Although the current scenario of Generative Artificial Intelligence is increasingly disruptive, there are many companies that are not sure of the best way to leverage the technology to enhance their processes. 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 using Generative AI. Furthermore, 22% of them still cannot quantify and measure the results of using this resource.
According to Mathias Brem, co-founder and CDO of Rox Partner, a technology consultancy specializing in data and cybersecurity, the use of the resource allows, for example, the data lake, a corporate repository that stores large volumes of structured and unstructured data, to be taken to a new level using a reinforced data-driven approach. “This addition has been driving the corporate world towards a data-oriented future, opening new frontiers for analysis and innovation in various areas,” he concludes.
To help companies employ Generative AI more effectively, Mathias Brem identified five high-impact changes that its adoption can provide. Check it out:
- Synthetic Data Generation
Generative AI enables creating sets of realistic and high-quality synthetic data, expanding data lakes with information representing non-existent real scenarios. This is crucial for training more robust and accurate machine learning models, addressing the lack of real data and avoiding biases. “Synthetic data can replicate complex situations, such as frauds or extreme customer behaviors, without relying on real data. This enhances the accuracy of predictive models,” notes Brem.
- Enrichment and Advanced Data 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 previously invisible insights and patterns. “With AI, we can transform raw data into rich and actionable information, enabling more strategic and informed decisions,” highlights Rox Partner’s CDO.
- Automation of Repetitive Tasks
The technology also allows automating repetitive tasks, such as data cleaning and anomaly detection, AI frees up professionals to focus on strategic analysis and development of machine learning models, increasing operational efficiency. “Automating routine processes allows the data team to focus on higher value-added activities, driving innovation and competitiveness,” states.
- Development of Innovative Products and Services
AI can generate innovative ideas for products and services, assist in research and development of tailored solutions. It can also optimize designs and generate 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 the executive.
- Expansion of Knowledge and Expertise
AI can create tailored training materials and optimize learning in different roles and levels of knowledge. Chatbots, for example, can assist employees in repetitive tasks, freeing up time for strategic activities. “Personalizing training through AI ensures that employees get exactly the knowledge they need, improving efficiency and productivity,” concludes.
