A Singapore Case Study
Executive Summary
As artificial intelligence transforms the global banking sector, questions about the future role of young workers have intensified. Drawing from Singapore’s experience as a leading financial hub, this case study examines how the banking industry is navigating AI adoption while maintaining young talent as a strategic priority. Despite AI’s capacity to automate routine tasks, major banks in Singapore are demonstrating that young workers remain central to their operations through unprecedented investments in upskilling, strategic workforce transformation, and the recognition that human judgment, relationship management, and adaptability cannot be replicated by technology.
- Background and Context
1.1 The AI Revolution in Banking
Singapore’s banking sector has emerged as a global leader in AI adoption. Major banks are making AI-powered decisions at unprecedented scales—OCBC Bank processes 6 million AI-powered decisions daily, with targets to reach 10 million by 2025. DBS Bank has deployed over 370 AI applications across business lines, generating revenue growth from S$750 million in 2024 to over S$1 billion projected for 2026.
The technology can now complete in ten minutes what previously took a private banker an entire day. Agentic AI models are transforming client journeys from onboarding and credit applications to compliance orchestration. This rapid advancement has raised fundamental questions about the future workforce composition in financial services.
1.2 Singapore as a Strategic Case Study
Singapore provides an ideal environment to examine this transformation. As Asia’s premier banking hub with robust regulatory frameworks, the city-state has invested heavily in both AI infrastructure and workforce development. The Monetary Authority of Singapore has allocated S$100 million through its FSTI 3.0 enhancement specifically for quantum and AI technologies, while maintaining strict governance through frameworks like Veritas, which promotes responsible AI use based on Fairness, Ethics, Accountability, and Transparency principles.
Recent research shows that 64% of Singapore’s financial institutions are actively deploying AI across key business functions, moving decisively from experimentation to operational reality. The sector demonstrates strong cybersecurity confidence, with 71% reporting they are ahead of peers on security and reliability. - The Challenge: Balancing Automation with Human Capital
2.1 Entry-Level Employment Pressures
Young graduates face a complex job market. While the employment rate for fresh resident graduates in Singapore reached 51.9% as of June 2025, this represents improvement from 47.9% in the previous cohort but still indicates significant challenges. College graduates aged 22-27 face a 5.6% unemployment rate, substantially higher than the 3.1% rate for all college graduates.
However, economists attribute these challenges primarily to workforce restructuring rather than AI displacement. Companies that hired aggressively in 2021 and 2022 are now reducing workforces, creating a cyclical phenomenon rather than a technology-driven structural shift.
2.2 The Skills Mismatch Crisis
A severe skills gap compounds the employment challenge. Research reveals that 82% of employers lack knowledge on how to run AI workforce training programs, while 78% of workers remain unsure about AI career opportunities. This disconnect threatens to create a generation unprepared for the evolving demands of financial services.
The transformation extends beyond technical skills. As AI handles data analysis and generates real-time investment ideas, the human value proposition shifts to judgment, empathy, and contextual advice. Relationship managers must become fluent in interpreting AI insights while building trust that algorithms cannot replicate. - Strategic Response: The Singapore Model
3.1 Government-Led Workforce Transformation
Singapore has adopted an anticipatory rather than reactive approach to workforce planning. Budget 2026 expanded AI-related support measures to help workers adapt to automation, emphasizing workforce readiness over infrastructure alone. The objective is ensuring productivity gains from AI translate into wage growth and employability rather than displacement.
Key government initiatives include:
Tripling the AI practitioner pool from 4,500 to 15,000 by 2029
S$20 million SG Digital Scholarship for AI-related education and overseas internships
TechSkills Accelerator program, which has trained 231,000 individuals and placed 17,000 in AI and tech roles since 2016
100 AI Centres of Excellence in partnership with companies
3.2 Banking Sector Upskilling at Scale
Singapore’s three major banks are retraining a combined 35,000 workers through comprehensive programs that emphasize skill development over mass layoffs. This represents one of the most ambitious workforce transformation initiatives in global banking.
