Throughout my career in cybersecurity and infrastructure protection — both in government and now at Google Cloud — I have consistently seen that friction between new and existing technology is often a barrier to progress. A new piece of software or service may work wonderfully on its own but then it’s placed within a complex, interconnected IT environment and lost in the operational inertia.
Today, enterprise technology is experiencing a historic transformation. Organizations globally are moving beyond integrating AI and LLMs, and are now utilizing AI to power autonomous, agentic workflows. Nearly 90% of the Fortune 100 are already using Gemini Enterprise to build, scale and govern agents. But as AI systems begin to plan, execute multi-step processes, and work alongside human teams, leaders are confronting this same tension between cutting-edge and legacy technology.
To understand how existing technology environments shape an organization’s ability to operationalize AI, Google Cloud partnered with Hypothesis Group to survey 1,250 enterprise IT and business decision-makers across the United States. The findings reveal a critical paradox: the legacy software systems enterprises rely on to deliver technology to their employees are simultaneously functioning as an innovation tax, actively holding back the AI transformation leaders are trying to achieve.
