Technology has become the foundation of modern banking operations. Once viewed as a cost center, information technology (IT) systems are now critical to supporting growth, customer satisfaction and regulatory compliance. Yet, as technology advances, so do the costs and complexities of managing sprawling IT estates.

For senior banking leaders, the challenge often lies in managing the delicate balance between investing in cutting-edge solutions and maintaining financial discipline amid rising economic pressures. As a result, leaders must grapple with one central question: How can we cut and manage costs without compromising on innovation or service delivery?

To truly unlock the benefits of artificial intelligence (AI) and deliver real value, banking leaders need greater visibility into their technology spend, along with a focus on agility and simplification. Here’s why that matters.

Create transparency

Banks have been early adopters of AI, quick to experiment with new technologies and applications. But with this early adoption comes the pressure to deliver measurable results and ensure that budgets are spent in the right areas of the business. Without a clear picture of where the money is going, it’s nearly impossible to prove return on investment (ROI) or assess the impacts, especially for larger organizations operating across multiple regions or countries.

Take First Citizens Bank as an example. Their old IT budgeting process was a major drain on time and resources, involving four team members working across 50 cost centers and spending 45 days managing spreadsheets. This left little room for more important work, such as analyzing data or strategic planning. By implementing tools for cost transparency, benchmarking and IT planning, they streamlined the process. This freed up time for cost managers to tackle bigger operational challenges and enabled IT finance teams to provide actionable insights that created real value.

When financial, operational and technology data come together, organizations gain a clearer view of how IT investments are being used. Decision-makers can easily spot redundancies, identify underused resources and address mismatched spending. For example, I’ve seen visibility tools uncover inefficiencies in cloud agreements, such as paying for unused server capacity or failing to optimize storage tiers.

With this clarity, IT teams are better equipped to cut unnecessary costs and boost operational efficiency. More broadly, it also helps banks align IT spending with their broader business goals, whether that’s enhancing customer service, simplifying compliance or strengthening cybersecurity against growing threats.

Plan with scenario forecasting

In a fast-paced industry like banking, agility is key. Constant revisions to regulations, shifts in economic conditions and changes in client expectations can place significant strains on IT budgets. Yet many banks rely on reactive responses rather than proactive planning, leaving them less prepared during periods of disruption.

One tool that can help here is scenario forecasting, which offers a way to bring agility into IT cost management. By modelling how key changes, such as new compliance requirements, rising vendor costs or changing merger opportunities, might impact IT costs, banking institutions can better prepare for and mitigate risks.

Consider the implications of the European Union’s (EU’s) new data-protection laws, for example. A proactive approach to modelling the costs of compliance, such as expanded encryption capabilities, enhanced data storage systems and stricter monitoring protocols, allows banks to make changes before the regulations take effect. This can play a big part in ensuring day-to-day operations continue to run smoothly.

Simplify ecosystems

After years of digital transformation, many banks now find themselves managing sprawling and complex IT systems. Over time, new tools and platforms have been stacked on top of one another, sometimes without much thought to how they work together. This can create a tangled web of overlapping legacy systems and redundant applications, which not only strain budgets but also impact efficiency and security.

Simplifying this complexity through a process called application rationalization is a critical move for banks ready to take back control of their tech portfolios. Application rationalization involves thoroughly auditing all systems, identifying outdated tools that no longer align with strategic goals and consolidating platforms wherever possible.

For example, Bank of Ireland tackled inefficiencies in its IT estate through a structured rationalization effort. In just the first year, it reduced its application portfolio by 15 percent, saving €2.5 million. This not only delivered financial savings but also freed up resources to modernize client-facing platforms and improve their service delivery.

Alongside cost savings, this process also reduces risk. Older systems that are no longer supported often bring cybersecurity vulnerabilities or compliance issues that modern tools can better address. Through streamlining IT ecosystems, banks can enhance operational resilience, improve efficiency and redirect budgets toward innovation and growth.

Innovate with AI and automation

AI is becoming a larger part of industries everywhere, with data showing that in the United Kingdom, it’s primarily used for data analysis (68 percent), process automation (52 percent) and cybersecurity (49 percent). But while these tools can be game-changers, they aren’t cheap.

For banks and financial institutions, the key to getting the most out of AI and automation is using them strategically. Take fraud detection. AI-powered systems can flag suspicious activity in near real-time, making it easier to stay ahead of potential threats. On the customer-service side, AI chatbots are taking pressure off call centers while providing customers with fast, helpful responses.

Done right, AI and automation can save a lot of money. Many banks are already using automated IT-infrastructure management to reduce the time and resources required to maintain their systems. AI in credit-risk modelling is another great example, helping banks make smarter, faster decisions on loan applications.

That said, these tools need more than just a strong start. It’s important to continue tracking ROI to measure long-term success. Are processing times dropping? Is the customer experience improving? Are systems more secure? Too many organizations stop monitoring once the tech is up and running, but regular reviews are key to ensuring AI and automation continue to deliver real value over time.

Turn cost management into long-term gain

For banks, managing technology costs shouldn’t just be about cutting budgets or reacting to immediate pressures. Instead, it’s a chance to rethink IT strategies in a way that balances cost-efficiency with long-term growth and innovation. By focusing on transparency, simplification and smart forecasting, banks can lay the groundwork for real transformation. And with targeted investments in AI and automation, they’ll be ready to succeed.

As the demands on banking technology continue to accelerate, leaders must adopt a proactive mindset, shifting from short-term fixes to strategies that secure resilience, agility and a competitive edge. By taking these steps, organizations can ensure that they benefit from AI while also balancing other business pressures and goals.

This article was originally published on International Banker.