DBS Group Holdings:
Identified 13,000 employees for AI and data training
More than 10,000 already trained as of November 2025
Freezing hiring for AI-vulnerable roles while redefining existing positions
Bank tellers transitioned to customer relationship and digital servicing roles, including video teller machine management
OCBC Bank:
Deployed OCBC GPT to all 30,000 employees globally in November 2023
Invested S$500 million in Punggol Digital District innovation hub
Training 30+ employees in quantum technology with plans to quadruple by 2026
The Deputy Chairman of the Monetary Authority of Singapore, Chee Hong Tat, emphasized that these efforts aim to help employees transition to adjacent roles through reskilling programs, maintaining employment while adapting to technological change.
3.3 Maintaining Graduate Recruitment Pipelines
Despite automation pressures, Singapore’s major banks continue robust graduate recruitment through structured multi-year programs that emphasize comprehensive development over immediate productivity.
OCBC Graduate Talent Programme:
24-month program open to graduates from all disciplines, including computing, engineering, arts, and sciences
Domain expertise foundation covering products, financial markets, regulations, service design, and ethics
Personalized rotations across core businesses including branch banking, compliance, and operations
Regional immersion experiences in Jakarta, Kuala Lumpur, and other markets
UBS, Standard Chartered, BNP Paribas, and Deutsche Bank:
All maintain active graduate programmes for 2026 cohorts
Programs span 12-24 months with structured rotations
Focus areas include global banking, wealth management, financial markets, and technology
These programs signal a fundamental belief that talent development remains a strategic investment even as automation accelerates. Banks are seeking highly motivated individuals with passion for problem-solving rather than specific academic backgrounds. - Solutions and Best Practices
4.1 Redefining Roles Rather Than Eliminating Them
Leading banks are transforming existing positions to emphasize higher-value activities. DBS CEO Tan Su Shan stated that automation will primarily remove routine work so employees can focus on customer engagement. This philosophy represents a strategic choice: using AI to augment rather than replace human workers.
The approach requires staff to embrace change as automation expands. Roles such as bank tellers are being redefined to focus on relationship building and complex customer needs that require empathy and judgment. Technology teams are designing digital infrastructure while operations teams ensure robust risk outcomes, elevating the importance of domain expertise and client-centricity.
4.2 Building AI Literacy Across the Organization
Rather than creating isolated AI specialist teams, banks are democratizing AI capabilities. OCBC’s deployment of generative AI tools to all 30,000 employees globally exemplifies this strategy. When every employee has access to AI assistance, the organization can identify innovative applications across diverse functions.
This approach also addresses the skills mismatch. By providing hands-on experience with AI tools during employment rather than expecting incoming graduates to possess complete AI expertise, banks bridge the gap between academic preparation and workplace requirements.
4.3 Creating Clear Career Pathways
Graduate programs are explicitly designed to provide pathway visibility. OCBC’s program helps participants find their interests and expertise through rotations before matching them to home departments that align individual strengths with organizational needs. This reduces the uncertainty that drives many graduates to reject job offers while holding out for better alignment.
The 24-month structured timeline provides sufficient exposure to make informed career decisions while developing a network of mentors, peers, and leaders who support long-term growth.
4.4 Emphasizing Domain Expertise and Soft Skills
As technical tasks become automated, banks are prioritizing capabilities that AI cannot replicate. The human value proposition now centers on judgment, empathy, contextual advice, and trust-building. Relationship managers must interpret AI insights and guide clients through complex decisions.
Training programs emphasize interpersonal effectiveness, business acumen, and leadership development alongside technical skills. This holistic approach recognizes that successful banking professionals need both analytical capabilities and relationship skills. - Outlook: The Future of Young Workers in Banking
5.1 Short-Term Outlook (2026-2027)
The immediate future presents a selective but skill-intensive hiring environment. Singapore’s total employment grew by 24,800 in Q3 2025 with unemployment holding steady at 2.0%. Employers are hiring competitively for high-impact skills, particularly in AI, data analysis, ESG compliance, and cybersecurity.
Banking and finance roles remain in demand, with financial analysts commanding median salaries of SGD 6,800-8,800 monthly and 4% hiring growth. The sector seeks professionals skilled in financial modeling, ESG risk assessment, and M&A integration—areas where human insight still guides strategy despite available automation.
Graduate employment rates will likely continue improving as companies complete workforce restructuring from the 2021-2022 hiring boom. However, competition remains intense, with more fresh graduates immediately entering the workforce rather than pursuing further studies or taking career breaks.
