The Bipolarity of Artificial Intelligence Usage

In accordance with the Global CIO Survey on AI Adoption by 2025, over three-quarters (78%) of surveyed executives affirm that expanding AI and machine learning use to create commercial value is the top priority for enterprise data strategy in the next three years. However, Artificial Intelligence (AI) is not a “one-size-fits-all solution,” and there are technical and financial challenges to overcome to extract value from this technology. In this text, we aim to unravel some positive aspects and points of concern for the application and use of AI.

Public Security and Ethics

The use of cameras for monitoring and the need for intelligence in public security are consensual. AI can recognize images, generate analytical reports, and adapt to any system with visual elements, contributing to the expansion of “smart cities.” However, ethical and responsible use of AI faces challenges. Measures and strategies must balance technological innovation with social issues. According to our Head of Data & AI, Guilherme Zuccolotto, “there must be an emphasis on accountability, ensuring that organizations are responsible for any consequences of AI-based decisions. Robust policies should be implemented to safeguard personal information, utilizing techniques such as anonymization and encryption. Additionally, active participation of the population in the governance and decisions related to the implementation of AI technologies is crucial: this public involvement contributes to defining ethical guidelines and acceptable limits, promoting a more inclusive approach.” It is important to emphasize that regulation plays a significant role in the creation of specific laws that establish standards and limits, ensuring that the development and use of technology are aligned with ethical principles.

AI Utilization in Testing

The progressive complexity in software development has exponentially increased, driven by the relentless pursuit of more advanced and personalized solutions. This evolution emphasizes the need to ensure quality and security in the process, with AI application emerging as a transformative element in the realm of software testing. According to the Gartner report, 56% of IT and Software Engineering leaders use API (Application Programming Interface) tests, 45% use integration tests, and 40% use performance tests. The data highlights a significant trend: automated tests are becoming increasingly integrated into organizations. In this context, AI implementation is a major trend. Studies indicate the growing use of Machine Learning and advanced algorithms to detect and predict defects. Furthermore, AI should be viewed as an accelerator for digital asset construction.

Professionals + AI

The International Monetary Fund (IMF) report indicates that in advanced economies like the United States and the United Kingdom, between 60% and 70% of current jobs are highly exposed to artificial intelligence. In Brazil, the IMF estimates this number to be 41%. This criterion, exposure of a job to artificial intelligence, encompasses both jobs that will benefit from the technology and those that will be threatened by it in the future. To prepare for this scenario, countries must establish comprehensive social safety nets and offer retraining programs for workers. This provides an opportunity for the development of all professionals to work in partnership with AI.

There is still much discussion about Artificial Intelligence, a topic that will remain on the agenda for a long time. If you enjoyed these reflections, we invite you to consume some of act digital’s content on the subject:

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