From the boardrooms of global enterprises to the data centres powering the modern economy, a tectonic shift is underway. It is not just about new systems or better code; it is about rethinking the very essence of how businesses operate.

At this intersection of strategy, technology, and culture lies what many call the “disruption layer” – the space where organisations confront the realities of legacy systems, emerging AI capabilities, and the often-overlooked human dynamics that make or break transformation.

Moving Beyond the Comfort of Legacy Systems

Transitioning from legacy infrastructure is not merely an exercise in IT modernisation; it is a cultural reckoning. As Jaco Vermeulen, CTO at BML Global, explains, “Business operating model and executive mindset [are] stuck in days of old where they perceive they can’t control if they don’t have something physical.” This psychological barrier, rooted in control and familiarity, often outweighs technical constraints.

Claus Jepsen, CTO at Unit4, reinforces this view, describing a deep-seated risk aversion: “Applications may be 20 – 30 years old, but IT teams know what they’re dealing with. They have become conditioned to maintaining these legacy stacks.” This mindset, while comforting, is increasingly at odds with the demands of an agile, responsive business.

Yet, transformation is not about indiscriminately replacing the old with the new. Vermeulen emphasises the need for a “pragmatic approach to change,” based on a holistic understanding of dependencies, scalability, and risk. Similarly, Jepsen introduces the concept of “strangle and replace,” where APIs are layered over legacy systems to gradually migrate capabilities without causing disruption.

Martin Butler, Professor of Digital Transformation at Vlerick Business School, takes it a step further, arguing for alignment between business strategy and systems architecture. “It starts with the business strategy. Capabilities will define systems architecture, and systems architecture will drive modernise, replace, or integrate,” he tells Silicon UK.

AI: A Catalyst or a Complication?

Artificial intelligence is perhaps the most hyped force in today’s digital economy, but its implementation often reveals more complexity than clarity. As Vermeulen bluntly states, “AI has done more triggering kneejerk reactions than to helpfully enable modernisation.” He explains that AI is frequently forced into processes without proper capability assessments, governance, or alignment to business architecture, leading to inefficiencies and disappointment.

However, in specific domains, AI has shown clear value. Butler points out its impact on software engineering: “It brings significant efficiencies to creating and testing code as well as testing scenarios. Test automation has reached new levels of efficiency.”

Jepsen echoes these sentiments, highlighting the dual nature of AI’s influence: “Clearly, there are a lot of efficiency gains in using AI to monitor, maintain and modernise code, but it also raises new questions around governance and data security.”

These complexities underline a key reality: AI is not a plug-and-play solution. It requires the right talent, ethical frameworks, and foundational infrastructure to deliver sustainable value. As Vermeulen puts it, “AI has… introduced a significant amount of complexity without delivering much value in most enterprise settings,” except in highly specialised use cases.

Culture Eats Strategy and Technology

Successful transformation is as much about people as it is about platforms. As Steve Flavell, Co-CEO at LoopUp, explains, “Digital reinvention requires an integrated and holistic approach such that it becomes ingrained into that organisation’s DNA.” He highlights the importance of leadership, continuous learning, and cross-functional collaboration to embed change into everyday operations.

This view is shared by Vlerick Business School’s Butler, who insists on beginning with a compelling business case: “Don’t start from a technological standpoint, but from the lens of business performance,” he tells Silicon UK. Whether the goal is improved customer experience or operational agility, the transformation must be rooted in clear, measurable outcomes. Only then can cultural change follow.

Vermeulen stresses that reinvention should be framed as evolution rather than revolution: “This ensures being contemporary or even ahead in the market without disrupting the business or leaping at dreams without the foundations to build towards those visions.”

Jepsen adds that success hinges on consensus around cross-departmental objectives and metrics: “Consensus on objectives that are cross-departmental is key. This will help to prevent corporate inertia towards embracing change.”

And it all comes back to collaboration. As Flavell puts it, “A cross-functional approach… improves buy-in and reduces resistance to change, as there is a far greater sense of involvement and trust.”

Thriving at the Edge: Capabilities for a Disruptive Future

The future belongs to organisations that can operate at the edge of change, where disruption is not feared but harnessed. To thrive here, several capabilities become critical.

Vision is foundational. Butler notes the importance of active scanning and understanding emerging technologies: “See the future as it unfolds,” he advises. Having an active emerging technology portfolio approach that tracks new applications and potential use cases as they emerge.” Selectivity is equally important. “Know what not to do,” Butler warns. Organisations must be disciplined in choosing initiatives that deliver real value, not just novelty.

Agility underpins it all. Flavell argues for “regular assessment, review and redirection, rather than long detailed planning processes,” while Vermeulen advises that executive leadership must “take a strategic evolutionary approach that ensures being stable, contemporary, scalable and [agile].”

The human dimension cannot be overlooked. Jepsen highlights the importance of data talent and literacy, especially in AI. “It is crucial to ensure the integrity of the data… you need the right talent in place to ensure you get the right results from these AI tools.”

Cyber resilience is another non-negotiable. “Focus on the data and treat it as a first-class citizen,” Jepsen advises. Meta information, interoperability, and data governance will all shape the future of competitive advantage.

Ultimately, thriving amid disruption demands a blend of clear vision, robust architecture, cultural maturity, and iterative execution. It means treating data as an asset, technology as an enabler, and people as the agents of enduring transformation.

The disruption layer is not a single point of change but an evolving frontier. It is where strategy meets uncertainty, and where bold decisions must be grounded in pragmatism and foresight. As these conversations from the edge reveal, transformation is not a destination but a capability—and those who master it will define the next era of business leadership.