5.2 Medium-Term Outlook (2028-2030)
By the late 2020s, the banking workforce will likely stabilize at a new equilibrium. The number of workers may decrease modestly from current levels, but their focus and value contribution will have fundamentally transformed. As Goldman Sachs CEO David Solomon noted, talented and motivated people serving clients will remain core to professional services, though their numbers and time allocation may shift.
Singapore aims to triple its AI practitioner pool to 15,000 by 2029. This expansion suggests that demand for AI-literate financial professionals will continue growing, with young workers who possess both technical fluency and domain expertise commanding premium positions.
The boundaries between business, operations, and technology will continue blurring. Teams will increasingly question why tasks cannot be automated, elevating work to higher strategic levels. This creates opportunities for young professionals who can navigate these intersections.
5.3 Long-Term Outlook (Beyond 2030)
The long-term trajectory suggests that human workers will remain central to banking but in fundamentally different capacities than previous generations. Historical technological transitions provide instructive precedent: computers and mobile phones transformed work methods without eliminating the need for talented professionals.
The most successful young professionals will likely be those who view AI as a tool that amplifies their capabilities rather than a threat to their employment. Just as today’s bankers cannot imagine working without computers or smartphones, future generations will consider AI assistance fundamental to their roles.
Singapore’s emphasis on continuous learning and adaptability positions its workforce well for this evolution. The SkillsFuture 2026 initiative and employer-sponsored training create a culture of lifelong development that will prove essential as technology continues advancing. - Impact on Singapore
6.1 Economic Competitiveness
Singapore’s approach to maintaining young talent while adopting AI provides significant competitive advantages. The city-state’s ability to attract and develop skilled professionals strengthens its position as Asia’s premier financial center. As global financial institutions increasingly prioritize markets with both technological infrastructure and talent pipelines, Singapore’s dual focus becomes a strategic asset.
DBS Bank’s AI revenue growing from S$750 million to over S$1 billion demonstrates that productivity gains can translate into business growth rather than workforce reduction. This creates a virtuous cycle: technology drives revenue, which funds further investment in both AI and human capital.
The concentration of 650 AI startups in Singapore, with 230 having secured funding, creates an ecosystem where young professionals can move between established banks and innovative fintechs. This dynamic labor market provides alternatives to traditional banking careers while maintaining relevance to the financial sector.
6.2 Social Cohesion and Consumer Spending
By prioritizing employment over maximum automation efficiency, Singapore’s banking sector supports broader social objectives. Young professionals who secure stable employment contribute to consumer spending, which powers the economy. Unemployment and limited job prospects, conversely, create precautionary behavior that dampens economic growth.
The approach also maintains intergenerational fairness. Previous generations entered banking with clear career ladders and skill development opportunities. Maintaining robust graduate programs ensures current graduates receive comparable opportunities despite technological change.
6.3 Regional Leadership and Knowledge Transfer
Singapore’s model provides a template for other markets navigating similar transformations. The 35,000-worker upskilling initiative demonstrates that large-scale workforce transformation is achievable with government-industry collaboration. Regional immersion programs that expose graduates to markets like Jakarta, Kuala Lumpur, and across ASEAN strengthen Singapore’s role as a financial hub serving the broader region.
As banks develop AI governance frameworks and responsible deployment practices, Singapore-trained professionals carry this expertise to other markets. The Veritas Framework, emphasizing Fairness, Ethics, Accountability, and Transparency, establishes standards that young professionals internalize and propagate throughout their careers.
6.4 Innovation and Entrepreneurship
The combination of AI literacy and banking expertise creates conditions for entrepreneurship. Young professionals who understand both technology and financial services can identify opportunities to build innovative solutions. Singapore’s 32 unicorns as of July 2025 include several AI-powered companies founded by individuals with financial services backgrounds.
This entrepreneurial pipeline strengthens Singapore’s position in fintech and financial innovation. Rather than viewing AI as merely a tool for existing institutions, the ecosystem recognizes opportunities for new business models that leverage technology while maintaining human judgment in critical areas. - Key Takeaways and Recommendations
7.1 For Banks and Financial Institutions
Invest in comprehensive upskilling programs. DBS and OCBC’s commitment to training thousands of employees demonstrates that workforce transformation requires sustained investment rather than short-term cost optimization.
