The pace of technological evolution has transitioned from a steady jog to a full-blown sprint, leaving many organizations breathless as they attempt to juggle modernization efforts with a growing skill shortage and evolving regulatory compliance.

IT leaders today are operating in a paradoxical landscape: they are expected to be at the forefront of AI innovation while keeping legacy IT infrastructure alive with the help of a dwindling set of experts who still retain the tribal knowledge and expertise to keep them running.

As system complexity grows and data volume expands across hybrid environments, the attack surface increases with it.

With cyber attacks increasing in volume and continuing to evolve, being targeted is not a question of if but when, and the pressure IT leaders face has never been higher.

Data security emerges as the biggest IT modernization concern

With the constant threat of a debilitating cyber breach hanging over their heads, it is no surprise that 69% of IT leaders cite data security as the top concern that’s keeping them up at night, overtaking the need to improve overall IT performance. This trend marks a shift in focus for the industry at large: optimization can only be a priority once data is secured and backup plans are in place.

The uptick in transition to hybrid environments has fragmented the traditional security perimeter enterprises used to maintain, making it harder to maintain a "single source of truth" for security policies. This is a foundational challenge because data security has a direct impact on how confidently organizations can pursue modernization initiatives and growth. As digital footprints expand, senior IT management must act as guardians of enterprise data while also managing the complexities of their internal governance structure.

The race to harness AI and automation has only further compounded the need for enterprises to secure data and take a closer look at their governance. The lifeblood of any AI initiative is access to high quality data that comes from a verified source with a traceable lineage. In order to find success with AI, the IT infrastructure must be able to support the integration, and data is the single most important piece of the puzzle.

Evolving compliance and regulatory demands

The regulatory landscape is shifting beneath the feet of global enterprises, with frameworks like DORA, and emerging AI-specific regulations like the EU AI Act demanding a new level of granular oversight that extends beyond the enterprise’s own systems and to the convoluted supply chain of the vendor ecosystem.

In fact, less than one-third of surveyed IT leaders reported that they were extremely confident in their organization's ability to pass their next regulatory audit, which is a direct consequence of how regulations have changed to keep up with the increased cyber risk.

For years, building cybersecurity strategies around passing audits was thought to be enough. Making sure that the right controls are in place, and the appropriate policies implemented was sufficient to tick all the boxes, and enterprises passed with flying colors.

As regulatory framework requirements shift from static compliance to dynamic defense demands, enterprises must center their cyber resilience around continuous readiness. This needs to be supported by regular activity, as opposed to one-off sweeps, such as constant vulnerability scanning and real-time response rehearsals.

DevOps and the IT skills shortage

DevOps has always been an area of IT ruled by speed and efficiency, and the proliferation of AI tools only exacerbated this further. As new technologies establish themselves as the tools of choice for most developers, enterprises that still use older systems begin to face a unique challenge: finding skilled personnel with the necessary expertise to keep those systems running.

This is not a problem related to a few isolated cases, in fact, for certain sectors such as banking and finance, the percentage is even higher. A 2024 study conducted by the Financial Conduct Authority (FCA) found that 92 percent of UK companies within the financial services sector rely on legacy technology.

This acute need has turned into a race against time, as the professionals with the much-needed skill sets have started to retire, causing the gap to widen with each passing year, underscoring the critical need to reskill existing employees and improve the pipeline of talent.

The path forward for IT leaders is not necessarily found in choosing between the old and the new, but in bridging the two with a strategy rooted in resilience. Prioritizing visibility, data governance, and security is key to ensuring resilience, regulatory compliance, and ultimately, the success of future modernization projects.

Navigating the AI era requires enterprises to view modernization not as a one-off update but a continuous project that is rooted in strategic vision and informed by business objectives.

Ultimately, the goal is to enhance what is working and remove what no longer serves its purpose, without disrupting daily operations or compromising resilience.

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This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

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President of the Data Modernisation business unit at Rocket Software.