment, scalability cannot rely solely on hiring more computing capacity. The architecture also needs to control costs, protect sensitive information, and maintain operational continuity. Therefore, applications, data, security, and support must evolve in an integrated manner.

Repatriation Exposes the Cost of Poorly Planned Cloud Solutions

Stefanini also highlights the repatriation of workloads. This phenomenon occurs when companies pull applications from the cloud and return them to traditional technology environments after costly, unstable, or poorly sized projects.

Repatriation does not necessarily represent a rejection of the cloud. Often, it reveals planning issues. A company may migrate old code without modernizing it, choose an architecture incompatible with its demand, or overlook costs related to traffic, storage, security, and support.

"It is very unlikely to find cloud migration projects, especially for the public cloud, that do not require the modernization of application code. It is an end-to-end transformation that must incorporate governance, security, and a solid architecture from the outset." Rodrigo Stefanini, CEO for Latin America and Spain of the Stefanini Group

The warning dismantles a common market promise: the idea that simply moving systems to the cloud will yield automatic efficiency. Without technical redesign and governance, migration may merely transfer old problems to a more expensive infrastructure.

Artificial Intelligence Accelerates Modernization

AI itself also participates in the migration process. According to the Stefanini Group, intelligent tools help analyze code, identify dependencies, document applications, suggest corrections, and automate testing stages.

Consequently, teams can reduce the time needed to modernize systems and lower risks during the transition. Technology does not eliminate the need for architects, developers, and security specialists. However, it enhances the capacity of these teams and accelerates tasks that previously took weeks.

"With the use of artificial intelligence, we can significantly accelerate migrations to the cloud. The application modernization cases developed by the Group allow our clients to reach the cloud faster, in a structured and secure manner." Rodrigo Stefanini

What Does AI-Enabled Cloud Change for the Financial Market?

For banks, fintechs, exchanges, and digital asset platforms, the message is clear. The infrastructure needs to be born ready for auditing, security, integration, and growth. Additionally, any use of AI agents in critical processes must allow for tracking decisions and identifying responsibilities.

Although the mentioned projects do not have a declared focus on blockchain, the same technological foundation supports initiatives for tokenization, digital payments, and programmable financial services. Organized data, reliable APIs, and consistent access controls form the invisible layer behind these solutions.

• Governance: defines who can access data, systems, and AI models.
• Security: reduces risks in distributed and highly integrated environments.
• Modernization: avoids transporting inefficient code to a more sophisticated infrastructure.
• Scalability: allows growth without losing operational or regulatory control.

Stefanini Bets on an AI-First Ecosystem

The Stefanini Group claims to operate in 46 countries, with 23 delivery centers distributed across five continents and more than 35,000 employees. The company organizes its operations into seven business units: Technology, Cyber, Data & Analytics, Financial Tech, Operations, Marketing, and Manufacturing.

The group also consolidates its proprietary artificial intelligence platforms in the SAI suite, which stands for Stefanini Artificial Intelligence. According to the company, this ecosystem combines data, automation, and AI to support end-to-end transformations.

Additionally, the company has become the subject of academic study through the case "Creating an Ecosystem Strategy in the Age of AI," developed by the INSEAD business school.

Instead of selling the cloud as a final destination, the strategy positions the infrastructure as a foundation. On top of it, companies can build automations, new products, and more efficient operations.

Migration is no longer the end goal

The central message of the projects presented by Stefanini is clear: migrating to the cloud is not enough. Companies need to modernize code, structure data, integrate security, and create governance from the start.

Cloud with AI can accelerate operations and open new opportunities. On the other hand, a rushed migration can increase costs and lead to the repatriation of systems. Therefore, the advantage lies not simply in being in the cloud, but in building an architecture capable of transforming technology into business results.

More information about the Stefanini Group is available at stefanini.com.

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