When we think of artificial intelligence almost automatically, we are transported to a futuristic scenario. However, this technology has been present in our lives for years. Let's think that artificial intelligence is behind the hundreds of suggestions for gifts or presents for this holiday season.

Its ability to analyze large volumes of data and detect patterns and trends makes it an indispensable tool for companies, especially when making decisions. And ESG is no exception. Moreover, the urgency of companies to identify, measure and communicate the impact of their activity to their stakeholders makes ESG issues a catalyst for advancing the development and application of artificial intelligence. In fact, in the Global Tech report recently published by KPMG, 46% of respondents in Spain place ESG issues among their priorities when investing in innovation.

Artificial intelligence has made its way into each of the ESG acronyms. For example, through advanced algorithms, companies can automate the analysis of their energy consumption, their use of raw materials or their carbon emissions in order to identify patterns and, on the basis of these patterns, propose solutions to reduce their environmental impact. This process can also form the basis for developing new products and services that meet the demands of an increasingly environmentally conscious consumer.

We must not forget that consumers and, in a broader sense, citizens, have increased their demands on the commitment of companies to the prosperity and development of society. In this sense, employment is perhaps the most obvious example of this contribution and, in particular, the promotion of diverse and inclusive environments. This is an area in which artificial intelligence, through prediction and optimization models based on Machine Learning, can also contribute differential value. By implementing this technology in people management, it is possible to know the real performance of the company in aspects such as diversity, salary equity or employee satisfaction with specific metrics, which allow to check the progress achieved. These artificial intelligence models make it possible to identify areas for improvement and promote a more equitable and socially responsible work environment and, therefore, more attractive to professionals with the skills that the organization needs at a time when talent determines the growth and transformation capacity of companies. Even the contribution of value generated by artificial intelligence itself is linked to the company's talent.

In addition, the analysis and predictive capabilities of artificial intelligence help to strengthen corporate governance. This tool is capable of gathering financial, compliance and risk-related data from both the company itself and its suppliers. In this way, it not only provides the necessary knowledge to make decisions that optimize the business from an operational point of view, but also to ensure that the company operates with transparency and accountability throughout its supply chain.

These are just a few examples of the applications and benefits of artificial intelligence in the ESG field. However, to take advantage of its full potential, it is essential that it is based on three pillars: security, ethics and people. Firstly, the use and implementation of this technology must be carried out in secure environments, taking into account risks such as data protection and possible harmful uses, which also generate a great deal of concern among organizations due to their high reputational cost.

The solution to this challenge is to prioritize ethics in the design and development of models: this promotes socially responsible artificial intelligence. On the ground, this implies reinforcing transparency both in the selection of data, mitigating any possible bias and guaranteeing user privacy, and in disclosing the criteria on which automated decisions are made. In addition, this transparency exercise facilitates external evaluation, which certifies fairness and justice in algorithmic decisions.

Nor should we lose sight of the need to integrate artificial intelligence-related decisions into the company's ESG objectives. From an environmental point of view, it is essential to optimize model processing to reduce energy consumption, which implies using efficient algorithms and energy-sustainable hardware. In addition, a sustainable life-cycle approach to models is necessary, considering their impact on the environment from conception to disposal. By prioritizing efficient architectures and responsible resource management, we ensure sustainable and environmentally conscious artificial intelligence.

In short, we can say that ESG and artificial intelligence are mutually reinforcing: if we said earlier that the environmental, social and good governance objectives of companies were acting as a catalyst for investment in artificial intelligence, it is also clear that this technology reinforces and justifies the role of ESG issues as the backbone of the company's reputation and, consequently, as a driver of growth. Hence the need to integrate them into corporate strategies. As soon as possible.