Citi: AI threatens 54% of current banking jobs, but will create new ones

 

A recent report from Citigroup has highlighted the potential for AI to significantly impact the global banking industry, suggesting that AI could add as much as $170 billion to banking profits globally by 2028. This represents an increase of approximately 9% to the sector’s profit pool.

The report also notes that the banking sector is particularly susceptible to automation, with 54% of jobs having a high potential to be automated and an additional 12% that could be augmented by AI technologies. This is the highest rate of potential job displacement compared to other industries.

Despite the risks to jobs, the adoption of AI is expected to boost profits substantially. A survey by Citi Treasury & Trade Solutions revealed that 93% of respondents anticipate profit increases in the coming years due to AI implementation.

David Birch, the author mentioned in the report, sees considerable opportunities for AI-led transformation in the banking sector. Simple tasks, such as assisting customers with opening financial accounts, could be streamlined with AI. “Even a basic bot could help make better and faster decisions,” Birch stated.

Job Implications

The transition toward AI will likely impact employment in banking, particularly roles that involve manual and repetitive tasks. Roles in back offices, analyst positions, and banking jobs that involve tasks like transferring data between systems are most at risk.

However, new job opportunities are also expected to emerge, particularly in areas like AI compliance, ethics, and governance. The importance of “soft skills” is also expected to grow, with interpersonal skills and the ability to understand customer needs becoming more valued.

Challenges and Considerations

The banking sector’s reliance on data offers significant potential for increased efficiency through automation. However, as a heavily regulated global industry, the implementation of AI in finance faces several challenges. These include slow adoption rates due to risk factors, the cost of acquiring skilled talent, and increased competition.

Shameek Kundu, CDO at Truera and an AI entrepreneur, points out accuracy issues as one of the major obstacles to the use of generative AI in corporate settings. Additionally, the finance industry’s long-standing proficiency with statistical models may slow AI adoption, as the advantages of AI and machine learning over traditional methods are not always clear.

Despite these challenges, Citigroup remains optimistic about AI’s transformative potential in banking, suggesting that the way banks and financial firms operate could evolve rapidly, echoing the changes seen over previous decades. AI is expected to accelerate this evolutionary process, reshaping the industry much like past technological advancements.

Source: computing.co.uk

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