The impact of AI on the ban­king indu­stry and its employ­ees in Euro­pe and beyond

With the release of ChatGPT in November 2022, a new era of artificial intelligence has begun. Companies worldwide started investing heavily in the new possibilities with Generative AI to remain competitive. Europe is in global competition. This raises the question of where Europe currently stands in the AI race compared to the big players USA and China and what influence AI will have on employees in Europe, especially in the banking sector? Likewise, it is to be discussed which options banks and also the Social Partners have to react to the developments and to mitigate any negative effects. 

These questions were analysed in a research study conducted by ARIX Research on behalf of the European Social Partners in the banking industry throughout 2023 and the first quarter of 2024. The study is based on secondary research combined with expert interviews in 10 European countries. The following information is an excerpt from the study including some updates and amendments.

Europe’s struggle and potential in the global AI race

The European Union has fallen behind global leaders like the US and China in the rapidly evolving field of artificial intelligence. Despite ambitious strategies outlined in the European Commission's action plan ‘Shaping Europe’s Digital Future’, many experts remain sceptical about Europe’s ability to close the gap soon. Overall, the EU is making progress but needs to accelerate its efforts in AI.

According to BCG Henderson institute, there are two main aspects for assessing a nation's competitiveness in the field of artificial intelligence.

First, a country's capacity to develop AI, considering factors such as the availability of skilled talent and access to startup funding from private and governmental sources.

Second, the capacity to deploy AI, assessing whether companies could commercialize and scale AI applications. This requires an AI-ready market, ample local data for training algorithms, and adequate infrastructure like supercomputers.

According to BCG and research conducted by ARIX, the European Union has fallen behind global leaders like the US and China in AI.

At present, the US is leading in the capacity to develop AI, China in the capacity to deploy AI. The European Union is leading only in ethical standards.

The US has the leadership in the capacity to develop AI, with significant numbers of BigTech & AI startups, AI patents, private investment and AI talents.

China, on the other hand, is leading in the capacity to deploy AI. This means that China is excelling in the application commercialization (e.g. usage of companies and impact on GDP) and implementation on an industrial scale (e.g. data availability through upload and download of mobile data, facial recognition by CCTV).

The EU is recognized for its high ethical standards in AI development, especially with the European AI Act, in force since 1 August 2024. The EU's approach to AI emphasizes ethical considerations, data privacy, and regulatory frameworks to ensure responsible AI usage.

If the EU were considered a single entity, it would be closer to the two champions in AI.

The key challenges in the AI race for Europe

The fundamental question arises as to whether Europe has a chance of catching up in the AI competition.

Europe faces several significant challenges in the AI race, including the fragmentation of its digital market, a talent drain to the US, difficulties in securing venture capital for AI start-ups, and regulatory challenges posed by the EU AI Act. Additionally, the rising energy demand driven by generative AI is a concern.

1. Fragmentation of the digital market: The EU's digital market is fragmented, which hinders its potential to be larger and more competitive. Brexit has further increased this fragmentation, with the UK being an important AI player.
2. Talent drain: Europe is losing AI talent to the US, leading to a digital skills gap. Companies in the EU will need to proactively upskill their current employees to address this issue.
3. Investment barriers: US companies, such as OpenAI, attract massive investments, while EU AI start-ups struggle to secure funding and often end up moving overseas.
4. Regulatory challenges: The EU AI Act is seen by some experts as a potential hindrance to AI innovation but could also be a competitive advantage. Users may favour EU products over those from the US or China due to higher ethical standards.
5. Energy demand: Generative AI is expected to drive power demand to exceed 5% of Europe’s electricity consumption by 2030. Competitive electricity prices are essential for Europe to remain a hub for generative AI applications.

These challenges highlight the need for Europe to address these issues to remain competitive in the global AI landscape.

