GenAI Applications: How Large Corporations Capture Efficiency at Scale

By

Mauro Oliveira

All companies will be impacted by Artificial Intelligence. Depending on the market sector, some will feel this impact sooner, others later. One of the biggest contemporary challenges for large companies—which sometimes take longer to adapt—is being aware of this prediction, understanding how their businesses will be impacted, and developing a strategic roadmap for transformation.

This is why, according to Mauro Oliveira, VP Partner at CI&T, planning this transformation now is crucial. "The question that leaders of large companies need to ask now is 'how do I transform into an AI-first company?'" he states.

Impacts of GenAI on Large Companies

More than just investing, demonstrating the value of investments in digital solutions has become part of the agenda of challenges for technology leaders in large companies.

Some examples of measured results include reducing production time and increasing delivered quality, reaching 30 to 40% reduction in necessary investment for development in highly complex institutions, such as companies in the financial sector.

At CI&T, this value demonstration has been incorporated into the operating method, permeating the entire partnership journey with institutions. However, it's not a simple journey, and to understand it, one must consider the three phases of digital transformation:

Phase 01.

Digital Transformation

From 2015 onwards, companies began to prepare for this transformation, focusing on customer experience, availability, scalability, and return on digital investment. However, this transition didn't occur as smoothly for all companies, and in some scenarios, digital investments began to be questioned.

Phase 02.

Digital Efficiency

With the return on digital investments being increasingly demanded, the search for efficiency became the focus. Demonstrating the value of investments became imperative.

Phase 03.

Hyper Digital

The emergence of Generative AI profoundly transformed digital solution engineering, elevating the search for efficiency to new levels. This process culminated in the approach called Hyper Digital, crowned by the creation of CI&T Flow, a platform with more than 35 generative AI agents built in conjunction with 20 of the largest companies in Brazil.

CI&T's AI-first positioning means that all people use and work with a new process, now faster, with higher quality, and generating more value for the business through humans empowered by GenAI. This is being hyper-efficient.

"Here in Brazil, 100% of CI&T's clients use our Artificial Intelligence platform in some way, and all our teams are empowered by AI," says Mauro.

How to Demonstrate the Gain of Hyper Digital?

For Mauro, demonstrating the gains of Hyper Digital should be based on numbers throughout the entire GenAI adoption chain, i.e., the end-to-end process, and not just in isolated moments. This includes the entire path composed of leadership and employee literacy > Planning > Roadmap of action > Use of Artificial Intelligence agents.

"GenAI is defining a new form of digital engineering, team organization, consumer behavior, and dynamics between competitors, and the time available to prepare for AI is getting shorter and shorter, it's a countdown. Those who are not making their plan now are already behind."

CI&T Use Cases

In one of Brazil's largest banks, the use of Generative AI showed impressive results after nine months of using CI&T's Hyper Digital solution:

The company recorded a 25% to 50% reduction in digital product lead time and a 30% increase in productivity.

2.5 times improvement in the quality levels of software developed with the support of CI&T/Flow.

The solution was applied in nine of the institution's 30 fronts, with potential to be expanded to other areas of the bank and amplify the results obtained.

In another use case, CI&T created for one of the world's largest car manufacturers an online pre-sales platform for the launch of one of the brand's models in Brazil, customized to the company's demand and commercial objectives.

In this case, Generative AI was used to transform efficiency in operations, product support and maintenance, cloud migration, solution quality, security correction and vulnerabilities, and acceleration of legacy technology modernization.

In these and other companies working in partnership with CI&T, Mauro highlights cultural differentials that are best practices for project success:

Engaged leadership that sees digital transformation as urgent, viewing AI not as a passing trend, but as a strategic priority.

Openness to innovation and collaboration throughout the process, creating environments where ideas are freely exchanged and teams can explore new approaches without fear of making mistakes.

Continuous learning with teams that maintain a posture of constant evolution to extract the maximum from GenAI.

Security mindset through rigorous standards of secure data use from the beginning of projects.

Demonstrating the value generated throughout the journey as a practice that strengthens alignment between teams and ensures continuous support from the organization as a whole.

By following these best practices, large companies can not only successfully adopt AI but also scale their results in a sustainable and innovative way.

Mauro Oliveira

Partner and EVP, CI&T