Singapore Finance Firms to Train More Than 80,000 Workers in AI by 2028

September 28, 2026 • FinTech News
Singapore Finance Firms to Train More Than 80,000 Workers in AI by 2028

Singapore’s financial sector is getting more than 80,000 employees ready for an AI-driven workplace. Twenty-three banks, insurers, and asset managers have committed to train their entire local workforce in key AI skills by 2028.

This commitment comes through the new IBF AI Workforce Co-Lab, launched by the Institute of Banking and Finance Singapore, known as IBF. The initiative goes beyond basic AI training. It also looks at how AI is changing individual jobs and tests new ways to handle workforce training and job redesign. More than half of the employees covered by this commitment have already finished relevant training through IBF-recognized programs.

Banks and insurers increasingly use AI for customer service, financial advice, credit underwriting, fraud detection, market analysis, and software development. Singapore’s financial authorities are treating workforce readiness as part of the industry’s AI strategy, not as a side project.

Finance firms make AI training a workforce priority.

Deputy Prime Minister and Minister for Trade and Industry Gan Kim Yong, who also chairs the Monetary Authority of Singapore, known as MAS, announced the initiative at the IBF Distinction Evening on September 24.

The 23 pioneer financial institutions span banking, insurance, and asset management. Together, they’ve committed to training their entire Singapore workforce, representing more than 80,000 employees, in critical AI skills by 2028 through IBF-recognized programs.

According to CNA, the group includes major names such as DBS, OCBC, UOB, AIA Singapore, and Prudential. These organizations represent around 40% of Singapore’s financial services workforce.

Employees will get a common foundation for working with AI under the program. However, the initiative also recognizes that one training track won’t fit every role. That’s why the Co-Lab will study how specific jobs are changing and build pathways for staff to gain skills that match new or expanded duties.

More than half the workforce has already completed training.

The scale of this commitment is notable, but another detail matters just as much: the program isn’t starting from zero. MAS says more than half of the employees covered by the 23-institution commitment have already received training. The remaining workforce will move through IBF-recognized programs as the initiative pushes toward its 2028 target.

IBF has also accredited close to 60 programs focused on critical AI skills for finance professionals. Some cover the responsible use of AI and are built around financial-sector use cases and MAS guidelines specifically.

That creates a broader skills framework around AI adoption. Staff need to know how to use AI tools well. At the same time, financial institutions need workers who can assess AI outputs, manage risks, apply professional judgment, and know where human oversight still matters.

AI is already changing financial services jobs.

AI adoption is spreading into several core areas of financial services. Gan said financial institutions already use AI in customer service, financial advisory, credit underwriting, fraud detection, market analysis, and software development. Larger institutions are weaving AI across multiple functions, while some fintech firms have built their businesses around AI from day one.

Two effects follow from that shift. AI can automate or speed up parts of existing workflows. Meanwhile, employees may take on new duties, such as supervising AI systems, checking their outputs, or using freed-up time to focus on higher-value work.

The IBF initiative is built around exactly that shift. Rather than assuming every AI-enabled role will simply vanish or stay the same, the Co-Lab will study how responsibilities are evolving and test practical ways to redesign jobs.

Three AI training pathways target different finance roles.

The first three pathways under the IBF AI Workforce Co-Lab focus on leaders, wealth managers, and operations staff.

AI training for financial leaders

The leadership pathway helps executives spot useful AI applications, set up proper governance, and manage workforce change. In effect, AI adoption becomes a management and organizational issue, not just a technology project. Leaders need to weigh which jobs are changing, where new opportunities may emerge, and what staff need before those changes actually take hold.

AI skills for wealth managers

The wealth-management pathway pairs AI capabilities with client-facing expertise. AI can help relationship managers process information faster, analyze portfolios, and prepare for client meetings. Still, professional judgment and responsibility for advice stay firmly with the human adviser.

MAS pointed to an example involving a UBS client adviser who uses AI tools to support meeting preparation, portfolio analysis, and due diligence, while staying responsible for the advice given to clients. Ten private banking employers have committed to upskill relationship managers through this pathway, working with IBF and training providers on practical programs.

AI training for operations staff

The operations pathway targets an area where AI can directly reshape routine processes. Its focus spans process improvement, exception handling, risk oversight, and checking AI-generated outputs.

Gan noted that many changes could mean greater responsibility within existing roles. Other staff could shift into related positions or brand-new roles involving AI. Financial operations demand more than an automated result alone, which is why this matters. Workers still need to catch errors, dig into exceptions, and grasp the consequences of decisions made along the way.

