For the past decade, IT teams have driven transformation – digitising processes, automating workflows, and migrating to the cloud. Today, technologies that once evolved independently are converging, reshaping how systems operate, unlocking new sources of competitive advantage, and creating opportunities for businesses to redefine value delivery. At the heart of this shift are data, low-code platforms, integration, orchestration, artificial intelligence, and cybersecurity. Their convergence signals a pivotal moment, one that will demand nothing less than a complete reinvention of the IT operating model over the next five years, elevating IT as a critical business differentiator.

Data stands out as a foundational driver. While already recognised as a strategic asset, data is increasingly being activated by teams and business domains where it originates, enabling decentralised value creation throughout the enterprise. IT will no longer simply store and centralise data usage. Instead, it will establish the foundations of a distributed data operating model – one that empowers business domains to own their data products while maintaining global standards for security, interoperability, and quality. Reinvention here means enabling data intelligence to emerge across the enterprise without losing coherence. This shift in the operating model will require new roles and expertise, refined data governance strategies, and technical capabilities from edge analytics platforms to vector databases and tailored GenAI agents to storage mechanisms that copes with data volumes doubling every 12 months.

Similarly, by 2030, most new business applications will be created outside traditional development teams, thanks to low-code platforms that empower citizen developers. Low-code platforms are rapidly evolving to provide a breadth of predefined functions – from HR to logistics – with the ability to design and deploy fit-for-purpose applications. For IT, this means reinventing itself yet again as both enabler and protector: providing secure building blocks, reusable APIs, and oversight mechanisms that allow safe innovation at scale.

Integration, in this context, becomes a strategic priority rather than a purely technical discipline. Event-driven architectures, API management solutions, and integration platforms enable organisations to assemble capabilities dynamically instead of building monolithic systems. This provides essential support to the shift in operating models concerning data and applications. The mission of IT shifts from owning every component to orchestrating a connected ecosystem of internal and external services – ensuring speed, adaptability and resilience.

To enable dynamically assembled systems, infrastructure must become adaptive: workloads should adjust automatically, compliance checks must run continuously, and the systems should self-configure. This makes autonomous orchestration another powerful driver by 2030. IT will no longer prescribe processes but define intent – delivering value through policy-as-code guardrails and resilience, rather than not manual workflow steering, moving towards truly autonomous operations.

Artificial intelligence, being the most visible catalyst for convergence across these technologies, is swiftly automating IT operations at scale. What began as simple assistance – coding suggestions or incident summaries – has evolved into autonomous problem solving. By 2030, AI-driven operations platforms will detect anomalies, resolve incidents, optimise performance, and even generate infrastructure or application code without human intervention. This shift forces IT departments to rethink roles, structures, and governance. Instead of manually running systems, teams must learn to supervise and shape AI behaviour, creating new responsibilities such as AI model governance, AI lifecycle management, and automated risk controls. At the same time, IT must address AI-specific risks-bias, hallucinations, privacy, and accountability, while ensuring regulatory compliance (e.g., AI Act), managing AI sovereignty, and optimising costs through practices like GenAI FinOps and TCO management. Cross-functional fusion teams will become the norm, blending IT and business expertise to co-create AI-driven solutions, making mastery of human-AI collaboration essential for success.

And, inevitably, the rise of autonomy and hyper-connectivity elevates the stakes for cybersecurity. With threats projected to cost $20 trillion by 2030, next-generation defences are moving towards self-learning, self-healing models. Security becomes embedded in every product team, architecture choice, and automation pipeline. Operations will increasingly leverage SIEM and SOAR solutions to transform risk management, automating responses and enabling proactive anomaly detection, facilitating security enhancement of business processes and applications. This shift in focus towards advanced roles that fine-tune workflows and investigations. Cybersecurity will no longer be a siloed function; it will become a pervasive capability woven into every layer of IT and business operations.

Together, this convergence and evolution lead to one clear truth: technology is reinventing faster than IT can adapt—unless the IT model evolves too. The IT function of 2030 will be intelligent, adaptive, distributed, and deeply integrated with the business. Reinvention is no longer an aspiration; it is the operating model for the future. For businesses, the transformation of IT is imperative for growth and resilience. Executives must champion new roles, operating models, and mindsets to ensure IT moves beyond support to become a strategic enabler. The future belongs to organisations that master integration, automation, and human–AI collaboration.

By Vincent Gauché –Managing Director, PwC Luxembourg, Krzysztof Jaros-Kraszewski – Director, PwC Luxembourg, Ravi Jhawar – Director, PwC Luxembourg