Enterprises are accelerating investments in artificial intelligence, but many are finding that their technology infrastructure and workforce are not ready to support large-scale AI deployment. According to new research by Kyndryl, organizations are moving beyond AI pilots and expanding implementation across business functions, yet outdated IT systems, legacy infrastructure, and workforce skill gaps are slowing progress toward realizing AI's full value.
The study found that aging servers, fragmented technology environments, and insufficient modernization efforts are major barriers to AI adoption. Many organizations also lack employees with the necessary AI expertise, making it difficult to integrate AI into everyday operations and scale projects efficiently. As a result, companies risk falling short of expected returns despite increasing investments in AI initiatives.
To overcome these challenges, businesses are increasingly prioritizing infrastructure upgrades, cloud modernization, and workforce reskilling. Rather than focusing solely on deploying AI models, successful organizations are investing in employee training, strengthening governance frameworks, and redesigning business processes to enable effective collaboration between people and AI systems. Experts say these foundational improvements are essential for sustainable AI adoption.
The report concludes that AI success depends on organizational readiness as much as technological capability. Companies that modernize their IT environments, develop AI-skilled talent, and align AI initiatives with broader business strategies will be better positioned to scale AI successfully and generate long-term business value. Without these investments, even advanced AI technologies may struggle to deliver meaningful impact.