^{(Source: BCG: Europe can catch up in AI, but must act – today, June 2020; Pitchbook: Why Europe struggles to scale its deep-tech start-ups,
March 27, 2023; Carnegie: Europe and AI: Leading, Lagging Behind, or Carving Its Own Way? Jul 9, 2020; McKinsey. Europe's AI Opportunity, 01Oct24.)}

AI adoption worldwide

AI adoption worldwide has increased dramatically in 2024 after years of little meaningful change.  Over the past six years, the adoption of AI in the respondents' companies has been around 50 per cent. This year, adoption has risen to 72 per cent, according to the survey. This is mainly driven by the use of Generative AI.

Expected global AI adoption by industry

The expected global AI adoption by industry in the upcoming years shows that 83% of financial services firms are expected to have adopted AI technologies by 2027. This places the financial services industry among the industries most affected by AI adoption.

AI investments of European banks

A study published by Infosys from May 2024 stated that European banks allocate less of their technology budgets to AI compared to the global average. Instead, they focus more on cybersecurity, open banking/APIs, and real-time payments. Such an allocation indicates a strategic prioritization of immediate security and operational needs over AI development. This puts European banks at a strategic disadvantage in AI compared to other countries.

Investments in AI talent development

Even though some European banks are prioritizing immediate operational needs, others invest in long-term AI talent development and innovation.

• For example, BBVA in Spain is among the top European banks investing in AI talent. They run an AI data university for data scientists and specialists, with more than 50,000 participants over six years. BBVA has also partnered with OpenAI to offer Generative AI-specific courses.
• BNP Paribas in France hosts an AI Summer School, which attracts over 2,000 employees annually and partners with Mistral AI.
• HSBC in the UK has an AI Ambassador program that trains employees in AI, addressing different levels of technical skills to represent the bank on AI and share their knowledge with peers.
• The Société Générale in France and the Danske Bank in Denmark host AI days and hackathons to engage employees and foster a culture of continuous learning and innovation.

These examples show the levels of AI investment and focus among selected European banks and highlight the possibility to embrace AI at a larger scale.

^{(Source: Evident AI Index, Dec. 2024)}

Use cases of AI in finance

The most reported AI use cases in finance involve improving customer relations (e.g. marketing and profiling), back-office operations such as process automation, organisation and management followed by fraud detection and prevention

The following are some specific examples reported by bank employees in different countries, who stated positive experiences, but also negative side-effects.

1. Speech Analytics System (Denmark): A system that measures and assesses employees' empathy during customer conversations to improve customer service. It creates an "empathy score" based on sentences like "I understand" and "that is indeed annoying." However, some employees achieved a low score in a discipline they believed themselves to be good at, leading to frustration and mistrust towards management.
2. Chatbot for Customer Dialogue called "David" (Romania): This chatbot aims to automate repetitive tasks by providing quick answers, customer information, templates, reports, access to FAQs, and current regulations. It helps to maintain a positive climate in the front office area, frees up time, and manage the job situation better.
3. AI-Powered Portal for Employees (Ireland): A portal that allows employees to find answers quickly by typing queries, and AI guides them to the right answers. It uses Power Apps to pre-populate forms, reducing repetitive data entry. This increases efficiency and reduces frustration for users but requires a cultural change and adoption of the new system.
4. Contract Analysis Tool (Germany): This tool checks a large number of contracts for specific clauses, saving time and reducing the need for manual work from 20 days to 2 hours.

These examples highlight both the positive and negative impacts of AI use cases in the financial sector. While AI can improve efficiency and customer service, in certain circumstances it can lead to frustration and require significant cultural changes within organizations.

^{(Source: ARIX Qualitative survey among employers and employee representatives in the banking industry in 10 countries, May 2023)} 

Impact of AI on jobs

The adoption of AI is expected to lead to a net decrease in the European labour demand by 2030, according to McKinsey Global Institute. Specifically, the finance sector could see a shortening in labour demand of 200,000 jobs, with the largest reductions in office support and customer service roles. This decline represents a reduction from 5.8 million to 5.6 million jobs, approximately 3.4%.

