The shift from experimental proofs of concept to commercially viable deployments is accelerating across global enterprises. According to the IT services provider Kyndryl in its Global & European Readiness Report 2026, 64 percent of surveyed organizations worldwide now report positive returns from their investments in artificial intelligence and machine learning. In Europe, this share reaches 65 percent. Compared to the previous year, these numbers represent an increase of 10 to 12 percentage points, highlighting growing operational maturity.
At the same time, the survey of 3,700 executives across 21 countries reveals profound strategic regret. A striking 98 percent of senior leaders stated that, in hindsight, they would take a fundamentally different approach to their AI adoption strategy. Furthermore, almost half of the participating companies were forced to drastically revise their AI roadmaps over the past twelve months. Hasty rollouts, siloed deployments, and inadequate architectural foundations have caused costly course corrections across multiple industries.
A primary bottleneck behind these strategic pivots lies in legacy corporate technology. Fully 66 percent of enterprise leaders acknowledged that their core IT infrastructure requires comprehensive modernization before AI solutions can be deployed sustainably. Many organizations deployed advanced models onto outdated systems without first addressing complex data pipelines and storage architectures. This misalignment created integration friction, slowing deployment timelines and inflating operational costs.
The operational challenge is equally acute in cybersecurity. The proportion of companies that feel adequately equipped to defend against AI-driven cyber attacks dropped to just 25 percent. This marks a sharp decline of 11 percentage points compared to 2025. While external threat actors increasingly leverage automated machine learning tools to probe corporate vulnerabilities, internal security postures have struggled to keep pace with the rapid operational spread of new tools.
Despite these obstacles, businesses are not retreating to testing labs. Globally, 84 percent of surveyed organizations have progressed beyond isolated pilot phases and now run operational workloads in production environments. Across the nine European core markets examined in the report, commercial pressures continue to mount. Companies must now demonstrate that their deployments deliver measurable balance-sheet value, operational efficiency, and durable competitive advantage.
Kyndryl's findings demonstrate that corporate AI success hinges far more on organizational resilience and foundational IT health than on access to raw algorithmic power. The era of uncontrolled experimentation is giving way to disciplined consolidation, placing governance and threat management at the forefront. Organizations that address infrastructure debt and reinforce defensive capabilities will solidify their competitive positioning, while those neglecting the basics face escalating operational vulnerabilities.