Legacy systems become the new obstacle to deploying AI in businesses
The race to incorporate artificial intelligence into businesses is leaving companies with a conclusion that is less eye-catching than the launch of new models, but potentially more important: an organization's ability to take advantage of AI depends, to a large extent, on how prepared its technology infrastructure is. A new study by GFT Technologies surveyed […]
A GFT Technologies survey of 945 CIOs and CTOs reveals that legacy systems are increasingly hindering the deployment of AI in businesses. The research indicates that 84% of surveyed technology leaders have canceled AI pilots or projects due to limitations in their existing infrastructure. This suggests that the issue is not with AI technology itself, but rather the inability of current systems to support it.
Companies often use a variety of legacy systems, such as separate databases for customer data, financial transactions, and inventory management, which may not be compatible with AI tools. As AI adoption accelerates, companies are recognizing the need to modernize their infrastructure to ensure secure, scalable, and efficient use of AI models.
The survey found that 93% of CIOs and CTOs believe failing to modernize before implementing AI could lead to a major security crisis. Moreover, 89% of technology leaders expressed concern that AI investment is growing faster than the business value it generates. GFT argues that successful AI adoption requires a comprehensive transformation that includes modernizing infrastructure, improving data governance, enhancing security, and aligning with overall business strategy.
For Latin American companies, this challenge is particularly relevant due to the region's extensive digital transformation history, which has resulted in a complex mix of technology generations. Building the necessary infrastructure is crucial for companies to turn their AI investments into tangible results rather than just pilot projects.
Written by urgent.news from Contxto's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