In line with these trends, approximately 600,000 individuals in banking might need to change occupations by 2030. The shift from traditional banking to digital platforms is expected to drive demand for professionals in STEM (Science, Technology, Engineering, Mathematics) and management roles. Demand for technological skills is expected to increase, and the importance of social and emotional skills will also rise, reflecting an increased need for people in managerial and interpersonal roles.

The top five job roles that are expected to see an increase in employment by 2030 are business and financial specialists, executives and managers, computer engineers and specialists, computer support workers, lawyers and legal professionals.

The bottom five roles that are expected to see a decrease in employment by 2030 are, financial clerks and tellers, office support workers, information and record clerks, administrative assistants and sales workers.

The newly created positions will not directly compensate for the job losses, as the increases and decreases occur in other positions and other areas in the company.

It should be noted that the forecast of job losses lags behind that of employees retiring by this time. It makes a difference whether there are real job losses or whether positions that become vacant due to retirement are not filled, insofar as there is no impact on current employees in the latter case.

AI impact on employment in banking until 2028

According to qualitative interviews conducted by ARIX in 10 countries among financial services representatives, the impact of AI on employment in banking over the next five years includes both positive and negative aspects.

Positive aspects:

• Efficiency and productivity: AI can streamline processes and rationalize routine tasks.
• Job enhancement: AI frees up time for more complex and creative tasks, it can enrich work.
• Filling the employee gap: AI can help address the employee gap created by an aging population and retiring boomers.
• Creation of new roles: AI can create new roles, particularly in IT but also beyond.
• Customer service improvement: AI can enhance customer service through hyper-personalization.
• Flexibility: AI can support flexible work arrangements, such as a four-day workweek and flexible work locations.

Negative aspects:

• Uncertain impact on employment: There is uncertainty about whether AI will lead to a net increase or decrease in jobs.
• Job displacement and degradation: AI could displace jobs, including higher-value roles, which need a master’s degree or PhD.
• More freelance jobs: The rise of AI may lead to an increase in freelance work.
• Work intensification: As AI takes over routine tasks, there is a need to adapt to more demanding and diversified job roles. When AI becomes standard, the pressure to deliver work results faster and better will increase.
• Need for employee skills adaptation: Employees will need to adapt their skills to work with AI - this might cause problems for elder employees.
• Regulatory uncertainty: There are still uncertainties around regulations related to AI.
• Ethical concerns: Issues such as data privacy, data security, and discrimination are still potential challenges.
• Over-reliance on AI: There is a risk of losing critical thinking and problem-solving skills due to over-reliance on AI.
• Global competition: The global competition in AI could intensify and impact job security.

^{(Source: ARIX Qual Interviews, n=20, 04/2023 
Q11. What are your expectations how the development of AI/automation will affect the employment and workplace in the banking sector in the upcoming five years? *The interviews took place before the European AI Act was finalised.)}

Possible strategies for banks to stay fit and maintain good jobs for employees 

As a general outlook, the interviewees recommended for banking institutions to focus on the following aspects until 2030.

Measures for the fitness and stability of banks:

• Investment in AI: Banks should invest heavily in digital and IT innovation, including AI.
• Universal banking system remains the best strategy to enable banks to have a holistic view of the financing of the economy and to adapt to changes.
• Communication and education on the role of banks in financing the economy and making it more secure (in contrast to Fintechs).
• New services: Banks should not give up their role as financiers of the economy and should offer new services to adapt to changes.
• Improve business model and profitability: Banks should prepare for resilience and invest in strategic priorities to improve the business model and profitability.
• Monitor and adapt to trends: Follow and monitor trends to stay updated with the changing landscape and adapt strategies accordingly.
• Foster innovation to stay competitive in a challenging environment.
• Definition of an AI-strategy anchored at top-level in the organization.

