At the center of the AI experience

In a $4.8 trillion market, no one wants to be left out. This is the total volume AI will grow to by 2033, according to forecasts from UNCTAD, the UN body for Trade and Development. This also represents a 25-fold increase in AI value in 2023, when it stood at $189 billion. If these predictions come to pass, it’ll become the leading global technology, with a 29% market share, surpassing IoT, blockchain, and electric vehicles, among others.

So it’s understandable that, between future projections and current AI-driven success stories, companies are looking to ramp up investment. But it’s not always straightforward. It requires tactical planning of coordinated staff training and tech innovation to achieve results. A recent report by The Adecco Group on AI leadership found that in Spain in particular, 59% of business leaders encountered difficulties in reaching a timely consensus on strategies, 13% points higher than the global average. Even in this scenario, 55% of participants said their management team’s use of AI had improved decision-making, compared to 49% overall.

This lack of business clarity is also evident in a 2025 study by consulting firm Seidor that shows 32% of organizations that participated were unsure how to apply AI to gain competitiveness. Despite this, they’re still forging ahead with investment among their plans, with 73% of companies estimating increases up to 80% over the next year.

A self-contained strategy for AI

So there’s a dualling scenario with the recognition of AI’s importance and subsequent buying in, but also a misunderstanding of how to apply it to harness maximum business value. The response by some organizations, therefore, is to focus efforts across all other departments through a central organization, an AI center of excellence.

Energy company Iberdrola’s AI Centre of Excellence, for instance, was established in 2022 within the framework of its Artificial Intelligence for the Sustainable Energy Transition project. But the company’s work with AI dates long before that. “We’ve been applying AI throughout our value chain for more than a decade, with more than 150 use cases ranging from electricity demand forecasting, to fraud detection and route optimization,” says global CIO Sergio Merchán. “The emergence of generative AI marked a turning point. Its ability to accelerate the development of solutions and transform processes led us to go a step further, to create an AI competence center that concentrates talent, agile methodologies, and data governance in a single ecosystem.”

This center has been designed following a centralized model, a single hub with common standards, but deeply connected to the business, adds Merchán. “Each initiative starts with hybrid teams made up of experts from the center, like data scientists, AI engineers, cloud architects, and profiles from the business area,” he says. “This collaboration guarantees both technical excellence and strategic relevance.” It also acts as a cross-functional technology partner, offering governance services, standards, and support in responsible AI.

For Merchán, the center acts as a value accelerator across three strategic axes as well. “First, it enables new products and services, like smart assistants, automatic contract validators, and copilots for developers, which improve the customer and employee experience,” he says. “Then it drives operational efficiency through energy optimization algorithms, autonomous agents, and document automation, aligning profitability with sustainability. And third, it consolidates a true data culture. It democratizes AI so any business area can incorporate advanced analytics into its DNA.”

Among the benefits of its implementation, Merchán also highlights time-to-market speed for solutions that previously took a long time or simply weren’t viable. “In essence, it’s our lab of the future,” he says. “It’s a space where imagination becomes a prototype, and the prototype becomes business value.”

In addition, Merchán points to the potential expansion of these types of departments, with the growing integration of intelligent tools into business environments. “AI has ceased to be an experiment and has become the new operating system for leading companies,” he says. “Companies that aspire to compete globally will need a specialized core that combines data science, engineering, and business vision with a clear mandate to transform the potential of AI into tangible business results, and those who get ahead of the curve will have a competitive advantage.”

A launching off point

Another Spanish company already integrating smart tools to varying degrees into its operations is insurance company Mapfre. In March, they released official data that reveal more than 40% of transactions are handled by virtual assistants, 1.2 million customers already have automated document management, and seven out of 10 customers in Spain have interacted with AI solutions.

The company’s efforts in this field were recently complemented by a new AI center, which is still in the gradual rollout phase. It employs professionals from geographies like Brazil, the US, and Spain, and brings together initiatives from 14 countries in total. Diego Bodas, Mapfre’s director of AI and head of this new body, speaks of executing good AI governance through this center, from which all AI initiatives across the group are coordinated in a cross-functional, secure, and responsible manner. “This center is a key element of the global governance model,” he says. Bodas also considers it a strategic asset both for staying up to date and developing their own efficient expertise. Plus, having a global and diverse team helps analyze and adapt work and methodologies to local needs, from case prioritization to regulation itself, he adds.

Such a cross-functional nature is proven by working with professionals from not just other geographic regions but departments such as operations, technology, security and privacy, legal, and HR to ensure AI governance is carried out to the highest standards.

“The creation of this center represents a significant shift in the way we approach AI, considering it not just as a tool, but a cross-cutting mechanism that leverages synergies and capabilities across the group,” he says.

Promoting a source for AI use

According to Bodas, Mapre’s center is understood as a facilitator for listening to ideas, and advising, executing, and monitoring AI initiatives within the group. It’s also a means to manage development of use cases, partnerships, prioritization methodologies, inventorying, and measuring model performance. “In short, it’s a trusted and specialized team to support the business in decision-making and execution, to optimize results with consistent use and adoption of AI,” he says. 

He further highlights strategy and organization, data quality, risk and compliance, and privacy as key pillars of action. But the one pillar he considers transversal is people and talent. “It’s the teams that identify client needs and proactively propose use cases to solve identified challenges,” he says, adding that the center equally promotes AI training for the entire staff.