AI That Is Not Affordable at Scale Is Not a Solution, It Is a Luxury Toy
Artificial intelligence is no longer judged only by its ability to innovate, but also by its viability at scale. As companies move from pilots to production, controlling costs becomes essential for AI to deliver real business value.
Pascal Bänninger
Artificial intelligence is no longer a technology reserved for pilot projects; it has become a tool that is increasingly integrated into companies’ operations. However, as organizations deploy intelligent assistants and AI-based solutions at scale, a new challenge is emerging: controlling the costs associated with their use without giving up the benefits they provide. This is one of the main conclusions drawn by MMG after several years of driving transformation projects for companies in sectors such as banking, insurance, and corporate procurement as part of their technological transformation processes.
While in an initial phase the goal was to identify use cases, validate concepts, and train teams, the conversation has now changed: the focus is on industrializing solutions and ensuring that projects remain sustainable. According to Pascal Baenninger, Managing Partner at MMG Management Consulting, companies are entering a second phase of maturity. “The focus now is on industrializing AI solutions: maintaining agility, ensuring regulatory compliance, and, above all, controlling costs.”
Many AI models operate under payment schemes linked to token consumption, a variable that is manageable during a pilot project but takes on a different dimension when the tool is used by hundreds or thousands of employees or customers. Pascal Baenninger cites the example of a major international insurer that initially decided to absorb all the costs of its AI infrastructure in order to accelerate internal adoption. When the bill reached several million euros, the company passed those costs on to the different business areas using the tools. “That was when new questions arose about which models to use, how to optimize consumption, and how to protect against price increases from providers.”
Many companies are now discovering that the real challenge of AI is not implementing it, but maintaining its profitability once adoption reaches massive scale.
From Pilot to Production: The Challenge of Scalability
For Pascal Baenninger, one of the most common mistakes is that pilot projects are designed with speed and idea validation as priorities. The problem appears when those same solutions evolve into corporate products and no one has anticipated aspects such as scalability, maintainability, or the economic impact of the chosen technology architecture. “Those who arrived first are paying for that learning now; those who arrive later can benefit from those lessons, although they also bear the cost of having waited.” And the situation does not seem to be exclusive to any one country. Both Pascal Baenninger and Jorge Yzaguirre, MMG’s strategic advisor for the Spanish market, believe that Spanish companies are following patterns very similar to those observed in other advanced markets. “Companies with a high degree of digitalization and a presence in sectors such as finance are following exactly the same path as Swiss, European, or North American companies,” explains Jorge Yzaguirre.
Beyond the choice of a specific tool, MMG argues that the success of a project depends on the ability to align business objectives, internal processes, existing systems, and available technological capabilities. This is a philosophy the firm encompasses under the concept of business engineering: an approach that MMG has developed and applied, and which addresses business transformation with the same discipline as an engineering project, from strategy to processes, systems, and execution. As Jorge Yzaguirre emphasizes, “provider selection is becoming increasingly important here. Organizations no longer assess only the functionalities of a solution, but also the sustainability of the provider, price stability, and the ability to maintain the tool over the long term.”
MMG aims to combine “Swiss precision” in project management with the dynamism and innovative capacity it identifies in the Spanish market.
Spain: Technological Talent and Growth Opportunities
MMG has recently opened offices in Spain to strengthen its presence in “one of the most dynamic technology markets in Europe.” The main reasons for this expansion are access to talent, proximity to international clients with operations in Spain, and the possibility of developing scalable teams while maintaining high quality standards. “Spain is one of Europe’s leading technology hubs, and Barcelona stands out especially in artificial intelligence,” says Pascal Baenninger.
The company already works with international organizations present in the Spanish market, particularly in areas such as financial services and insurance, and expects to leverage these synergies to accelerate its local growth. “I believe MMG’s philosophy fits very well with the Spanish market, and I see more than significant potential,” says Jorge Yzaguirre. There is another view he also shares with Pascal Baenninger: the focus on national talent. In contrast to the perception that technological innovation is concentrated in other markets, both highlight “the level of Spanish professionals and their ability to develop complex projects.” Pascal Baenninger also stresses that “the Spanish ecosystem has a particularly valuable characteristic: a greater willingness to experiment, test new ideas, and take on certain risks associated with innovation.”
This combination precisely sums up the motto with which MMG approaches this new stage: “Swiss precision, Spanish dynamism.” It is a formula that seeks to unite the consultancy’s planning and rigor with the talent, creativity, and adaptability it finds in Spain.
Source: El Economista