Why the finance industry is looking to agentic AI
The Rise of Agentic AI in Finance
Why the finance industry is looking – In the evolving landscape of financial technology, a new wave of innovation is emerging. Agentic AI—software capable of performing tasks independently rather than merely responding to queries—has captured attention at major industry gatherings. At the Money 20/20 Europe event, held in Amsterdam, a landmark demonstration took place. Mastercard, ING, and Worldline showcased “Europe’s first live end-to-end agentic payment,” where an AI assistant handled a complex transaction for a shopper. The process involved the AI identifying concert tickets in a specified location and price range, executing the purchase after user selection, and securing final approval from a human. This example highlights how AI is transitioning from theoretical potential to practical application in finance.
From Buzzword to Reality
Scarlett Sieber, chief strategy and growth officer at the event, emphasized that AI in finance has moved beyond being a mere marketing term. “AI used to be a buzzword,” she stated, “but now real adoption is happening across the board.” This shift reflects broader industry collaboration, as fintech startups and traditional banks increasingly work together to integrate agentic AI. The technology’s ability to perform tasks autonomously is reshaping how financial services are delivered, from customer interactions to back-office operations.
According to a 2026 report by the University of Cambridge, which surveyed over 600 firms and regulators globally, the deployment of AI agents in finance is projected to grow from 24% to 81% by 2030. However, the report also warned that the pace of AI development often outstrips the regulatory frameworks designed to manage it. “The rapid technological change currently outpaces the supervisory frameworks and technical capacities required to oversee them,” the study noted. This challenge underscores the need for robust governance as agentic AI becomes more entrenched in the sector.
Transforming Consumer Engagement
Israeli fintech company eToro has been at the forefront of agentic AI integration. Its investment platform allows users to replicate the strategies of other traders, but recent upgrades have expanded its capabilities. CEO Yoni Assia explained that the AI assistant now acts on behalf of users within predefined limits, rather than just offering advice. One standout feature is the POTU$ app, which continuously monitors Donald Trump’s social media and related news. When the president makes a statement that could influence financial markets, the app initiates trades in users’ accounts within seconds.
Assia noted that AI adoption at eToro has grown dramatically. “AI use has increased roughly tenfold in six months,” he said, highlighting that 95% of the company’s new code is now AI-generated. This represents a significant shift from two years ago, when no AI code was used. Yet, he stressed that AI remains a tool, not a replacement. “AI is useless without humans steering it,” he added, emphasizing the importance of human oversight in critical decision-making processes.
Efficiency and Workforce Changes
Swedish fintech firm Klarna, known for its “buy now, pay later” payment options, has also embraced agentic AI. Last month, the company launched a shopping search app within ChatGPT, demonstrating its commitment to AI-driven solutions. In 2024, Klarna introduced an AI assistant powered by OpenAI, which handles customer service tasks equivalent to 700 full-time human agents. CEO Sebastian Siemiatkowski told CNN that this advancement has enabled the firm to reduce its workforce from 6,000 to fewer than 3,000 while maintaining rising revenue per employee.
Despite these efficiency gains, Siemiatkowski acknowledged the trade-offs. “Cost cutting has led to lower quality,” he admitted, as reported by Bloomberg last year. Klarna has since begun rehiring human agents to improve service standards. He further warned that AI could lead to job losses across industries, particularly in customer-facing roles. “Sales and legal professions may fare very well,” he said, “but there could be short-term negative implications in specific job areas.” The exact percentage of roles replaced by AI, however, remains undisclosed.
Traditional Banks Embrace Digital Shifts
Even established institutions like ABN AMRO are adapting to the AI revolution. The third-largest Dutch bank, which reduced its physical branches from 500 in 2010 to just 26 today, has integrated AI into its operations. CEO Marguerite Bérard told CNN that 85% of her colleagues now use AI daily, with bots like “Ana” and “Lenny” facilitating millions of customer interactions and streamlining credit applications. This transformation exemplifies how traditional banks are modernizing their services to stay competitive in a rapidly evolving market.
Meanwhile, the broader adoption of agentic AI has sparked concerns among analysts. Gartner predicted that over 40% of AI projects in 2027 would be abandoned, citing reasons such as rising costs, unclear business value, and insufficient risk controls. A recent collaboration between Accenture and Wharton Business School echoed these warnings, stressing that leaders must balance automation with human judgment. “Governance, accountability, and trust must be embedded into the system,” the report stated, as automation continues to redefine workflows across industries.
Autonomy and Human Oversight
As agentic AI becomes more autonomous, its role in financial decision-making is expanding. From managing investment portfolios to executing trades based on real-time data, AI systems are increasingly taking on tasks once reserved for human professionals. Yet, the emphasis on human oversight remains critical. Bérard emphasized that AI’s effectiveness depends on the quality of the processes it supports. “If you apply AI to a flawed system, the result will still be flawed,” she said, underscoring the need for careful implementation.
For instance, eToro’s POTU$ app demonstrates how AI can act as a proactive tool. By analyzing social media trends and news, it identifies potential market-moving events and triggers trades automatically. This level of responsiveness is a testament to the technology’s ability to process vast amounts of data in real time. However, Assia reminded audiences that such systems require human input to guide their actions. “AI is a multiplier, not a substitute,” he argued, highlighting its potential to enhance, rather than replace, human expertise.
Industry-Wide Implications
The integration of agentic AI is not limited to finance. Its applications are spreading across sectors, from retail to healthcare. This trend raises questions about the future of employment and the role of human workers. While AI-driven automation can reduce operational costs and improve efficiency, it also poses challenges. Siemiatkowski admitted that AI’s initial adoption led to “lower quality” in some areas, prompting a reassessment of its role in customer support.
Yet, the benefits of agentic AI are undeniable. It enables faster decision-making, reduces manual errors, and provides 24/7 service. For example, Klarna’s AI assistant handles customer inquiries instantly, freeing up human agents for more complex tasks. This shift aligns with the broader goal of optimizing workforce capabilities while maintaining service quality. As the technology matures, the balance between automation and human intervention will likely become more refined, ensuring that AI complements rather than undermines core financial functions.
Experts suggest that the key to successful AI adoption lies in strategic implementation. The Cambridge report noted that while adoption is rising, challenges such as regulatory lag and technical limitations persist. These hurdles require collaboration between developers, regulators, and industry leaders to create frameworks that support innovation without compromising safety. As the finance industry continues to evolve, agentic AI may become a cornerstone of digital transformation, redefining how services are delivered and consumed.
Ultimately, the integration of agentic AI represents a paradigm shift. It moves beyond mere automation to enable intelligent, self-sufficient systems that can operate independently. However, the human element remains indispensable. Whether guiding AI in investment decisions or ensuring ethical oversight in financial transactions, humans are still the ultimate arbiters of trust and accuracy. As the technology advances, its ability to enhance productivity while maintaining human-centric values will determine its long-term success in the financial sector.