Artificial intelligence is rapidly transforming the finance profession, promising greater efficiency, faster insights, and smarter decision-making. Yet alongside that optimism lies a growing sense of uncertainty, particularly among professionals wondering how AI will reshape career paths, workplace expectations, and the skills needed to succeed.
For Chiew Chun Wee, Regional Lead, Policy & Insights, Asia Pacific at ACCA, the conversation shouldn’t centre on whether AI will replace finance professionals. Instead, it should focus on how the profession evolves alongside technology, ensuring organisations continue investing in people while equipping them with the judgement, ethics, and adaptability that AI cannot replicate.
Drawing on ACCA’s latest Global Talent Trends research, Chiew explains why confidence and concern can coexist, the capabilities that will define tomorrow’s finance leaders, how organisations can build trust during AI transformation, and why purpose, sustainability and multi-generational talent will shape the future of work just as much as technology itself.
Highlights
- Confidence in AI Doesn’t Eliminate Career Uncertainty
- The Finance Leaders Who Stand Out Will Be the Ones Who Apply Human Judgment
- AI Adoption Must Be Matched by Investment in People
- Purpose, Sustainability, and Generational Diversity Are Reshaping Talent Strategy
- Final Thoughts: Preparing People Is Just as Important as Adopting Technology
Confidence in AI Doesn’t Eliminate Career Uncertainty
Q: Many finance professionals are simultaneously optimistic about learning AI and concerned about its impact on their careers. Why does this tension exist, and what does it reveal about the future of the profession?
A: One of the most revealing findings from our research is that these two sentiments coexist. Rather than seeing this as a contradiction, business leaders should see it as an important signal.
In Singapore, 81% of finance professionals say they are confident in their ability to learn and apply AI. At the same time, 62% are concerned about what AI could mean for their own roles. We see a similar pattern across many markets worldwide.
The reason is simple: they’re answering two different questions.
The first is, “Can I learn to use AI?” That is a question of capability. Finance professionals are analytical, methodical, and accustomed to working with new systems, so it’s no surprise they feel confident in developing these skills.
The second is, “What will AI mean for my career?” That is a much harder question because no one can say with certainty how quickly or how extensively AI will reshape the finance profession.
What this tells us is that finance professionals are approaching AI with both optimism and realism. They recognise the opportunities AI presents and are eager to embrace new technologies, while also asking sensible questions about how the profession itself will evolve.
Interestingly, this concern is strongest among younger and aspiring professionals. That’s understandable because today’s AI tools are particularly effective at automating many of the routine, entry-level tasks that have traditionally served as the foundation of a finance career.
The bigger challenge, therefore, isn’t immediate job displacement. It’s how we develop judgment, commercial thinking, and professional confidence if those early-career learning opportunities become less available. The profession’s ability to build a strong talent pipeline depends on addressing that challenge honestly.
Another finding deserves attention. Around half of Singapore respondents worry that their employers are investing more in AI than in people. Whether perception or reality, it reflects how employees are interpreting organisational priorities.
Our message to business leaders is straightforward: the pace of AI adoption and the pace of investment in people cannot diverge. Reskilling, career transition planning, and transparent communication are not optional — they are essential components of any successful AI strategy.
The Finance Leaders Who Stand Out Will Be the Ones Who Apply Human Judgment
Q: As AI automates more routine tasks, what capabilities will distinguish the most valuable finance professionals over the next decade?
A: One of the biggest misconceptions is that AI will simply take over routine work, leaving people to focus on the “interesting” tasks. While that sounds reassuring, it overlooks an important reality: AI won’t just absorb routine tasks — it will raise the bar on everything else.
In the past, the challenge was accessing information. Increasingly, the challenge will be knowing which information to trust, how to interpret it, and when to question it.
That’s where professional judgement, ethics, and critical thinking become even more valuable. Someone still needs to challenge assumptions, understand business context, weigh competing priorities, and ultimately take responsibility for decisions.
The finance professionals who thrive won’t simply interpret data. They’ll bridge the gap between what AI recommends and what the business can realistically execute.
Take cash flow management as an example. AI may identify a potential shortfall and recommend delaying payments to suppliers or reducing investment in research and development. Technically, those recommendations may make sense. But AI cannot assess the long-term reputational impact, supplier relationships or broader strategic consequences of those decisions.
That’s where finance leaders create value. They apply commercial judgement, understand organisational priorities, and balance financial outcomes with operational realities.
To do that effectively, professionals need technology fluency — not necessarily the ability to build AI systems, but the ability to work alongside them intelligently. That means knowing how to use AI effectively, challenge its outputs, and recognise its limitations.
Alongside these technical capabilities, the enduring human skills remain just as important: curiosity, communication, adaptability, and the ability to build trust and strong relationships.
At ACCA, we often talk about becoming a specialist in a generalist world — maintaining deep technical expertise while developing the breadth needed to navigate increasingly complex business environments.
That breadth also includes sustainability.
While some perceive sustainability to be losing momentum, the long-term forces driving it — climate change, resource constraints, biodiversity loss, and growing stakeholder expectations — remain firmly in place. Regulatory requirements and market expectations will continue to evolve, creating strong demand for finance professionals who can connect financial performance with long-term sustainability strategy.
