AI Adoption in European Financial Services: Progress, Challenges, and Future Directions

European financial services firms are increasingly embedding Artificial Intelligence (AI) and Generative AI (GenAI) technologies into their operations to enhance productivity and efficiency. Yet, according to our second EY European Financial Services AI Survey, only a mere 9% of these firms consider themselves ahead of the curve in AI adoption. Despite high aspirations for a more AI-driven business environment, with 28% of firms accelerating their AI adoption over the past year, the majority remain in the early, experimental stages, particularly concerning GenAI.

Optimism amidst slow adoption

While 90% of firms have integrated AI to some extent and plan to increase annual investments, many are still in the early stages of adoption. A significant portion of firms report limited GenAI expertise within their workforce, with 29% feeling they lag behind their peers in AI adoption and only 9% believing they are ahead. However, there is a strong intent to boost GenAI expenditure next year, with 72% of executives planning to do so, and 69% expecting GenAI to significantly impact productivity.

Several factors hinder AI adoption in the financial sector, including workforce inexperience, regulatory uncertainty, and the rapid evolution of AI technology. The survey highlights significant disparities across different financial sectors, with 40% of banking respondents and 36% of wealth or asset management firms feeling they are behind their peers, compared to just 17% of insurance respondents. Interestingly, 17% of banks consider themselves ahead in AI adoption, the highest among surveyed industries, while 10% have not yet planned for AI integration.

Current AI use cases: back-office focus

AI adoption within the financial sector is predominantly concentrated on enhancing back-office operations, with a notable lag in customer-facing applications and client interactions. Almost half (48%) of AI use cases currently in production are focused on back-office functions, and approximately half of these use cases span data science, innovation, and product services. This trend highlights a critical gap, as only 21% of AI applications are directed towards customer-facing roles. Despite the potential for AI to revolutionize areas such as customer service, front-office operations, sales and marketing, and finance, these domains remain underutilized, signaling an urgent need for strategic realignment. Firms must reassess their AI deployment strategies to ensure a balanced approach that leverages AI's capabilities across all business functions, not just the back-office.

Over the next 12 months, companies plan to continue prioritizing AI use cases in back-office operations, data science, and product services, with little shift towards other critical domains. Interestingly, only 7% of respondents aspire to be recognized as market leaders in GenAI adoption, reflecting a pragmatic approach to integration rather than a pursuit of leadership. This cautious stance is further evidenced by the fact that document processing remains the leading high-impact use case for GenAI, with 66% of firms focusing on it. To truly harness the transformative potential of AI, financial firms must broaden their focus beyond back-office efficiencies and embrace AI-driven innovations in customer-facing and strategic areas.

Productivity

The survey reveals that 64% of banks expect GenAI to significantly impact productivity, compared to 74% of insurers and 73% of wealth or asset managers. Additionally, 93% of respondents believe up to 10% of roles could be made redundant due to AI integration, emphasizing the need for strategic workforce transitions and reskilling initiatives. A smaller segment of firms foresees that 10-20% of roles will be rendered redundant, further underscoring the urgency for proactive employment planning and adaptation to the evolving AI landscape.

Top concerns: GenAI knowledge and regulation

The two biggest concerns for integrating GenAI remain limited understanding and experience and regulatory uncertainty. Ethical issues, previously ranked third, have fallen to eighth place, with leaders now more concerned about the speed of GenAI evolution compared to their integration pace, followed by cost of implementation and control frameworks. Yet, concerns about GenAI ethics do still persist, with the top issues being the quality of output, transparency and explainability, privacy, and potential discrimination and bias. Only 14% of respondents have a fully functional AI ethics framework in place, with 31% in early development stages and 49% yet to develop one.

Recommendations for financial services firms embarking on their AI adoption journey

1. Invest in workforce training and upskilling

The survey highlights that 78% of financial services firms acknowledge their workforce's limited experience with GenAI technologies, yet only a quarter have initiated new training and upskilling programs. To bridge this gap, firms should prioritize comprehensive training initiatives to build internal AI competencies. This includes not only technical skills but also understanding the ethical implications and regulatory requirements associated with AI. By investing in workforce development, firms can ensure they are better prepared for AI integration and can leverage the full potential of these technologies to drive productivity and innovation.

2. Develop a balanced AI deployment strategy

Currently, AI adoption within the financial sector is predominantly focused on back-office operations, with significant underutilization in customer-facing applications and strategic areas. To truly harness the transformative potential of AI, firms must reassess their AI deployment strategies to ensure a balanced approach. This involves expanding AI use cases beyond back-office efficiencies to include customer service, front-office operations, sales and marketing, and finance. By doing so, firms can enhance client interactions, improve customer satisfaction, and drive overall business growth. Strategic realignment of AI initiatives will enable firms to achieve a more comprehensive and impactful AI integration.

3. Establish robust governance and ethical frameworks

Regulatory uncertainty and ethical concerns are major barriers to AI adoption, with only 11% of firms feeling prepared for upcoming AI regulations and just 14% having a fully functional AI ethics framework in place. Financial services firms must proactively develop and implement robust governance and ethical frameworks to navigate the complex regulatory landscape and address ethical issues such as transparency, privacy, and bias. Establishing clear guidelines and oversight mechanisms will not only ensure compliance with regulations but also build trust with stakeholders and mitigate potential risks associated with AI deployment. 

To maximize the potential of GenAI, financial services firms need to align opportunities with their business objectives, anticipate future innovations, develop internal expertise, and implement robust governance frameworks. While the effort involved is significant, the benefits that GenAI offers make the investment and strategic planning worthwhile.

About the research 

The EY 2024 European Financial Services AI Survey gathered insights from 116 financial services executives across 106 private and listed firms in Europe, representing a combined market cap of nearly €880bn. Conducted between September and November 2024, the survey aimed to assess the impacts of AI and GenAI integration on productivity, talent, skills, capital allocation, and risk management. The participants included senior leaders from a diverse range of financial institutions, including banks, insurers, wealth and asset managers, fintechs, and other cross-sector financial firms. The majority of respondents were C-suite executives, followed by heads of data & AI, enterprise architecture, and innovation, as well as directors and data science leads.

For a deep dive assessment versus survey benchmarks into the results of the study, please contact Laurent Moscetti or Ajay Bali.