Implement AI projects in large -scale company It implies both adapting platforms and technological profiles and a cultural change in companies where adoption and innovation are promoted through data. Adopt a strategy to implement AI implies establish or adjust a “Data Driven” culture In the company.
According to Globant, the most common challenges when taking this step, as well as the necessary aspects to implement an AI strategy in the company that facilitates the achievement of business objectives are the following: quality of the data, talent management, regulation and safety, ethics in the use of the AI and impact of AI on the culture of the company.
The basis of a good AI model are the data. That is why it is basic that the quality of the information with which we train them to achieve reliable results is good. The poor quality of the data is one of the factors for which it is expected that at least 30% of the generative projects are abandoned by the end of 2025, according to Gartner.
Therefore, it is necessary to analyze the available data, both for training and production training, to avoid feeding models with incomplete or incorrect data that lead to incomprehensible or unreliable results.
The implementation of AI needs specialized knowledge in Big Data management, Machine Learning or generative. Everything implies that many companies face the problem of not having the right talent. This leads to more difficulties in the adoption and implementation of an AI strategy.
On the other hand, it is essential to comply with the regulations in force in each market, but in a digitalized world in which AI has advanced it is also crucial to guarantee the safety of the information used, preventing vulnerabilities or gaps that can take advantage of cybercriminals. However, one third of the cios and fissures cite the regulatory requirements among the greatest obstacles to integrate AI in cybersecurity strategies.
As for ethics in the use of AI, it goes beyond compliance with privacy laws, since training models without taking into account concepts such as biases can lead to discriminatory or unfair results.
In fact, these biases concern 57% of human resources directors in Spain. In fact, at present, the ethical use of AI, in addition to regulatory compliance, is directly linked to the social impact of companies that use this technology.
Of course, it is key, in relation to the impact of AI on the culture of a company, to be clear that it is basic that AI is understood as a tool that drives both the company and the work of its employees, and that the equipment is aware of the tools of AI at their disposal to carry out their work more efficiently, and that therefore allows them to contribute greater value.
The success in the implementation of an AI strategy is therefore as or becoming a company with a data culture, aware of their importance for the performance of operations and for the transformation and evolution of the business.
From Globant they also indicate the necessary keys to the adoption and government of the AI strategy: to promote a culture of innovation, creative thinking and experimentation, to explore new business possibilities. Also put the focus on learning and continuous training, and fight to establish an ethical awareness through guides or governance structures that guarantee that the equipment includes the ethical implications of their operations.
Izaskun López-Samaniego, Data Strategist de Globantremember that «If an organization wishes to implement artificial intelligence today, it should undoubtedly become a truly Data Driven company. That is, that it is aware of the relevance of the data and, especially, of its supervision, to ensure that the AI works for the benefit of the company and the whole society. Faced with the challenges of this trip of the AI data, organizations can rely on a partner like Globant, which has the purpose of supporting and preparing companies to highlight in a market as competitive as the current«.
