How CaixaBank drives partner and customer relationships through AI

CaixaBank has integrated AI as a cornerstone of its technological transformation, with more than 2,000 employees already using AI agents to automate tasks and improve customer service, according to Mariona Vicens, the bank's director of digital transformation and advanced analytics. The bank, which serves over 12 million digital users, is embedding gen AI into its 2025-2027 Strategic Plan and Cosmos Plan to drive agility, efficiency, and personalized customer interactions, while also establishing a governance framework with an AI Office to ensure responsible use.

The transformation of the financial sector is no longer just about offering a mobile app or allowing customers to bank from anywhere. After years of digitizing services, institutions now face the more ambitious challenge of building a more personalized, agile, and intelligent relationship with millions of users who expect immediate answers, simple experiences, and service tailored to specific needs. The emergence of gen AI has accelerated this evolution. While banks have used AI models for years to automate processes, improve efficiency, and analyze large volumes of data, a new generation of conversational tools opens the door to a much more natural interaction between customers and financial institutions. Spain’s CaixaBank, for example, has positioned AI as one of the cornerstones of its technological transformation https://www.cio.com/article/4177613/4-recs-for-cios-to-stay-on-the-human-side-of-ai-transformation.html?utm=hybrid search . The bank, which has more than 12 million digital users, believes this change isn’t solely due to tech’s evolution, but also to a shift in user expectations. “Today’s customer is more digital, autonomous, and also more demanding in their relationship with the bank,” says Mariona Vicens, CaixaBank’s director of digital transformation and advanced analytics. “They not only interact more through digital channels, but also expect simplicity and personalized solutions at any time and from any device.” Although gen AI has made a big impact, CaixaBank says its commitment to these technologies began much earlier. But it now represents a qualitative leap. “It’s more focused on developing new models based on conversational applications,” she says. “The most visible improvement is that gen AI allows for more natural, contextual, and useful interactions for both employees and customers.” This evolution is part of CaixaBank’s 2025-2027 Strategic Plan, in which it identifies agility, new services, efficiency, and technological resilience as main and interconnected objectives. For Vicens, agility is particularly key. “It’s what allows us to respond to a customer who increasingly expects immediacy, and it’s also what determines the bank’s ability to adapt in an increasingly dynamic environment.” The Cosmos Plan, the specific roadmap for processes and technology framed within CaixaBank’s strategic plan, reflects this integrated vision. “It combines investment in technology, automation, and AI to enable a more flexible and efficient organization capable of evolving at the pace set by customers,” she says. “Ultimately, agility is the visible engine of change, but it’s only possible when all elements of the model advance in a coordinated manner.” AI is certainly at the forefront of how the bank operates. More than 2,000 employees are already using agents to automate tasks, streamline processes, and improve customer service — a number the bank expects to increase before the year’s end. “With this implementation, combined with the application of other models like gen AI integrated into office tools, we expect to scale the gains in productivity and agility,” Vicens says. While AI opens up new possibilities for transforming customer relationships, it also presents challenges related to regulation, transparency, and trust. For CaixaBank, innovation isn’t just about developing new use cases, but doing so under a governance model that ensures the technology is used responsibly. With that objective, the bank has defined a specific governance framework for these tools, with a corporate-level AI Office and a policy that anchors principles such as transparency and explainability, data fairness and privacy, robustness and security, and human oversight. This framework, CaixaBank explains, translates into concrete controls throughout the entire AI lifecycle: prior validation of use cases, structured risk assessment before implementation, corporate inventory of systems, subsequent monitoring, and incident management. However, it’s all based on the clear premise that relevant decisions can’t be entirely delegated to AI, so they must maintain human oversight. The entry of the EU AI Act https://www.cio.com/article/4150989/european-parliament-delays-implementation-of-parts-of-the-eu-ai-act.html?utm=hybrid search has placed financial institutions under evolving regulatory requirements. Far from seeing it as an obstacle, CaixaBank believes this framework fits perfectly with how it’s approached the tech all along. “It fits naturally, because we’re precisely structuring our AI governance model with this framework and other regulatory frameworks as a reference, and we integrate it into the AI lifecycle from the design stage and by default,” says Vicens. Corporate policy explicitly incorporates the regulations into its global risk management system. In practice, any AI-based application must follow a clearly defined process before being implemented. “This means that any use of AI must be identified, evaluated, and monitored,” she says. “Before developing a use case, its type, value, and feasibility are validated, and then its risks are assessed. And once implemented, its performance is monitored.” Of course, in a financial environment, customer trust remains a most valuable asset. All this transformation strategy is finding a tangible application in one particular development: a contracting assistant that accompanies the client through digital channels. The system acts as a first point of contact when a user requests information about a product from the CaixaBank website or app. From there, it can answer questions, provide contextual information, guide the conversation, and, when necessary, transfer the interaction to a specialist without the customer having to restart the process. For the bank, this ability to understand context is a key differentiator. “Unlike a chatbot that answers a collection of FAQs, this agent is a contracting assistant that understands the context of the conversation with the customer, provides support, and can escalate to a human,” she says. For products like pre-approved loans, it can even lead the conversation to the final step before closing. The bank emphasizes that human intervention remains an essential part of the process. “We see AI as a tool to inform, streamline, and support the customer to enhance their user experience in a way that complements the ongoing support provided by our team of specialized remote banking managers,” Vicens adds. Plus, customers can choose to speak with a human from the outset or at any point during the conversation, and the final contract is always signed with the assistance of a CaixaBank specialist. Beyond human oversight, the bank has established a framework to ensure the responsible use of AI. “It has defined responsible AI principles that cover the entire lifecycle of developments to ensure fair, transparent, responsible use, aligned with legislation and the group’s values,” she says. “Before deploying any AI solution aimed at customers, compliance with these principles is verified.” In the specific case of the contracting assistant, data protection is one of the essential elements. The information travels encrypted, and the model isn’t trained with the data sent to the LLM. Currently, this technology is available in 40 products and manages an average of 6,000 conversations per month — figures that, according to CaixaBank, provide clear metrics of scale and productivity. The implementation of the onboarding assistant is one example of a much broader strategy in which AI, data, and automation are used to transform the relationship between the bank and its customers. “The key is no longer just being available, but providing real value in every interaction, and strengthening trust through useful experiences tailored to each user,” says Vicens.