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AI and Data

Artificial intelligence:
innovation for the energy
of the future


Artificial intelligence is the fourth industrial revolution after mechanization, electrification, and computerization. It is being implemented rapidly both for businesses and home users: advances are occurring at a pace that are unprecedented in the world of technology. Plenitude also looks towards integrating new solutions into its innovation journey.

May 7th 2024

Artificial intelligence is a topical theme at the moment. We hear about it at work, at home, and in our free time. It is possible to give a simple and comprehensive definition of it by taking an explanation of the technology conceived in 1950 by Alan Turing, the famous British mathematician considered a historical father of AI who said, "A computer would deserve to be called intelligent if it could deceive a human into believing that it was human.”

AI has been a technological novelty since before 2023. We have been using it every day for about 10 years for some tasks that have now become routine: analyzing large quantities of data, doing a database search, translating a text, chatting with a company's customer service, looking at an interactive map on our smartphones. With no effort on the part of users and—almost always—with no perception of interacting with an artificial intelligence.

Since last year, there has been the rapid addition of generative AI services, making for a remarkable leap forward: people chat with systems that are able to make conversation and provide answers by fishing from a vast database of information. This is the fourth industrial revolution, which has progressed like never seen before in the world of technology, if we consider that the first three radical mutations were mechanization, electrification and computerization.

To date, we can summarize three areas in which artificial intelligence creates innovation.

Machine Learning

Machine learning is a fundamental component of artificial intelligence. Machine learning is the application of algorithms and analysis techniques that enable systems to learn and improve automatically from experience, without being explicitly programmed to do so. The advantage is the speed of calculation that leads to complex analysis results within seconds. Generative AI, that is, AI that can create content, uses a model of such machine learning. It learns and generates by improving; for example, by exploring huge amounts of unstructured data through conversational interfaces and summaries. What is it used for? To speed up and improve customer interactions, to localize content even in different languages, and to check document compliance.

Natural language processing

Natural Language Processing (NLP) means AI algorithms that can analyze, represent, and then understand natural language, both written and spoken. The purposes can range from understanding content, to translation, to producing text independently from data or documents provided. One example is customer service chatbots, with which we have become accustomed to interacting through voice commands or text-based conversation. The goal of these services is to direct standard user problems to first-level information and find the best solution in the shortest possible time. This saves time and human resources, which can be devoted to building a direct relationship between users and customer service operators for handling more complex and personal second-level requests.

Computer vision

Machines can see images and text and using algorithms, can process them beyond simply recognizing and categorizing the identified items or information. Computer vision that can extract and contextualize complex data can be useful for initiating other types of processes. One example of streamlining complex processes is thinking about how easy it is to pay a utility bill just by photographing the document, or to compare commercial offers by uploading dematerialized documents and without waiting on the phone for an operator to ask for information.

The energy sector is also beginning to implement tools that exploit the potential of AI. Plenitude has been studying for some time how best to integrate the adoption of AI services within its business processes, with projects addressing the most complex process automation areas to improve operational efficiency, for example, solutions to problems can be found in near-real time by adopting results-oriented real time strategies.

Plenitude brings useful innovation to people. This means using technology across the board daily and implementing it to bring value to employees, partners and customers. In the case of artificial intelligence, technology is a valuable tool to facilitate the best choice of business strategy in the shortest possible time. AI emerges as a catalyst for continuous innovation that focuses on building a digital core with Cloud, Big Data, and generative AI for the development of new models of work and services. Plenitude is aware of the significant impact of this latest technological revolution, and for this reason it is making the most of the potential of artificial intelligence while remaining consistent with its values as an energy Benefit Corporation.

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