If you talk to CIOs right now, most of them will tell you AI is finally doing what it promised. According to Lenovo’s CIO Playbook 2026, enterprises are moving well beyond experiments and into real deployments, and the returns are starting to show. Believe it or not, some organizations expect as much as $2.79 back for every dollar they put into AI. That is not a vague projection anymore, folks. For many companies, it already feels real.
Almost half of AI proof-of-concepts have made it into production, which is a big deal when you think about how many AI pilots used to stall out. Spending is rising too. Nearly every organization surveyed plans to increase AI budgets over the next year, with average growth sitting around 13 percent. On the surface, this looks like a clean success story, the kind CIOs like to put in slide decks.
But the same research also shows a quieter problem forming underneath all that optimism. While 60 percent of organizations say they are in late-stage AI adoption, only 27 percent have solid governance in place. That means most companies are scaling systems they do not fully control yet. Data quality is still messy. Integration is harder than expected. Skills are missing. And yet, confidence remains sky high.
That disconnect matters even more as attention shifts to Agentic AI. This is the next big thing CIOs are talking about, and it is very different from the chatbots and copilots everyone is used to. Agentic systems can act, make decisions, and move across systems with far less human involvement. CIOs know this is coming, but most are not ready for it. Only 21 percent say they are using Agentic AI today. More than half are still poking at pilots or early tests. Even more telling, three in five admit they are at least a year away from being able to scale it properly.
One thing CIOs do seem to agree on is where AI should live. Hybrid AI has clearly won the argument. About 62 percent of organizations now prefer a mix of public cloud, private cloud, and on-premises infrastructure. That is not about fashion. It is about control. Once AI becomes core to operations, companies want flexibility, predictable costs, better security, and a way to keep sensitive data where it belongs.
Infrastructure is suddenly a lot less boring, too. The research shows that performance, scalability, and energy efficiency are now among the top factors for AI success. That includes servers in data centers, systems at the edge, and even employee devices. AI-capable PCs are now the top IT investment priority for 2026, which says a lot about how workloads are spreading out from the cloud and into everyday work.
Lenovo is leaning hard into this shift, positioning itself as a company that can cover the whole stack. Its new Agentic AI and xIQ platforms are designed to help enterprises go from pilot projects to real operations without tripping over governance and integration later. The company is also pushing its ThinkSystem and ThinkEdge servers as a way to make inference faster and more practical across cloud, data center, and edge setups.
What this research really shows is that the easy part of enterprise AI may already be over. Early gains came from trying things out and proving AI could work. The next phase is about running it at scale without breaking everything else. CIOs who build the right foundation now will probably do well. The ones who keep winging it may find out too late that AI success is a lot harder once it becomes mission critical.
