MOVE YOUR BUT
FINANCE EDITION
AI Game Plan: Future-Proofing Finance
The financial sector is experiencing a significant and eagerly expected change.
“Artificial Intelligence is catalyzing a metamorphosis in the financial industry, enabling institutions to scale up personalized service. For example, GenAI is set to become an integral part of bank operations, helping them pursue a delicate balance between enhanced customer convenience and robust risk and compliance processes.”
Artificial intelligence (AI) is revolutionizing the finance industry by optimizing operations, enhancing customer experiences, and unlocking new revenue streams. However, several significant challenges—or "buts"—hinder its full adoption. Roadblocks like legacy systems, regulatory concerns, or a lack of skilled talent are holding back innovation. Yet, when you look at the financial industry, the transformative power of AI is becoming impossible to ignore.
This report explores in detail the top five "buts" blocking AI in the finance industry and presents strategic solutions to overcome them.
The global AI in banking market was valued at $20 billion in 2023, estimated at $26 billion in 2024, and is projected to grow to approximately $315 billion by 2033.
85% of banks believe AI will significantly impact customer experience by offering personalized services and automating processes.
Spending on generative AI in the banking sector is expected to soar to $85 billion by 2030, driven by an impressive compound annual growth rate of 56%.
And that’s only scratching the surface. While AI is rapidly transforming the finance industry, revolutionizing how banks operate, enhancing customer experiences, and improving risk assessment, it still faces several hurdles. So, brace yourself as we dive into the complexities and challenges of AI in finance.
5 Barriers to AI Adoption & How Globant Helps Break Them Down
1 THE BUT
A Steep AI Learning Curve Can Stall Innovation…
AI adoption requires a daunting shift in organizational mindset. Employees across all levels must be equipped to go through continuous learning. Training and development will be essential as workers upskill and reskill to align with AI‑driven processes. While the upfront investment in education and change management may seem steep, the long‑term returns are profound. AI can boost productivity, streamline decision‑making, and unlock new growth opportunities. Organizations that prioritize this paradigm shift will position themselves to thrive in an AI‑enhanced future, while those that resist risk falling behind.
THE SOLUTION
…AI-tailored training and early-win projects are crucial to overcoming it.
65% of financial institution leaders believe successful AI implementation will rely more on people's willingness to adopt it than on the technology itself. Implementing a tailored AI training program for different roles is crucial for adoption, ensuring employees understand how AI enhances their tasks.
Organizations must also foster a culture of experimentation, encouraging continuous learning and innovation. Early-win projects, like AI chatbots or predictive tools, demonstrate quick successes, build trust, and accelerate broader AI integration across the company.
This approach ensures that employees, from frontline staff to decision-makers, receive the right level of training suited to their responsibilities, helping them understand how AI can enhance their day-to-day tasks.
AI-Driven Financial Advisory and Legacy System Modernization
Allianz's initiative launched an AI‑powered RAG‑based LLM system, revolutionizing financial advisory by delivering real‑time, contextually relevant information, offering accurate, personalized advice instantly without manual research. This boosts efficiency by reducing time spent on sourcing data, enabling advisors to focus on client engagement and strategic planning.
The system enhances decision‑making through AI‑driven insights, improves client satisfaction with tailored responses, and ensures compliance with regulatory guidelines, reducing risk. Additionally, Globant helped a prominent bank to accelerate the modernization of its outdated COBOL codebase into Java microservices using GeneXus Enterprise AI. They rearchitected and optimized over 11,600 lines of COBOL in just 105 hours.
