Manpower Management in the Age of Artificial Intelligence


23 May 2024

Manpower Management in the Age of Artificial Intelligence

  1. Since the advent of ChatGPT, a burning question among bankers is how to apply generative artificial intelligence (AI) technology to banking services and operations. AI has revolutionary effects across different industries globally.  The banking industry is no exception.
  2. The pace of digitalisation in the banking industry has accelerated over the last decade. In particular, with the emergence of AI technology, banks are able to provide more customised services for customers.  They can also process and analyse massive amounts of data more effectively, which is useful in detecting suspicious transactions and fraud.  These capabilities have substantially boosted operational efficiency and enhanced customer experience.

Implications of AI for manpower

  1. We welcome the industry’s efforts in driving financial innovation with the aim of improving work efficiency and service quality. Amid the unstoppable rise of AI, there is a growing demand for relevant professional talent in the industry.  At the same time, there are also some questions: Would human jobs be displaced by AI?  What types of jobs would be affected?  When would this happen? 
  2. Looking back at history, the adoption of technology in streamlining daily banking operations is nothing new, as seen with the introduction of ATMs in the early 1980s in Hong Kong. This innovation led to a gradual shift of job roles from routine cash handling tasks to more sophisticated client relationship management roles, contributing to an improvement in banking service quality.   
  3. Likewise, the emergence of AI is reshaping the nature of certain traditional job roles while giving rise to fresh new job posts, such as AI engineers and data engineers. As far as generative AI is concerned, its impact may not be limited to replacing repetitive jobs alone, and there may be broader implications for manpower management in the industry and even the labour market as a whole. 

Planning ahead for manpower development and training strategies

  1. To adapt to the forthcoming changes, the banking industry must proactively plan ahead for manpower development. The key is enhancing the professional knowledge and skill-sets of employees, enabling them to complement and co-exist with technology in the AI era.  By effectively utilising innovative technology, banks can also enhance customer experience.  This will create a “triple-win” outcome for bank staff, customers and the banks themselves.
  2. As a banking supervisor, the HKMA also makes sure the policy guidelines are kept up-to-date with the latest developments. Following industry consultations, the HKMA has released today an updated module of the Supervisory Policy Manual on capacity building.  The key updates are related to manpower planning and training.  In gist, banks should set a clear future direction for manpower development to support business priorities, and draw up effective strategies to address talent needs, including allocating sufficient financial resources for staff training as needed.
  3. In addition, banks should assess the impact of technological advancement and changing customer needs on the requirements of different job roles, which would help inform a reskilling plan for supporting staff to acquire new knowledge and skills over the medium to long term. In fact, some banks have already taken steps in this direction, with approximately 2% of their staff successfully transitioning to new roles in 2022 after undergoing appropriate training programmes.  These successful cases include frontline staff at bank branches retrained and redeployed to other functional areas such as wealth management, risk management, compliance, and so on. 
  4. Forward-looking analysis is crucial for long-term manpower planning. In support of the industry’s work in this regard, the HKMA will embark on in-depth research studies in collaboration with the industry in the coming months, with focus on two important areas.  First is examining the extent of AI’s impact on various job roles within the banking industry.  This would provide useful reference for the industry, thereby facilitating a better assessment of future manpower deployment, and formulation of corresponding strategies to support affected employees in their transition journey. 
  5. Secondly, we will assess the future talent and skill requirements of the banking industry in the context of global financial and technological trends. Back in 2020, the HKMA jointly issued an inaugural study on “Capacity Building for Future Banking 2021-2025” with the Hong Kong Association of Banks and the Hong Kong Institute of Bankers.  The study identified fintech, green and sustainable finance, and business related to the Guangdong-Hong Kong-Macao Greater Bay Area as three major areas with notable skill gaps that need to be bridged in order to address the needs of the banking industry.  These results have provided a pivotal roadmap for capacity building in the industry.  We plan to conduct the study again for publication next year.  This second report aims to identify the skill gaps in the next five-year horizon, i.e. from 2026 to 2030, so that the industry can develop and adjust talent development strategies and measures in good time to support future business growth.

Embracing changes through collective efforts

  1. Talent is the pre-requisite for sustainable development of the banking industry. AI certainly brings opportunities to the sector, but it also comes with challenges.  The full impact of the application of generative AI on jobs traditionally performed by humans remains to be seen.  That said, I believe, with our collective efforts in embracing technological advancement and market changes, and empowering practitioners with the necessary future skills and knowledge, the banking sector will be well-positioned to maximise the benefits of technology while minimising its impact on the labour market.       


Arthur Yuen
Deputy Chief Executive
Hong Kong Monetary Authority

23 May 2024

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Last revision date : 23 May 2024