Google Cloud survey links legacy software to stalled AI projects

Legacy systems are consuming AI modernization resources

Google Cloud partnered with Hypothesis Group to examine how existing technology environments affect organizations’ ability to put AI into operation. The study defines legacy technology as software running locally on computers and servers rather than natively in the cloud.

Nearly half, or 49%, of respondents said reliance on on-premises software had delayed, reduced in scope, paused or canceled AI or other technology initiatives. Google Cloud describes this as an “innovation tax”, arguing that the staff and resources required to maintain older systems are competing directly with work on AI modernization.

Routine patching and maintenance were identified as major operational bottlenecks. The company says AI-enabled vulnerability discovery is increasing the number of flaws found in legacy codebases faster than human security teams can realistically address them. This leaves IT teams balancing the upkeep of existing systems against efforts to deploy newer AI capabilities.

Vendor dependence adds commercial and security risks

The survey suggests that continued dependence on legacy environments is often driven by vendor lock-in rather than a deliberate architectural preference. Thirty-nine percent of decision-makers said reliance on legacy software and cloud providers forced them to deal with complex licensing rules or contracts, or reduced negotiating flexibility.

Google Cloud also warns that concentrating operating systems, productivity applications, cloud hosting and AI models with one vendor can create a single point of failure. In the company’s view, an autonomous AI agent is only as secure as the operating system and network it uses. A weakness in that underlying stack could increase an organization’s attack surface rather than improve resilience.

The findings indicate that many leaders want more freedom to select AI systems independently of their existing software estates. Eighty percent agreed that a provider’s installed base should not determine which AI technology an organization uses. Seventy-eight percent said providers that led the previous era of enterprise technology may not be best positioned to lead the AI era.

Google Cloud calls for choice and AI-assisted defense

Google Cloud says enterprises and policymakers should preserve architectural and provider choice across software, cloud and AI. It also calls for secure-by-design foundations that remove vulnerability classes before software ships, reducing the need for IT teams to handle perpetual patching.

For legacy systems already in production, the company recommends moving from manual triage toward AI-assisted defense. It points to Security Command Center and Mandiant threat analytics as platforms that can help teams identify active exploit paths, prioritize critical exposure and automate remediation across complex, hybrid environments.

For enterprise users, the survey frames AI modernization as an infrastructure and procurement issue as well as a model-selection decision. Google Cloud’s findings support a strategy built around interoperability, reduced vendor dependence and stronger protection for the systems on which autonomous workflows will run.