Job redesign becomes part of Singapore’s AI strategy.

The initiative also backs workers whose career paths may shift more substantially. IBF is launching a job redesign playbook for financial services with the Skills and Workforce Development Agency and the Institute for Human Resource Professionals.

That playbook gives business leaders and HR teams practical guidance on redesigning jobs as financial institutions adopt AI. IBF is also working with Ngee Ann Polytechnic’s Centre for Shaping Human-First Transformation on a pilot that blends skills mapping, coaching, and change-management tools.

The goal is to help finance staff and managers take on new duties as AI reshapes how work gets done. One example cited by MAS involves a UOB employee who moved from wholesale banking into a retail banking anti-money-laundering role after getting training and coaching through the bank’s Better U Pivot program. She now uses generative AI to automate checks and improve workflows in her new role.

Singapore also prepares young finance talent.

This workforce push reaches beyond current staff too. IBF has launched a pilot Young Talent Programme for AI in Finance, aimed at undergraduates who want to build skills in both AI and financial services.

The first cohort has finished its masterclasses and will move into project work backed by industry mentors. Some participants are also set to take on work attachments at financial institutions directly.

That program points to another piece of the puzzle: financial institutions need staff who grasp both the technology and the professional context where it gets used. For banks, insurers, and asset managers, that mix matters more as AI moves deeper into regulated financial processes.

AI training fits into a wider Singapore fintech strategy.

This 80,000-worker commitment is part of a broader push by Singapore to speed up tech adoption across financial services. In August, MAS announced S$220 million over three years under the renewed Financial Sector Technology and Innovation Scheme, known as FSTI 4.0.

That program backs AI adoption, financial-sector infrastructure, innovation projects, and talent development. MAS says Singapore’s fintech ecosystem had more than 1,800 fintech firms employing close to 10,000 professionals across technology, data, AI, compliance, and cybersecurity.

MAS has also launched an AI Pathfinder track to help financial institutions adopt market-ready AI fintech solutions, and it has backed work on responsible AI deployment in financial services. Together, these efforts build a wider framework where AI investment and workforce readiness grow side by side.

Human oversight remains a key part of AI adoption

This workforce program also sits next to Singapore’s broader push for responsible AI use. IBF has built AI training programs with the Association of Banks in Singapore, NUS Asian Institute of Digital Finance, and Singapore College of Insurance that cover responsible AI use in financial-sector applications. These programs suit different job functions and stay grounded in financial-sector use cases and MAS guidelines.

MAS has separately worked with financial institutions and fintech firms on safeguards for AI agents in finance. Its July 2026 SAFR initiative sets out a framework for letting AI agents handle financial tasks safely, securely, and reliably.

That matters as financial institutions shift from experimental AI tools toward systems that can shape or run more complex processes. The more responsibility AI systems take on, the more workers need to grasp how those systems work, where they can fail, and when human intervention becomes necessary.

What the 80,000-worker commitment means for finance

Singapore’s initiative offers a useful example of how financial institutions are handling AI workforce disruption. Teaching staff to use generative AI is only the starting point. Beyond that, the program pairs core skills with role-specific training, job redesign, and career-transition support.

For employees, that can mean learning how AI fits into existing roles or getting ready for adjacent duties. For employers, it means checking how technology reshapes workflows before deciding how jobs should evolve. For regulators and industry bodies, it builds a way to share lessons across financial institutions, rather than leaving each firm to work out its own workforce plan alone.

Scale also makes this program stand out. More than 80,000 employees across 23 institutions will fall under the 2028 commitment, and more than half have already finished training as of now.

Moving from AI adoption to AI readiness

Singapore’s financial sector now treats AI readiness as a workforce issue just as much as a tech one. The 23 pioneer institutions will keep training staff while the IBF AI Workforce Co-Lab studies how jobs are changing and tests new ways to redesign them. Organizers also plan to share the program’s findings with the wider financial sector over time.

The most significant part of this initiative may therefore reach past the 80,000 employees covered by the initial commitment. Should the Co-Lab produce practical models for redesigning finance jobs, training staff, and supporting career transitions, other institutions could adopt those same approaches as AI use grows further.

For Singapore’s financial sector, the next stage of AI adoption is becoming less about whether staff will encounter the technology and more about how their roles will change alongside it.

Singapore to train 80,000 FS sector employees in AI skills

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