Maintain robust graduate recruitment. Multi-year structured programs provide talent pipelines while signaling organizational commitment to developing future leaders.
Redefine roles to emphasize higher-value activities. Rather than eliminating positions, transform them to focus on relationship management, complex problem-solving, and strategic thinking that AI cannot replicate.
Democratize AI access. Providing tools to all employees, not just specialists, accelerates organizational learning and identifies innovative applications.
Prioritize domain expertise alongside technical skills. The combination of industry knowledge and AI literacy creates competitive advantage.
7.2 For Government and Regulators
Adopt anticipatory workforce planning. Singapore’s Budget 2026 approach of addressing skills gaps before crisis demonstrates effective policy-making.
Create public-private partnerships for training. The TechSkills Accelerator and AI Centres of Excellence leverage both government resources and industry expertise.
Establish governance frameworks that promote responsible AI. The Veritas Framework ensures technology adoption aligns with ethical principles and societal values.
Monitor displacement risks while supporting transformation. Balancing innovation with employment stability requires ongoing assessment and policy adjustment.
7.3 For Young Professionals and Graduates
Develop AI literacy alongside domain expertise. Understanding how to work with AI tools provides competitive advantage regardless of specific role.
Prioritize adaptability and continuous learning. Technology will continue evolving; the ability to learn new tools and approaches matters more than specific current skills.
Cultivate soft skills that complement automation. Empathy, judgment, relationship-building, and strategic thinking become increasingly valuable as routine tasks automate.
Consider structured graduate programs. Multi-year programs provide comprehensive exposure and networking opportunities that accelerate career development.
View AI as a tool rather than a threat. Professionals who leverage AI to amplify their capabilities will outperform those who resist or ignore technological change.
7.4 For Educational Institutions
Integrate AI literacy across curricula. Rather than creating isolated AI courses, embed technological competency throughout business and finance programs.
Emphasize practical application. Internships, case studies, and project-based learning prepare students for workplace realities better than purely theoretical instruction.
Foster interdisciplinary thinking. The blurring of boundaries between business, operations, and technology requires graduates comfortable working across traditional silos.
Maintain connections with industry. Regular dialogue with employers ensures curricula remain relevant to evolving workforce needs. - Conclusion
Singapore’s banking sector demonstrates that young workers can remain core to financial services even as AI transforms operational models. The key lies not in resisting automation but in strategically integrating technology while investing in human capital development.
The 35,000-worker upskilling initiative, continued graduate recruitment, and emphasis on roles that leverage uniquely human capabilities represent a coherent strategy for navigating technological transition. This approach recognizes that while AI excels at data processing and pattern recognition, banking ultimately depends on trust, judgment, and relationships that require human professionals.
Goldman Sachs CEO David Solomon’s assertion that talented, motivated people serving clients will always be core to professional services finds validation in Singapore’s experience. The number of workers and their time allocation will evolve, but the fundamental need for human expertise persists.
For young professionals entering the field, the message is clear: AI is transforming banking, but this transformation creates opportunities rather than only threats. Those who develop AI literacy alongside domain expertise, cultivate soft skills that complement automation, and maintain adaptability throughout their careers will find themselves well-positioned for success.
The world evolves, as Solomon noted, but the need for talented people evolves with it rather than disappearing. Singapore’s banking sector is proving that with strategic foresight, public-private collaboration, and commitment to workforce development, young workers can remain not just employed but central to the industry’s continued success in the AI era.
Appendix: Key Statistics
Metric Value
Singapore banks retraining workers 35,000
DBS employees identified for AI training 13,000
OCBC AI-powered decisions daily (2024) 6 million
DBS AI revenue (2024) S$750 million
DBS AI revenue (2026 projected) Over S$1 billion
Fresh graduate employment rate (June 2025) 51.9%
Singapore unemployment rate (Q3 2025) 2.0%
Singapore AI startups 650
Singapore unicorns (July 2025) 32
MAS FSTI 3.0 AI investment S$100 million
Target AI practitioners by 2029 15,000
Singapore financial institutions deploying AI 64%