This blog was written by HFCL.
2024 was the year of AI pilots. 2025 must be the year of AI performance
In 2025, the banking industry is rethinking its approach to technology and infrastructure. Caught between rising cost-to-income ratios, eroding profitability, and intensifying competition from digital-native disruptors, the question facing most institutions isn’t whether they should adopt AI—but whether they’ve structured themselves to truly benefit from it.
Artificial intelligence is no longer a “nice to have.” It has moved from boardroom conversations and pilot projects into the very core of banking strategies. And yet, there’s a striking disconnect. According to IBM’s 2025 Global Outlook for Banking and Financial Markets, only 8% of banks in 2024 had a strategic, enterprise-wide approach to generative AI. A staggering 78% were still in tactical mode. That gap is more than just operational. It’s existential.
Beyond the AI Buzz: A Strategy-First Imperative
For years, banks have invested in digital transformation. But many initiatives—focused on front-end digitization or isolated use cases—have fallen short of producing long-term financial impact. Cost reductions have remained elusive. Core systems remain siloed. And customer experiences often remain underwhelming.
That’s because AI’s true value isn’t in isolated tools. It’s in how well a bank integrates AI across its entire operating model, from decision-making and product design to compliance and risk management. To thrive, banks must move beyond “AI as a tool” to “AI as a business model foundation.”
How Strategy-Oriented Banks Are Winning
Banks that are winning today aren’t just using AI to automate—they’re reimagining how they operate.
- They’re designing for enterprise-wide scalability—restructuring legacy systems into modular, flexible, cloud-native architectures that can assimilate AI-driven features across business functions.
- They’re building a culture of AI risk governance, where every employee is trained to manage AI-related risks around ethics, bias, privacy, and model explainability.
- They’re transforming high-impact functions like AML, KYC, credit scoring, and product recommendation engines—using AI to cut costs and improve precision simultaneously.
This holistic AI strategy is helping institutions shift “right and up” on the banking performance quadrant—boosting both Return on Average Equity (ROAE) and Price-to-Book Ratios (PBR).
Rewriting the Rules of Profitability
Banking profitability has long depended on a delicate balancing act—interest rate arbitrage, efficient cost structures, and prudent risk management. But the rules are being rewritten.
Generative AI, large language models (LLMs), and large reasoning models (LRMs) are introducing a new lever: precision at scale. Banks can now predict customer behavior, simulate risk scenarios, and personalize engagement like never before.
Yet, this power requires a complete shift in thinking. Instead of adding AI onto existing structures, the frontrunners are building AI-first organizations—embedding it into the fabric of how they operate, design products, serve customers, and report compliance.
From Compliance Cost Center to AI Differentiator
One of the least glamorous but most impactful areas for AI is compliance and risk. For decades, regulatory reporting and fraud detection have eaten into banks’ margins. But now, AI is turning these burdens into strategic advantages.
For instance:
- AI can simulate future regulatory changes to prepare better.
- LRMs can flag anomalies in real time, drastically cutting fraud detection times.
AI-driven credit models are making previously “unscorable” customers—especially SMEs—creditworthy.
As IBM notes, only 28% of financial organizations currently use AI and automation extensively for security, despite rising breach costs averaging $375 million for major incidents. For those that do, the payoff isn’t just in risk reduction—but in customer trust and operational resilience.
The Future Belongs to the AI-Built Bank
The next frontier in banking won’t be won by those who “use” AI—it will be won by those who are built on AI. These banks will:
- Treat AI platforms as the new core.
- Operate with “AI factories” that drive experimentation and scale.
- Redefine success beyond transactions—towards intelligent, anticipatory, embedded financial experiences.
The transformation isn’t just technological. It’s cultural, strategic, and financial. And it’s happening now.
Bridging AI Strategy with Network Intelligence: The IOBYHFCL Advantage
At the core of a successful AI strategy lies a robust, secure, and intelligent network infrastructure. That’s where IO by HFCL comes in. As India’s leading enterprise Wi-Fi, switching and management solution, IO by HFCL is redefining how banks build digital foundations for an AI-first future.
Our end-to-end, AI-powered network solutions are purpose-built for the BFSI sector—enabling seamless integration of AI workloads, secure branch connectivity, and real-time visibility across thousands of distributed endpoints. From State Bank of India’s GITC campus to NABARD’s rural outreach, IO by HFCL has consistently delivered high-availability, compliance-ready networks that scale with speed and precision.
In an era where infrastructure is strategy, we’re helping banks move beyond patchwork digital fixes to future-ready, intelligent network fabrics—essential for enabling AI-driven decisions, secure financial services, and resilient operations.
Closing Thoughts: From Pilots to Performance
2024 was the year of AI pilots. 2025 must be the year of AI performance. The clock is ticking. Banks that fail to align their AI ambitions with enterprise-wide strategies risk becoming the cautionary tales of this decade.
But for those ready to lead—with clarity of vision, bold investment, and unrelenting focus—the payoff will be more than efficiency. It will be dominance.
Because in this new era of financial services, AI is not just the disruptor—it’s the differentiator.
