When Taiwan's financial industry discusses AI, most conversations remain confined to "implementing tools and enhancing efficiency," treating AI as mere assistance and hoping it will preserve existing workforce structures. However, a more fundamental reckoning is truly unfolding: identifying which financial specialties no longer create value for clients or markets and have only been temporarily protected by established processes and regulatory frameworks.
The emergence of AI agents makes this issue impossible to avoid. These systems don't just automate specific functions; they are autonomous units that can decompose tasks, execute them across systems, and provide real-time feedback and corrections independently. For the highly process-driven financial sector, this means the entire professional division of labor is being repriced.
The first wave of disruption hits research departments. Taiwan's financial institutions have long relied on substantial human resources to collect public information, organize financial statements, apply existing models, and produce standardized reports, whether for securities analysis, industry research, or macroeconomic reports. However, AI agents can now instantly process all financial statements, news, and data while simultaneously running dozens of scenarios. Human researchers often merely provide slower, narrower-coverage versions. Even more brutally, the market has already spoken: Most research reports contribute marginally to investment performance, yet they have long been regarded as "professional symbols."
Next is the wealth management advisor system.
In an era where information is no longer scarce, advisors' core value is still based on product explanations, performance comparisons, and standardized recommendations. AI agents can instantly generate allocation recommendations that are more consistent and traceable based on client risk profiles, asset structures, and market conditions. When recommendations can be automated, advisors who cannot establish long-term trust relationships and provide comprehensive asset planning will be reduced to mere sales channels, which calls their existence into question.
Risk management departments cannot remain detached, either. Taiwan's financial institutions have long equated risk management with model calculations, stress testing, and report writing. In doing so, they have overlooked the fact that genuine risks often stem from model assumptions themselves. AI agents can monitor anomalies in real time, reverse-track risk sources, simulate extreme scenarios, and continuously adjust parameters. As "risk identification" and "report writing" become automated, mid-level risk management personnel who merely maintain processes rather than participate in risk judgment will rapidly become marginalized.
Compliance departments are most unavoidably impacted. Regulatory reviews, rule comparisons, and document trails are highly structured processes, which are precisely AI agents' strengths. Once systems can instantly cross-reference regulations, flag risks, and maintain complete audit trails, financial institutions will inevitably reevaluate the need for human resources merely to demonstrate that processes were completed. Only those capable of handling gray areas and assuming responsibility for judgment calls will remain.
This does not signify a devaluation of financial expertise, but rather that the boundaries of value are rapidly widening. Those who are retained will not be the most knowledgeable about processes, but rather, those who are most willing to take responsibility for outcomes. AI can provide recommendations and generate reports but cannot assume investment losses, legal liability, or reputational risks. Decision-makers who can make trade-offs in uncertain environments while bearing the consequences will find their value amplified.
From research and wealth management to risk control and compliance, AI agents are forcing Taiwan's financial sector to confront a long-deferred issue: Which financial roles actually create value, rather than merely maintaining institutional operations? As intermediate value is clarified, professions unable to transform into judgment, responsibility, and trust will naturally receive the market's clearest answer.
*The author is an adjunct professor at Tunghai University EMBA
