In 2007, a company dedicated to selling office paper undergoes a profound internal transformation. For the first time, the headquarters orders the creation of a website to centralize sales, displacing the traditional door-to-door sales model. This decision generates concern among some employees, who perceive digitalization as a threat to their way of life. The situation leads to a series of comedic events, such as the director and his assistant, who blindly follow GPS instructions and end up driving their car into a pond. This episode, far from being real, corresponds to one of the most memorable plots from the series 'The Office.' Today, the story could be updated: the website would be replaced by artificial intelligence, reflecting the current challenge many companies face in integrating this technology into their daily operations. Expectations for AI as a driver of efficiency and automation are high. Institutions like MIT and consulting firms like McKinsey predict that AI adoption could increase business productivity by 20% to 40%. In the context of 'The Office,' AI would have allowed salespeople to anticipate customer loss through purchase pattern analysis, automate personalized emails, or plan more efficient delivery routes. However, the current enthusiasm for AI has not yet translated into immediate results. “There is a hype, and results will take time to arrive, but the implementation period will be shorter than for previous technologies like the cloud or the internet,” says Myriam Blázquez, general director of Experis. David López, dean of the MBA at Esade, adds that this process follows the so-called “J-curve”: first, there is investment and learning, and then the real impact on productivity comes. The real challenge for companies is not just technological but also organizational and cultural. “Within companies, different adoption rhythms coexist: some employees integrate AI intensively, sometimes without sufficient control, while others show resistance or skepticism. Additionally, many organizations approach AI in a tactical and poorly coordinated manner,” explains López. Adapting processes to AI can be key to business survival, especially after the pandemic and with the expansion of robotics, which is widening the productivity gap between leading and lagging companies, according to the Productivity Council in Spain. Redesigning processes and workflows can generate significant efficiencies, but it also involves changes in professional profiles and requires training, as well as quality data to measure impact, Blázquez points out. In Europe, AI adoption is uneven. With the imminent retirement of the baby boom generation, the continent needs to increase its productivity, and AI is a key tool. According to Eurostat, by 2025, 15% of European workers will use AI regularly, although with significant differences between countries: Malta (29.6%), Denmark (27.2%), and the Netherlands (26.6%) lead, while Hungary (1.3%), Romania (5%), and Italy (8%) lag behind. Spain slightly exceeds the average, with 18%. The differences between countries are reflected more in investment and institutional preparedness than in productivity. According to the 'Stanford AI Index Report,' in 2024, private investment in AI in the United States was $109.1 billion, compared to $9.3 billion in China and $4.5 billion in the United Kingdom, indicating very different adoption trajectories.