Over the past years, organisations have invested heavily in digital transformation. They have accelerated cloud adoption, implemented new service management platforms, launched automation initiatives and, more recently, embraced artificial intelligence.
This pace of investment shows no signs of slowing. Analyst firm Gartner forecasts worldwide IT spending to reach USD 6.37 trillion in 2026, with more than USD 1.46 trillion allocated to software alone. At the same time, software costs per employee continue to rise across organizations.
Yet despite these investments, many core service management metrics remain largely unchanged. First-contact resolution rates have improved only marginally, while self-service adoption continues to progress more slowly than many organizations expected. In short, companies are investing more than ever in digital service capabilities, without necessarily seeing a proportional increase in productivity or service quality. Organizations are facing a modern innovation paradox.
This raises an important question: if organizations have access to more technology than ever before, why do service teams continue to struggle with fragmented processes, growing complexity and increasing operational overhead?
The answer is not a lack of investment. Rather, many organizations are trying to address modern challenges with an operating model that is no longer suited to today's digital environments. With every new application, complexity increases—often faster than an organization’s ability to manage it effectively.
When Fragmented IT Environments Become a Productivity Challenge
For years, organizations have introduced new tools, workflows and platforms to meet specific business requirements. Each investment may have delivered value individually. Collectively, however, they have often resulted in fragmented operating environments where services, assets, endpoints, software and processes are managed across multiple disconnected systems.
As complexity increases, visibility decreases. At the same time, automation becomes more difficult to scale. As a result, teams spend a growing share of their time consolidating information, integrating systems and coordinating activities across organizational and technical boundaries.
Artificial intelligence faces the same challenge. AI systems can only deliver meaningful outcomes when they have access to the information they need within a connected context. When relevant data is spread across multiple systems, opportunities remain untapped and outputs risk becoming incomplete—or even inaccurate. Service teams are still required to manually connect information, validate data and make decisions.
This is where the concept of an integrated platform becomes increasingly relevant—not as another layer of technology, but to connect services, assets, endpoints and identities within a shared operational context. Creating this context enables service teams not only to respond faster but also to improve end-to-end business processes. Examples include helping employees become productive from day one, managing software requests from demand to licence utilisation, or identifying and resolving device issues proactively before they impact users.
Research in Action highlights the value of Matrix42's unified platform approach:
For Matrix42, this reflects the essence of an integrated platform strategy: modular solutions that work together seamlessly, connecting tickets, assets, endpoints and identities in a single operational model. The objective is to reduce fragmentation without sacrificing flexibility, control or the ability to evolve incrementally. The true value lies in connectivity.
How Context Enables Intelligent Automation in Service Management
When services, assets, endpoints, software, identities and workflows are connected within a shared operational context, the role of automation changes fundamentally. Automation is no longer limited to individual tasks or isolated workflows. Instead, it can operate across entire service processes. This is where Intelligent Service Management comes into play.
By combining operational data, automation and AI within a connected model, Intelligent Service Management enables service teams to diagnose issues faster, automate repetitive work and identify potential problems before they escalate. This marks the shift from reactive ticket handling to proactive service operations.
Rather than waiting for incidents to occur, signals from devices, assets, systems and service processes can be detected early, analysed with AI and translated into preventive actions or automated workflows. For organisations, this means less manual coordination, more reliable service delivery and greater capacity for work where human judgement truly matters.
This evolution demonstrates that intelligent automation is not simply another feature added to existing processes. It represents the next stage in the evolution of service management itself. Research in Action also recognizes this direction in Matrix42's product strategy:
Ultimately, the roadmap is not the most important aspect. What matters is the direction it represents. Service management is becoming more integrated, more automated and more strategic. It is evolving into Intelligent Service Management—a model where context, automation, AI and governance work together to ensure that technology investments translate into measurable service outcomes.
Learn how Matrix42 helps organisations connect services, assets, endpoints and workflows through an integrated platform.
What might also be interesting: Read our blog on why Research in Action recognises Matrix42 as a "European Powerhouse in Service Management."