Measures to maintain and develop good jobs for employees:

• Attractive workplace: Banks should invest in attractive workplaces and be more employee-oriented in their HR policies, emphasizing satisfaction and show care for employees.
• Good working conditions, collective agreements, and institutional employee co-determination can make the company more attractive.
• Flexibility, remote working, and reconciliation measures are essential for employees to combine work and personal life.
• Training and competence development: Banks should invest in their people and innovative training regimes to provide training and career development opportunities, including competence development, reskilling and upskilling of employees to meet digitalization trends.
• Coaching with retraining and redeployment options: Measures like coaching, support for personal interests, and social benefits can help retain employees.
• Diversity and inclusion: Adoption of inclusive practices that value diversity in their workforce, such as gender and intergenerational diversity.
• Value-creating team: Nurturing good relationships between managers, employees, and colleagues.

^{(Source: ARIX Qual Interviews, n=20, 04/2023; 
Q20. What options and strategies can banks pursue to stay fit for the future while at the same time preserving good and satisfying jobs for their employees?)}

What can be the role of Social Partners to influence the development of AI positively?

Social Partners play a crucial role in shaping the development of AI and ensuring that it benefits both employees and organizations according to the experts ARIX has interviewed.

Their role includes several key measures:

1. Collaborative social dialogue and collective bargaining: Social Partners should engage in social dialogue, negotiations, and collaboration to ensure a balance between technological advancements and human rights.
2. Facilitate AI adoption: Social Partners can facilitate AI adoption by assisting in selecting and implementing AI technologies and ensuring fair, flexible responses to AI-driven changes.
3. Develop guiding principles and frameworks: They should establish guiding principles and transparent frameworks from a European perspective to support countries and organizations to choose their own measures.
4. Promote learning and skill development: Social Partners should promote communication and learning from each other, colleagues, representative and regulatory bodies, as well as identifying training needs and skills requirements to cope with rapid changes in the workplace and achieve better outcomes.
5. Advocate for ethical AI & transparency: Social Partners should advocate for ethical AI development that improves safety and transparency, to ensure respect for fundamental values and to avoid bias, exclusion and discrimination.
6. Support legislation by enhancing existing rights and shaping of new rights, e.g. the right to training and protective rights like oversight of automated decisions. Social Partners can engage in dialogue with policymakers to raise awareness and ensure appropriate regulations and legislation.
7. Foster industry attractiveness by innovation and learning. Social Partners can foster an attractive industry that values performance development, innovation, learning, and creating a safe and contextually appropriate environment.

These measures help ensure that AI development is responsible, ethical, and beneficial for both employees and organizations.

^{(Source: ARIX Qual Interviews, n=20, 04/2023; 
Q22. What can be the role of the Social Partners to influence the development of ethical and responsible AI/digitalization and agile working in a positive way?)}

Key take aways:

1. AI-leadership: The US leads in AI development, China in AI use. The EU leads on ethical standards and it will need substantial efforts to close the gap.
2. Key challenges for Europe are a fragmentation of the digital market, drain of AI talents, a lack of venture capital and a rising energy demand.
3. Adoption: 83% of financial services firms are expected to have adopted AI technologies in the next 5 years.
4. AI Investment: European banks spend less on AI compared to the global average.
5. AI use cases: The main use cases involve improving customer relations, back-office operations (automation) and fraud detection.
6. Impact on jobs: AI will cause job loss but also job increase in the next years. Approx. 200,000 jobs in finance in Europe are at risk and about 600,000 individuals might need to change occupations by 2030 according to McKinsey Global Institute. On the other hand, it should be noted that the forecast of job losses lags behind that of employees retiring by this time, which is likely to cushion the impact.
7. Views on AI: The supporting role of AI, the creation of new roles and possible job enhancement are viewed positively, while potential job losses, and ethical concerns are seen as challenges.
8. Banks need to balance their need for strategic prioritisation of AI with a focus on profitability and customer satisfaction with employee well-being and skill development being one of the priorities.
9. The Social Partner's role includes collective bargaining, setting frameworks, promoting skill development, and advocating for ethical AI.