Economy and Profitability with Generative Artificial Intelligence

Artificial intelligence is already transforming the way people work, yet the current monetization model for AI makes widespread adoption among companies unfeasible. In this context, H2O.ai proposes a Big AI model with generative capabilities to harness the potential profitability for companies.

"AI-assisted work is both the present and future for companies. Failure to adapt could result in imminent job loss because we are not offering anything new," explained Favio Vázquez, Senior Data Scientist for Latin America, H2O.ai.

According to Vázquez, interest in AI technology has surged exponentially every 24 months, as evidenced by the number of articles published on the subject in the Archive platform. He notes that AI technology has already surpassed humans in many tasks and is increasingly closer to understanding human thought and analysis. However, the challenge lies in implementation.

"Companies have been hesitant to adopt artificial intelligence due to the time, complexity, and exponential nature of the process, coupled with a lack of success," Vázquez elaborated.

The main barriers to adoption include the high cost of investment required for experimentation. Despite its potential, implementing AI does not always guarantee profitability. Challenges include dealing with niche markets, low model accuracy, lengthy time for market use, high hardware costs, and the fact that the human brain still excels in areas where AI falls short.

"We conducted a study and found that if a client had opted for any other platform with a 6-month experimentation period, they would have spent 53 million tokens, equivalent to over US$1 million in OpenAI. Just for experimentation," Vázquez emphasized.

He further suggests that the current system is not scalable and proposes to globally change the generative model through three pillars: Firstly, enabling the use of AI without token cost to prevent the dilution of benefits obtained from its usage. Secondly, developing new roles within companies where generative AI guided by workers is employed. And thirdly, fostering creative development and experimentation with AI usage.

"AI-assisted work is not just the future but already a reality for many companies. Individuals will acquire adjacent skills, enabling them to perform a variety of tasks. Failure to innovate could lead to job loss and stagnation," Vázquez emphasized.

According to H2O.ai's proposal, the optimal approach for companies is not to equip each worker with AI but to cultivate workers capable of integrating the human element and artificial intelligence. This approach aims to automate tasks efficiently, thereby enhancing productivity and boosting company profitability.