What changes when AI becomes central to decision-making rather than serving as a support tool? This was the central question at a recent Globant roundtable, where leading financial executives from Chile discussed how agentic AI is shaping their industry’s future.
Leaders from banks, insurers, fintechs, and financial infrastructure firms agreed that the industry is moving beyond experimentation. Agentic AI is no longer limited to future concepts or innovation labs; it is now integrated into daily operations and transforming organizations from within.
Most participants agreed the change goes beyond automation. The true transformation is structural, redefining workflows, operating models, and collaboration between people and intelligent systems. The following are four key insights from the discussion.
1. The New Competitive Advantage Is Scaling Expertise
A major industry shift is the ability to scale expertise, not just automate tasks.
In the past, financial services grew by hiring more people, expanding operations, or reaching new regions. Now, agentic AI is creating a new model where institutional knowledge can be scaled.
Organizations are starting to turn underwriting logic, compliance rules, customer decisions, and best practices into systems run by intelligent agents. In this setup, expertise is not limited to certain teams or people. Instead, it is captured, shared, and improved across the whole company.
As the industry moves deeper into the AI era, standing out will depend less on having the latest technology and more on how well organizations use their internal knowledge at scale. This is leading to a new way of working, where people and autonomous systems act as connected networks instead of separate departments.
“The equation every company should be optimizing is how to deliver the best possible customer experience at the lowest possible cost. To achieve that, AI agents that enhance the experience and deliver tailored products to each customer in real time become critical. At Global66, we are already moving in that direction.”- Tomas Bercovich, Co-Founder & CEO Global66
2. The First Wave of ROI Is Operational
Most organizations using agentic AI report the greatest benefits in efficiency, speed, consistent service, and resilience, rather than immediate revenue growth.
Participants shared examples of how AI is making onboarding, customer support, fraud checks, compliance reviews, and internal operations smoother. Often, the value comes from doing things faster while also improving accuracy, thus improving the customer experience. Operational gains are significant. In a competitive, margin-sensitive industry, improving efficiency at scale can fundamentally reshape profitability and responsiveness.
Many agreed that while the most immediate gains are operational, larger revenue opportunities will emerge as organizations develop AI-driven products, deliver highly personalized financial services, provide autonomous advisory capabilities, and unlock new engagement models. For now, the industry remains in a transitional phase, building the operational and technological foundations required to support the next generation of AI-native financial business models.
“In our experience, we have seen very significant improvements in service quality and process efficiency thanks to AI, but that does not always translate into increased sales or revenue. Value capture is often more limited than initially expected, and the clearest impact tends to be in operational efficiency and customer experience.”- André Gailey, CEO Itau Chile
3. Humans Are Becoming Orchestrators
A main topic was how people’s roles are changing in organizations that use AI. As intelligent agents take over repetitive and analytical tasks, people are moving into roles that need judgment, creativity, ethics, and strategy. Participants said that in the future, employees will guide intelligent systems rather than simply carry out tasks.
This evolution has significant implications for talent, leadership, and organizational culture. Financial institutions increasingly recognize that AI adoption is both a technology and a workforce transformation, involving AI systems that validate outputs, design workflows, manage exceptions, and make complex judgment calls in ambiguous situations. At the leadership level, the challenge becomes balancing innovation speed with governance, trust, and accountability.
During the roundtable, it was highlighted that organizations best positioned for this transition will invest equally in cultural adaptation, skill development, and technology. Ultimately, the question is not whether humans or AI will drive the future of work, but how organizations design effective collaboration between the two.
4. AI Is Moving from Copilot to Core Infrastructure
One of the clearest takeaways from the roundtable was that financial institutions are moving beyond the “copilot phase” of AI adoption. Simply layering AI assistants onto existing workflows has not delivered the transformational impact many organizations initially expected.
Leading players are now redesigning operations around autonomous or semi-autonomous agents capable of executing entire workflows, with humans intervening only when supervision, governance, or strategic judgment is required. This shift fundamentally changes the economics of operations: instead of focusing solely on making employees more productive, organizations are beginning to rethink how work itself is distributed between humans and intelligent systems.
As AI agents become embedded into core processes, new organizational questions emerge around accountability, risk management, and decision ownership. The consensus was clear: the organizations creating meaningful value will not be the ones that simply adopt AI tools, but those that rebuild their operating models around AI-native execution.
“This shift is not about layering artificial intelligence onto existing processes, but about completely redesigning how organizations operate. Processes are beginning to be executed by AI agents, while humans move into roles focused on supervision, quality control, and strategic direction. It is a profound transformation of the operating model, not an incremental one.” – Tomas Zavala, CEO Caja Los Andes
Why This Moment Is Crucial
Accelerated digital adoption, rising customer expectations, regulatory complexity, and rapid fintech expansion are converging. In this context, agentic AI introduces a fundamental change: systems that not only generate insights but also plan, decide, and act autonomously within defined parameters.
This shift is already showing up in real-world uses:
- Automated compliance and AML processes
- Real-time fraud detection
- Intelligent credit and payment optimization
- Frictionless omnichannel experiences
- Proactive wealth management services
The conversation is no longer about whether AI will change financial services, but about how fast organizations can adapt to compete in an AI-driven world.
AI systems are already running workflows, learning patterns, and helping with complex financial decisions in real time. But the organizations seeing real value are not just adding AI; they are rebuilding their operations around intelligent systems. Its biggest impact might be turning company knowledge into a resource that is always available, can grow with the business, and can be used at any scale.
