65% of companies in Spain risk becoming irrelevant if they do not adopt big data strategies, a sector growing at an annual rate of 30%. Machine Learning allows models to learn automatically but requires human supervision to avoid negative outcomes, as seen with Microsoft’s bot. The quality and quantity of data, as well as accurate and efficient labeling, are key to successful Machine Learning model training.
Automation and artificial intelligence (AI) are creating more jobs than they are replacing. By 2025, it is expected that 97 million new jobs will be created, surpassing the 85 million workers projected to be replaced. The demand for roles such as data analysts, AI and machine learning experts, data scientists, and synthetic data builders is constantly growing. Additionally, AI is driving hybrid work, where machines handle repetitive and dangerous tasks, allowing humans to focus on higher-value activities.
Customer relationship management goes beyond technological platforms and includes strategies, data analysis, and business objectives. CRM (Customer Relationship Management) systems enable comprehensive management of sales, marketing, and customer service, leveraging the proliferation of technology and personalization of relationships. The use of CRM has grown significantly, with more than 62% of Spanish companies using a CRM to analyze information and for business purposes.
Vertical farms allow for sustainable and efficient crop production. Robotic technology and artificial intelligence are key in this process, optimizing everything from monitoring and planting to harvesting. The adoption of robotics in vertical farming will continue to grow, as it can address most challenges and improve the entire crop growth cycle.
Voice recognition has advanced from interpreting just numbers to being used across various industries and devices. A voice assistant market worth $31.82 billion is expected by 2025. Voice-controlled devices in smart homes and the integration of artificial intelligence are revolutionizing automation and personalizing experiences.
Digital transformation is impacting the sports world, including football, through the use of artificial intelligence (AI) and data analytics. At the 2022 Qatar World Cup, teams had access to advanced statistics generated by FIFA to evaluate their performance. Data and video analysts were used to gather information during matches. The current challenge is not just to accumulate data, but to develop the ability to interpret it and obtain relevant information for strategic decision-making. AI and analytical tools enable the use of data to develop strategies based on strengths and weaknesses. The question is whether data will replace intuition in football.
The new generation of robots in the culinary world uses IoT sensors and artificial intelligence to perform tasks in the kitchen efficiently. These robots can help address staff shortages, reduce food waste, and improve the customer experience. Examples include an autonomous AI system that automates cooking, a barista robot that prepares up to 400 cups of coffee, and a robot that fries chicken wings, increasing food production speed. The food industry is experiencing technological advances, and more complexity is expected in data management and training to program the robots.
Compared to other fields, robotics has particular characteristics because its goal is to enable a physical agent to interact with the real world.
The pandemic has boosted e-commerce and home deliveries, highlighting the
importance of the "last mile" in the customer experience. Logistics increasingly requires data management and the adoption of technologies such as artificial intelligence, Big Data, and the Internet of Things to meet consumer demands. Despite the growth of e-commerce, digitalization in the logistics sector in Spain is still lagging behind.
Optimizing the last mile is achieved through smart warehouses, route optimization with Big Data, and real-time tracking, which improves profitability and the customer experience.
La mayoría de las pymes españolas confían en la digitalización y planean invertir en ella en los próximos tres años, sin embargo, aún necesitan realizar una transformación digital centrada en la gestión eficiente de grandes volúmenes de datos. El uso de estrategias de Big Data puede ayudar a estas empresas a abordar problemas de manera proactiva, generar nuevas oportunidades, mejorar la eficiencia operativa y fidelizar a los clientes. Sin embargo, las pymes se enfrentan a desafíos como la integración de diferentes fuentes y tipos de datos, la necesidad de procesar grandes volúmenes de datos rápidamente y la selección y preparación adecuada de los datos. Para tener éxito en una estrategia de Big Data, las pymes deben definir claramente los problemas de negocio, seleccionar y preparar los datos adecuados, almacenarlos de manera segura y realizar un análisis exhaustivo para tomar decisiones basadas en datos. El inicio de un nuevo año es un momento oportuno para implementar estrategias de transformación digital y Big Data, lo que requiere un cambio de mentalidad y enfoque estratégico en estas empresas.
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