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Scaling AI in finance - A guide for executive managers
Study / 5 July 2024

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Prof Dr Bernd Wallraff is the professor of Business Administration / Business Psychology at CBS International Business School and a lecturer at the FS. He specialises in "The Impact of Artificial Intelligence on Leadership" and provides expert advice on innovation culture and digital leadership as well as supporting strategy and change processes.

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In the dynamic world of finance, the use of artificial intelligence (AI) is no longer a topic for the future, it has become a reality. But while many companies have already taken their first steps towards implementing AI, scaling these technologies poses a particular challenge. Our latest study provides valuable insights and practical recommendations on how to successfully scale AI in the financial sector.

The importance of scaling AI

Integrating AI into business processes can deliver significant competitive advantages. It enables more efficient processes, improved risk management strategies and tailored customer offerings. However, the true added value of AI will only be realised when these technologies are not only used in isolated pilot projects, but also in core processes in a targeted manner.

Successfully scaling AI is crucial for companies in the finance sector to maximise the full potential of these technologies. By scaling, companies can not only achieve individual improvements, but also consistently increase efficiency and optimise their core processes. This leads to faster and more accurate decision-making processes, making it possible to be more agile in responding to market changes and customer needs. In addition, scaling AI can help to reduce costs while increasing the quality and security of services.

The maturity model

Our study has developed a maturity model that comprises five central dimensions of AI scaling:

  1. Strategy & Organisation: A clear strategic approach is crucial. Companies must develop a comprehensive AI strategy that is integrated into the overall corporate strategy.
  2. Culture & Change Management: The transition to an AI-supported organisation requires an adjustment of the corporate culture. It is necessary to promote acceptance and understanding of AI technologies.
  3. Resources & Processes: Providing adequate resources and optimising processes are essential. Without dedicated budgets and structured processes, AI cannot be scaled effectively.
  4. Data: The quality and availability of data are the foundation of any AI application. A robust data strategy is essential.
  5. Technology & Infrastructure: The technical infrastructure must be scalable and flexible. This includes hardware as well as software solutions.

 

Recommendations for the financial sector

Based on our research, we have the following recommendations for executive managers in the financial sector:

  1. Strategic planning: Define clear goals for your AI initiatives and integrate them into the overall corporate strategy. This creates a solid basis for all further measures.
  2. Promote a change in culture: Create an environment that supports innovation and the use of new technologies. Training and information campaigns can help to address any reservations and increase the acceptance of AI.
  3. Utilise resources effectively: Ensure that sufficient financial and personnel resources are made available for AI projects. This also includes training for your employees.
  4. Optimise data management: Develop a comprehensive data strategy that regulates the collection, storage and use of data. Make sure that your data meets the highest quality standards.
  5. Expand your technological infrastructure: Invest in a scalable and flexible IT infrastructure. Regularly evaluate new technologies and adapt your systems accordingly.

Conclusion

Scaling AI is a complex but necessary step for companies in the financial sector that want to remain competitive and up-to-date in the long term. With a clear strategy, an open corporate culture, adequate resources, robust data management and a flexible infrastructure, companies can utilise the diverse potential of AI. In general, it makes sense to have professional support for the broad introduction of AI in your company. This is why the topics of digitalisation and artificial intelligence also play a major role in our training to become a Certified Organisational Developer in our Executive Education programme.

For detailed insights and practical examples, we recommend that you take a look at our complete study. It provides a comprehensive analysis and valuable guidance for executive managers who want to reach the next level of AI implementation.

By taking these steps, finance companies can not only increase their efficiency and competitiveness, but also ensure the future viability of their organisation. Scaling AI is not just a technological challenge, but requires a holistic approach that takes the strategy, the culture and the processes of the company into account. 

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