Global IT spending is set to reach $6.31 trillion in 2026, 13.5 per cent more than the previous year. Gartner values the artificial intelligence market alone at $2.59 trillion. So there is no shortage of capital for technology. It is much harder to ensure that subsequent investments form a single, efficient system rather than yet another layer of systems, data and dependencies.
This is clearly illustrated by IBM’s data. Half of the 2,000 CEOs surveyed admitted that the pace of technology investment had left their companies with a fragmented, poorly integrated IT environment. Only 25 per cent of AI initiatives delivered the expected return, and a mere 16 per cent were successfully rolled out across the entire organisation. At the same time, 68 per cent of CEOs consider an integrated data architecture to be essential for cross-functional collaboration within the company.
It is precisely in this gap between the purchase of technology and its actual use that the problem of integration lies.
A company is only as fast as its slowest connection
A new CRM system can be deployed in the cloud. An AI model can be up and running in a matter of days. However, connecting them to the procurement system, warehouse, finance, customer service or data accumulated over a dozen or so years can prove much more difficult.
If each such operation requires a separate project, data mapping and a manually created connection, the cost of the technology ceases to be limited to the price of the licence. The cost of every subsequent change comes into play.
The scale of the problem grows alongside AI. In a 2026 Salesforce survey, 96 per cent of IT leaders stated that the effectiveness of AI agents depends on data integration between systems. At the same time, half of the deployed agents operated in isolation, whilst 40 per cent of respondents cited outdated architecture and data silos as one of the main barriers to AI utilising data.
This is not a minor technical issue. An agent tasked with preparing a quote, handling a complaint or predicting stock shortages needs data from several systems and the ability to perform specific operations within them. Without this layer, even an advanced model remains an interface to incomplete information.
Integration is becoming financially measurable
In 2026,KPMG surveyed 300 managers responsible for, amongst other things, sales, marketing and customer service. 87 per cent considered the integration of these areas a priority, but only 5 per cent of companies reported having fully integrated their processes. Organisations belonging to this small group were three times more likely to report higher revenue growth. The most frequently cited barriers were legacy systems and fragmented data.
This does not prove that integration in itself generates revenue. However, it does demonstrate its link to something far more tangible than simply having a well-organised IT architecture. A company that is unable to quickly integrate sales, payments, logistics and customer information launches products more slowly, automates fewer processes and incurs the cost of maintaining the same data in multiple locations.
HEINEKEN calculated the cost of integration
HEINEKEN is a good example of the scale involved . The company built a global API platform designed to replace a model based on more dispersed integrations with a common communication layer between systems.
According to a Microsoft case study published in 2026, the core platform was built in around five months. It already handles around 90 per cent of the company’s global API transactions. Within roughly eight months, its monthly traffic exceeded 50 million calls, and the cost per call fell by as much as 75 per cent. Since its launch, the platform has recorded 100 per cent availability and no incidents in the highest P1 or P2 categories.
This is a case study of a technology provider, so it is not a universal benchmark. However, it illustrates a significant shift in the economic model. An API built once can be reused by subsequent applications and teams. Integration ceases to be a separate undertaking each time.
A similar mechanism can be seen in banking. Wells Fargo uses standardised, reusable APIs to connect generative AI models without having to rewrite applications whenever the model changes. In one of the bank’s processes, the time taken to find an answer has been reduced by around 20 per cent.
Integration is therefore a rather unspectacular part of the transformation, but it is precisely where its cost becomes apparent. The more a company invests in the cloud, SaaS and AI, the greater the value of being able to quickly integrate new technologies with existing processes.
By 2026, access to yet another system or AI model will no longer be the problem. The problem begins when you have to make it actually work with the rest of the organisation.
