Why the finance industry is looking to agentic AI

Revolutionizing Finance: The Rise of Agentic AI

Why the finance industry is looking – The financial sector is witnessing a transformative shift as institutions increasingly adopt agentic AI, a technology that transcends traditional automation by enabling AI systems to perform complex tasks independently. At the forefront of this evolution is the collaboration between Mastercard, Dutch bank ING, and payment services provider Worldline, which recently unveiled “Europe’s first live end-to-end agentic payment” during the Money 20/20 Europe event in Amsterdam. This innovation demonstrates how AI can now not only process transactions but also engage in decision-making processes with human oversight.

Agentic AI, as the term suggests, operates as a self-directed agent capable of initiating actions without explicit step-by-step instructions. In this latest test, an AI assistant was tasked with identifying concert tickets in a specific location on a designated date, within a set budget. Once the shopper made a selection, the system executed the payment with approval from a human user. This seamless integration of AI into real-world financial workflows has sparked widespread interest among industry leaders.

From Buzzword to Reality

Scarlett Sieber, chief strategy and growth officer at the Money 20/20 Europe event, highlighted the growing acceptance of AI in finance. “What was once a buzzword is now becoming a standard feature,” she explained, emphasizing that major firms are actively implementing these technologies. The conference, described as the largest annual gathering of fintech professionals, showcased agentic AI as a critical driver of innovation.

A 2026 study by the University of Cambridge projected that the deployment of AI agents in the financial industry would surge from 24% to 81% by 2030. The research, which surveyed over 600 organizations globally, noted that this rapid advancement has outpaced existing regulatory frameworks. “The speed of technological change is overwhelming,” the report warned, stressing the need for robust oversight to manage risks effectively.

Real-World Applications and Human Control

Israeli-based eToro, renowned for its investment platform, exemplifies how agentic AI is being applied in practical scenarios. The company recently enhanced its AI assistant, shifting from offering portfolio advice to executing trades on behalf of users under predefined conditions. One standout feature is the POTU$ app, which continuously monitors Donald Trump’s social media and news coverage. When a market-moving statement is detected, the AI can swiftly place a trade in a user’s account, showcasing its ability to act in real-time.

According to Yoni Assia, CEO of eToro, the company has seen a dramatic increase in AI usage. “In just six months, our reliance on AI has grown roughly tenfold,” he stated, noting that 95% of new code now stems from AI development. However, Assia also emphasized that AI cannot function without human direction. “No matter how advanced the technology becomes, we must ensure it aligns with our strategic goals,” he said, highlighting the importance of human oversight in maintaining control.

Automation and Workforce Transformation

Swedish fintech giant Klarna has also embraced agentic AI, leveraging it to streamline operations and reduce costs. Last year, the company introduced a ChatGPT-powered shopping search app, demonstrating how AI can enhance customer experiences. In 2024, Klarna launched an AI assistant with OpenAI, claiming it equates to the work of 700 full-time employees. This has led to a significant reduction in the workforce, with the company’s employee count dropping from 6,000 to fewer than 3,000 in recent years.

Despite these efficiencies, Klarna’s CEO Sebastian Siemiatkowski acknowledged the challenges of AI adoption. “While automation allows us to do more with less, it also raises questions about quality,” he told CNN. He admitted that cost-cutting measures had initially led to a decline in service standards, prompting the company to rehire human agents. “We are investing in the quality of human support,” he added, recognizing the balance between AI-driven efficiency and the irreplaceable value of human judgment.

The impact of agentic AI extends beyond customer-facing roles. Traditional institutions, such as ABN AMRO, are also integrating these systems into their operations. The bank, which reduced its physical branches from 500 in 2010 to 26 today, reported that 85% of its staff now use AI tools daily. Its AI bot “Ana” facilitates millions of customer interactions, while “Lenny” automates credit request processes, illustrating how even legacy banks are embracing AI to stay competitive.

Broader Industry Implications

As agentic AI permeates various sectors, its potential to reshape industries becomes evident. However, not everyone is optimistic. Gartner, a leading research firm, predicted that over 40% of agentic AI projects would be abandoned by 2027, citing concerns about rising costs, uncertain returns, and insufficient risk management protocols. Similarly, a joint report from Accenture and Wharton business school emphasized the need for leaders to define the boundaries of AI autonomy, ensuring human input remains central where it matters most.

For Bérard, the emphasis on human oversight is paramount. “If you deploy AI on a flawed process, the results can be equally flawed,” she noted, underscoring the importance of refining workflows before automation. This perspective aligns with the broader debate on how to harmonize AI capabilities with human expertise. While AI can handle repetitive and data-intensive tasks, it still requires human intervention to interpret context, make ethical decisions, and adapt to unforeseen circumstances.

Looking Ahead: Challenges and Opportunities

As the technology continues to evolve, the finance industry faces both opportunities and challenges. While agentic AI promises to enhance efficiency and innovation, its widespread adoption raises questions about job displacement and the future of human roles. Siemiatkowski admitted that customer-facing jobs—such as sales and legal services—could be most affected, though he noted that the impact would be gradual and industry-specific.

Still, the potential for AI to drive growth and improve service quality cannot be ignored. The partnership between Mastercard, ING, and Worldline highlights how even large-scale financial operations can benefit from AI’s ability to streamline processes and reduce manual effort. With continued investment and refinement, agentic AI may become a cornerstone of the financial sector, reshaping how services are delivered and how decisions are made.

In the coming years, the balance between AI and human oversight will likely define the success of these initiatives. As institutions like eToro and Klarna demonstrate, the integration of agentic AI can lead to significant operational improvements. However, the industry must also address concerns about oversight, quality, and the human element in decision-making. For now, the trend suggests that agentic AI is not just a futuristic concept but a rapidly evolving reality in finance and beyond.