By Greg Fuller

Artificial intelligence is transforming Europe’s financial services and banking sector, driving innovation in fraud detection and personalised customer experiences. Greg Fuller highlights that without targeted investment in AI literacy, institutions risk underutilising advanced systems. Building workforce capability through structured training, ethical governance, and continuous learning is essential for long-term competitiveness and resilience.

The pace of change is only accelerating. In 2025, the skill requirements for AI-exposed jobs are evolving 66% faster than for other positions. From junior analysts to senior compliance officers, employees must now adapt to a workplace where AI is not just a tool, but a collaborative partner.

To unlock the full value of AI, European financial institutions must shift their focus from technology acquisition to human enablement. This means embedding AI literacy at every level of the organisation, ensuring that every employee has the knowledge and confidence to work effectively alongside intelligent systems.

The foundation for future-ready finance in Europe

AI literacy is becoming a foundational capability, not only for driving innovation, but for ensuring long-term resilience and competitiveness. However, it should be viewed as the starting point of a broader organisational transformation, not the end goal.

While technical teams must understand core elements of AI such as data governance, regulatory compliance and the ethical use of large language models, true AI readiness requires a shift in mindset across the entire organisation. It’s not just about understanding how AI works; it’s about recognising how it can enhance human decision-making, streamline operations and unlock new sources of value.

When professionals across departments understand how AI can support their work, they’re more likely to trust and embrace it. This familiarity accelerates adoption and fuels innovation, as employees begin to identify new, high impact cases for AI within their own roles.

To sustain this momentum, financial institutions must build a culture of continuous learning and adaptability. This goes beyond technical training and includes developing essential “power skills” such as critical thinking, collaboration and ethical reasoning to ensure employees can thrive in an AI-augmented environment.

How can FS&B firms build AI literacy skills among employees?

While investment in AI continues to accelerate, many institutions face the challenge of ensuring their workforce is prepared to use these technologies both responsibly and effectively.

To close this capability gap, financial institutions must adopt a structured and inclusive approach to AI upskilling. This can be achieved through the following key steps:

1. Establish a skills baseline across the organisation 

Before launching any AI literacy initiatives, FS&B firms should assess their workforce’s current levels of AI awareness, data literacy and understanding of EU-specific regulations like the EU AI Act. This can be done through surveys, focus-groups or formal assessments.

These assessments should be framed as developmental, not evaluative, tools for employees. This helps build a culture of continuous learning and supports the development of personalised learning paths that benefit both individuals and the organisation. 

2. Align AI literacy with organisational purpose

AI literacy must be grounded in a clear, shared vision that connects AI to the organisation’s broader mission and values.  

Leaders must articulate how AI will support strategic priorities, from improving operational efficiency to enhancing customer trust. This message should be free from technical jargon and focused on how AI will augment human expertise rather than replace it. When employees understand that AI is a tool designed to empower their work, they’re more likely to embrace it with curiosity and confidence.

Equally important is establishing a shared understanding of what responsible AI use looks like. Institutions should develop a unified policy that clearly defines ethical and secure AI practices, outlining how new tools are evaluated and ensure that all AI applications comply with evolving regulatory frameworks. Incorporating these principles into the organisation’s AI narrative means that firms can create a culture of trust, accountability and innovation to ensure the technology is used responsibly.

3. Prioritise developing internal talent

Relying solely on external hiring to meet AI capability needs is neither scalable nor sustainable. Instead, financial institutions should prioritise developing internal talent by identifying how AI will reshape roles across the organisation and equipping employees accordingly.  

This begins with designing structured learning pathways that reflects the varying needs of the workforce. All employees should gain a foundational understanding of AI, including its ethical implications and regulatory context. For those in operational roles such as lending, compliance or trading, training should focus on practical, role-specific applications. Meanwhile, data specialists and analysts will require advanced technical instruction to build and deploy AI solutions effectively.

Learning programmes should go beyond theory. Real-world simulations, interactive tools and instructor-led sessions are essential to help employees apply their knowledge in context and build confidence in using AI day-to-day.One effective way to reinforce learning is by launching small, hands-on projects that allow teams to explore generative AI in their specific roles—such as automating a routine report, experimenting with prompt engineering for customer communications, or building a simple chatbot for internal FAQs. These projects not only build confidence but also help surface practical use cases that can scale across the organisation.

4. Track progress

To ensure AI literacy efforts deliver lasting value, financial institutions must track progress at both the individual and organisational level. This involves monitoring engagement in training programmes, the usage of AI tools, employee sentiment and measurable business outcomes such as increased efficiency, quicker decision-making or improved customer experiences. Consistently tracking these metrics enables institutions to fine-tune their AI strategies, demonstrate tangible impact and reinforce AI literacy as a core enabler of innovation and performance.

Adapting for tomorrow: Making AI literacy an imperative

The evolution of AI presents both a challenge and an opportunity for European FS&B firms. To navigate this shift successfully, organisations must treat AI literacy not merely as a technical skill, but as a foundational element of their organisational culture.

Embedding this mindset requires more than training, it demands proactive leadership, consistent communication and a deep-rooted commitment to continuous learning. Without strong support and direction from leadership, AI adoption risks becoming fragmented and misaligned with strategic priorities. Real transformation happens when AI is integrated across every level of the organisation, empowering teams to innovate, adapt, and create lasting value.

About the Author

In Greg Fuller’s 24+ year career with Skillsoft, he has been involved in tens of thousands of hours of content development projects; all focused on tech skills. Along the way, Greg has acquired several technical certifications such as PMP, CISSP, Oracle OCP, Cisco CCNP, and many others. Greg has applied much of the knowledge that he’s acquired working closely with several Fortune 500 companies to help build their upskilling programs.