‘We are looking at AI holistically across our portfolio as well’

AI Technologies: Overhyped, imperative or real opportunity?’ was the theme of Les Journées de l’Économie on 24 March. Ecorama Luxembourg spoke to Kaisu Christie, Group Chief Digital Officer at the European Investment Bank (EIB), on this hot topic. She believes the EIB has a role to play not only as a policy partner with EU institutions but also by “joining our forces together with private and public funders in Europe to really drive it forward as well.”

Ecorama Luxembourg: Europe faces increasing competition in artificial intelligence (AI) from global players. How can the European Investment Bank (EIB) strengthen Europe’s position in AI, particularly in supporting startups, research, and industrial applications?

Kaisu Christie: We are already making significant investments in AI across Europe. Naturally, we support the European Union’s strategic priorities to foster a digital Europe. We also recognize the exceptional talent that exists in Europe, and we believe it is essential to harness and develop this talent further.

As a bank, and in collaboration with the European Investment Fund (EIF), we play a crucial role in this ecosystem. To date, the EIB has provided approximately €3 billion in loans for AI-related investments across key sectors. These investments are not limited to companies developing AI technologies; they also include sectors such as healthcare, energy, the environment, transport, and manufacturing. It is essential that AI is integrated into companies of all sizes, across all industries. We have numerous examples that we would be happy to share.

E.L.: Specifically, could you share some of these examples?

K.C.: Certainly. Our support spans both large and smaller companies. Through the EIF’s equity portfolio, we have provided over €300 million in funding and guarantees to some of the most promising AI companies in Europe. These include Mistral, a leading French AI company, and DeepL, a German company specializing in machine translation, among others.

We view AI as a strategic investment area across the entire European landscape—supporting both established players and emerging startups. Our aim is to leverage the full range of financial instruments available to us to ensure that Europe remains competitive and innovative in this critical field.

E.L.: What are the main challenges and opportunities for the EIB in financing AI-driven innovation?

K.C.: A key priority for us is supporting the adoption of AI across all industries—not just within the core technology sector, but also in areas such as healthcare, manufacturing, energy, and transport. The goal is to drive innovation, improve productivity, enhance competitiveness, and generate broader economic benefits. At the same time, we are mindful of avoiding what we call « AI washing »—where investments are misdirected toward projects that use AI as a buzzword rather than delivering real, measurable value. Our focus is on ensuring that AI is used meaningfully to enable tangible progress.

Another significant challenge in Europe today lies in fragmentation. While we have excellent universities, a strong talent base, and a growing number of innovative startups—what one might call a « nursery » of potential—we still face difficulties in scaling these ventures. Our role is to help address this fragmentation by promoting pan-European funding mechanisms. This includes not only direct financing from the EIB but also mobilizing capital from our partners in the private sector and national promotional banks. The objective is to provide sustained financial support to help these startups grow and remain in Europe.

Let’s be candid: several promising AI companies that originated in Europe have been acquired by U.S. firms and are now headquartered outside the EU. This is a trend we are actively working to counter. We aim to ensure that sufficient funding—from both the EIB and the broader investment ecosystem—is available to retain and grow these companies within Europe.

A third point, which is both a challenge and an opportunity, relates to our role as the EU’s climate bank. As AI adoption increases, so does the demand for energy, given the computational intensity of AI systems. This presents a dual challenge: managing the environmental footprint of AI while also leveraging AI to support the energy transition. For example, AI can play a critical role in optimizing battery technologies, energy storage, and distribution systems.

We see a strong case for investing not only in AI applications and infrastructure, but also in AI-enabled solutions that advance sustainable, secure, and affordable energy systems across Europe. In this way, AI becomes both a beneficiary of and a contributor to Europe’s green and digital transitions.

E.L.: How do you see the Bank’s role evolving in shaping the future of AI in Europe?

K.C.: At present, there are numerous initiatives across Europe aimed at safeguarding the continent’s strategic autonomy in key technologies. One particularly important development is the introduction of the EU AI Act, which establishes a unified regulatory framework for artificial intelligence across all 27 EU member states. This is a significant step forward, as it ensures consistency in rules around trust, transparency, and reliability, rather than having each country develop its own approach. I see this as a foundational element in Europe’s AI strategy.

Another important aspect is the role of public investment. Frameworks such as Horizon Europe and the Digital Europe Programme are channeling public funding into digital innovation, including AI. As the EU’s financing arm, the EIB plays a central role in supporting these programmes. We are actively involved in discussions with the European Commission to help shape these initiatives, and we often act as a catalyst in the market—not only by providing loans, guarantees, and equity but also by mobilizing private capital and working in partnership with national promotional banks and other institutional investors.

Our approach to AI is comprehensive. We do not limit our focus to companies that develop AI technologies; we also invest across the value chain and across industries. Whether it’s SMEs or large corporations, we aim to ensure that funding is available to support AI adoption and innovation at all levels.

In summary, our role is threefold: – As a direct investor, providing capital to AI-related projects;- As a policy partner, working closely with EU institutions;- And as a market facilitator, bringing together public and private stakeholders to accelerate AI development in Europe.

E.L.: You mentioned a number of AI-related projects. What are the key criteria for selecting these projects, and how does the Bank ensure they contribute to Europe’s long-term technological and economic competitiveness?

K.C.: Our investment priorities are closely aligned with those of the European Union, particularly under the Digital Europe strategy. We work in close partnership with the European Commission through programmes such as InvestEU, which is one of the EU’s flagship investment initiatives, as well as the Connecting Europe Facility. At present, we are also engaged in discussions with the Commission regarding AI-specific funding mechanisms, which we consider a critical area of focus.