Those who can bridge finance, technology, and sustainability will be among the profession’s most valuable leaders over the coming decade.
AI Adoption Must Be Matched by Investment in People
Q: Many organisations are investing heavily in AI, yet employees remain uncertain about what it means for their careers. What can business leaders do to build confidence, adaptability, and trust during this transition?
A: The first thing business leaders should avoid is offering reassurance without substance. It’s obvious that automation will reduce certain tasks over time. Rather than making promises that may not be sustainable, leaders should be transparent that roles will evolve—and commit to ensuring employees are better equipped for those future roles than they are today. That commitment needs to be backed by action, not just communication.
One practical starting point is to move beyond traditional, top-down training. Instead, give employees the budget, tools, and permission to automate their own pain points. When employees are empowered to experiment, AI becomes something they shape rather than something imposed on them. That shift can significantly improve both confidence and engagement.
Leaders should also help employees visualise how their work will change. Publishing simple “Before and After” role blueprints for different functions—for example, showing how an analyst’s time shifts from data compilation to business analysis and decision support—provides far greater clarity than simply saying AI will augment existing roles. Employees want to know what their jobs will actually look like next year.
Accountability matters too. Organisations should consider linking part of leadership performance to employee retention and internal mobility during AI transformation, rather than measuring success solely through productivity gains. When leaders are visibly accountable for people’s outcomes as well as business outcomes, employees gain confidence that their future genuinely matters.
Finally, organisations should recognise that employee anxiety is not simply an HR issue—it’s an operational one. People who feel uncertain are more likely to resist change, adopt new technologies slowly, and make avoidable mistakes. One practical way to build confidence is by normalising “failure reviews”, where teams openly discuss AI implementation challenges without assigning blame. These conversations transform apprehension into learning and help create the kind of culture where both innovation and trust can thrive.
Ultimately, organisations that navigate AI successfully won’t be the ones that spend the most on technology or communication campaigns. They’ll be the ones who invest just as deliberately in developing their people.
Purpose, Sustainability, and Generational Diversity Are Reshaping Talent Strategy
Q: ACCA’s research highlights growing expectations around purpose, culture, and multi-generational workforce dynamics. How are these reshaping talent strategies across the Asia Pacific?
A: One of the most interesting tensions in our research is that professionals increasingly want purpose-driven careers, particularly around sustainability, while many remain unconvinced that their organisations genuinely share those priorities.
In Singapore, nearly half of the respondents believe ESG is treated more as a branding exercise than as a strategic business imperative. Employees can tell the difference between authentic commitment and marketing, and organisations risk losing talented people if those two don’t align.
The demand is already there. Sixty-three percent of finance professionals in Singapore say they want roles focused on environmental and climate issues, yet only 33% currently work in those areas. That’s a significant pool of untapped talent that organisations have an opportunity to develop.
At the same time, workplaces are becoming increasingly multi-generational. Careers are extending from roughly 35–40 years to as much as 50 years, meaning organisations may soon have as many as five generations working together. Differences in expectations around flexibility, career progression, and workplace values are inevitable, but they also present opportunities if managed intentionally.
One particularly striking finding from our research is that recognising the value of older employees ranked as the top diversity issue globally—and this wasn’t driven only by older workers. Gen Y respondents identified it as their leading concern as well. In Singapore, this sentiment was stronger than in any other market we surveyed.
Rather than relying on one-off initiatives, organisations should build these priorities into the way they develop talent. One effective approach is structured two-way mentoring, where experienced professionals share judgment, leadership, and industry knowledge while younger employees contribute technology fluency, digital skills, and fresh market perspectives. When organisations actively value learning in both directions, they reinforce that experience and innovation are equally important.
The organisations that succeed won’t treat sustainability, purpose, and generational diversity as separate HR initiatives. They’ll integrate them into business strategy, creating workplaces that reflect both what they promise externally and what employees experience every day.
Final Thoughts: Preparing People Is Just as Important as Adopting Technology
AI may be transforming how finance teams analyse data and make decisions, but Chiew believes the profession’s future will ultimately depend on how organisations invest in people as much as technology.
As automation takes on more routine work, the demand for judgment, ethical leadership, commercial awareness, and the ability to navigate complexity will only increase. Finance professionals who combine technical expertise with curiosity, adaptability, and sustainability thinking will be best positioned to create long-term value.
For business leaders, the message is equally clear: successful AI adoption isn’t simply about deploying new tools. It’s about building trust, supporting continuous learning, and ensuring that technology enhances — rather than replaces — the human capabilities that have always been at the heart of sound financial decision-making.
Highlights
- Confidence in AI Doesn’t Eliminate Career Uncertainty
- The Finance Leaders Who Stand Out Will Be the Ones Who Apply Human Judgment
- AI Adoption Must Be Matched by Investment in People
- Purpose, Sustainability, and Generational Diversity Are Reshaping Talent Strategy
- Final Thoughts: Preparing People Is Just as Important as Adopting Technology
Read the Chinese article here.
