Generative Artificial Intelligence is emerging as a disruptive tool in the business landscape, but many companies still do not know how to make the most of this technology. According to the report "Startups & Generative Artificial Intelligence: Unlocking its potential in Brazil," conducted by Google and Box1824, 63% of AI startups in Brazil still do not have a clear strategy for the use of Generative AI, and 22% are unable to quantify the results of its use.
Mathias Brem, co-founder and CDO of Rox Partner, a technology consultancy specializing in data and cybersecurity, highlights how Generative AI can revolutionize data management. "This plugin has driven the corporate world towards a data-driven future, opening new frontiers for analysis and innovation in various areas," he states.
To help companies use Generative AI more effectively, Brem listed five high-impact changes its adoption can bring:
1. Synthetic Data Generation
Generative AI allows the creation of realistic, high-quality synthetic datasets, expanding data lakes with information that represents non-existent real-world scenarios. This is crucial for training more robust and accurate machine learning models, compensating for the lack of real data and avoiding biases. "Synthetic data can replicate complex situations, such as fraud or extreme customer behaviors, without relying on real data. This increases the accuracy of predictive models," observes Brem.
2. Advanced Data Enrichment and Analysis
AI can enrich existing data by generating detailed product descriptions, translating texts, identifying relevant information from unstructured documents, and creating new attributes. This enables deeper analyses, revealing insights and patterns previously invisible. "With AI, we can transform raw data into rich, actionable information, enabling more strategic and well-founded decisions," highlights Brem.
3. Automation of Repetitive Tasks
Technology enables the automation of repetitive tasks, such as data cleaning and anomaly detection, freeing professionals to focus on strategic analysis and the development of machine learning models, thereby increasing operational efficiency. "Automating routine processes allows the data team to focus on higher value activities, which drives innovation and competitiveness," he/she states.
4. Development of Innovative Products and Services
AI can generate innovative ideas for products and services, assist in research and development of customized solutions, optimize designs, and produce realistic prototypes, speeding up the development process. "The ability to generate new concepts and prototypes quickly accelerates the innovation cycle, keeping companies at the forefront of the market," comments Brem.
5. Expanding Knowledge and Expertise
AI can create customized training materials and optimize learning across different roles and levels of knowledge. Chatbots, for example, can assist employees with repetitive tasks, freeing up time for strategic activities. "Personalizing training through AI ensures that employees acquire exactly the knowledge they need, improving efficiency and productivity," concludes Brem.
With these five strategies, the adoption of Generative AI can transform data management, driving innovation and competitiveness in companies.