When evaluating projects, we assess how AI technologies contribute to broader EU goals, such as:- Enhancing competitiveness and productivity;- Supporting strategic sectors like healthcare, energy, and climate action;- Enabling the digital and green transitions.

For example, we look at how AI can be applied to optimize healthcare delivery, improve energy efficiency, and facilitate climate resilience. As the EU’s climate bank, we are particularly interested in how AI can support the energy transition—such as by improving grid efficiency, managing energy flows, and integrating renewable energy sources.

Importantly, we do not view AI solely through a technological lens. We take a holistic approach, evaluating how AI can be embedded across our entire investment portfolio to support sustainable, inclusive, and forward-looking economic growth.

E.L.: How is AI being integrated into the Bank’s own operations?

K.C.: We’ve increasingly begun to “eat our own dog food,” so to speak. In other words, while we fund AI adoption externally, we are also actively applying it internally—both in front-office and back-office operations.

We’re using AI to enhance the day-to-day productivity of our staff and to support decision-making at the management and governance levels. Several use cases are already underway. For example, we are employing chatbots to assist our lending officers in accessing information more efficiently, enabling them to perform their work more effectively.

In our IT development processes—particularly in my own area—we are testing AI to accelerate software development and support business transformation initiatives. Like many organizations, we are also exploring how AI can help us search, aggregate, and analyze information. As a data-intensive institution, this kind of analytical capability is especially valuable.

A key aspect of our journey has been identifying high impact use cases that allow us to build internal expertise and operationalize AI in a meaningful way. We began this journey a few years ago, and we are continuing to expand our capabilities.

Equally important is our investment in people. For many of our staff, AI is a new technology, and as with any innovation, there is a learning curve. We are committed to equipping our teams with the skills and understanding needed to use these tools effectively and responsibly.

E.L.: Do you invest in your people? Do you have a structured plan or schedule for that?

K.C.: Yes, absolutely. We have a very active internal AI community. When we first began this journey, it started with a small team working alongside business stakeholders—colleagues from risk, compliance, and HR—exploring what AI means for us in terms of skills, ethics, technology, and use cases.

Today, that community has grown to include over 1,000 members. Participation is entirely voluntary—any colleague can join. We offer a mix of formal and informal learning opportunities. This includes structured training sessions, as well as peer-to-peer knowledge sharing, where colleagues exchange experiences, tips, and lessons learned.

Our approach to learning is both technical and ethical. When we develop AI solutions, we do so collaboratively—bringing together business experts and technology specialists. But we also pay close attention to the ethical and regulatory dimensions. We ensure that all AI applications are developed in a way that is compliant with relevant regulations and aligned with our institutional values.

In essence, there is both a « hard » side—focused on technical skills and compliance—and a « soft » side, which includes values, ethics, and responsible innovation. I’m particularly proud of how engaged our community is. While part of the initiative is centrally coordinated, much of the momentum comes from the passion and initiative of our own people. It’s a collaborative, evolving effort that reflects our commitment to responsible AI adoption.

E.L.: What role does AI play in enhancing decision-making and financial processes?

K.C.: We are already leveraging AI in several areas—both in front-office and back-office operations. For example, in our treasury operations, we use AI to support the calculation of funding positions and funding costs. Previously, this was a more manual and time-consuming process. Now, with AI, our colleagues can quickly model different scenarios, explore various options, and assess what actions might be appropriate in the market on a given day or within a specific timeframe.

However, it’s important to emphasize that there is always a human in the loop. AI serves as an assistant, providing insights and recommendations, but the final decisions remain firmly in the hands of our experienced staff.

In back-office financial processes, such as invoice handling, we are also applying AI to enable straight-through processing. This improves efficiency, reduces errors, and accelerates payment workflows. So, AI supports both strategic decision-making and operational efficiency.

Given that we are a financial institution—and trust is central to our mission—we ensure that human oversight is built into all AI use cases. This safeguards the integrity of our processes and ensures accountability at every step.

E.L.: How does the EIB ensure that the AI initiatives it finances align with European values, ethical guidelines, and emerging regulatory frameworks?

K.C.: We are fully committed to embedding the principles of the EU AI Act into both our internal operations and the projects we finance. Our approach has been to treat the Act as a guiding framework and to build internal governance structures that comply with its requirements.

One of the strengths of the EU AI Act is its risk-based approach. It helps us identify which AI use cases are considered high-risk—requiring stricter oversight and controls—and which are lower-risk, where a lighter regulatory touch may be appropriate. This structure allows us to apply the right level of scrutiny based on the potential impact of each use case.

Internally, we’ve developed a framework that includes: – training and capacity building for staff; – clear accountability for AI solution owners; – rigorous testing, monitoring, and transparency of AI use cases;- and a structured review process that incorporates diverse perspectives (legal, HR, data protection, compliance, and business) to ensure a 360-degree assessment.

This multidisciplinary approach ensures that we balance innovation with responsibility. For example, a business owner may be eager to deploy AI quickly, but our legal or compliance teams might highlight ethical or regulatory considerations that need to be addressed. This dialogue helps us refine and adapt solutions before implementation.

Another advantage we have is our position within the EU institutional ecosystem. We collaborate closely with other EU agencies and institutions—both here in Luxembourg and in Brussels. This allows us to share best practices, align on standards, and even reuse solutions where appropriate. It’s a practical way to avoid duplication, maximize efficiency, and ensure a cohesive approach across the European Union.

Ultimately, our goal is to build trust from the outset—both in how we use AI internally and in how we support its adoption across the EU. By combining robust governance with collaboration and shared learning, we aim to ensure that AI is developed and deployed in a way that reflects European values and serves the public good.