In our recent blog, we shared that application modernization sits at the top of every CIO’s priority list, and for good reason. But modernization is not a one-time project. It’s a constantly moving one, and the decisions organizations make in 2026 will determine whether they keep pace or fall behind.
Here’s what we believe will drive decision-making in the year ahead, how vendor strategies are evolving, and why these shifts signal a more cautious customer mindset.
AI Budgets Are Real, But Direction Is Unclear
CIOs have carved out approximately 25% of their annual budgets for AI projects. That budget allocation is happening right now. The challenge is that many organizations do not necessarily know what those AI projects will be yet. They just know the board said they need to have an AI project, so they have money set aside.
This creates an interesting dynamic for infrastructure vendors. Organizations are actively looking for ways to tie infrastructure deliverables to AI use cases because that is where the budget is being spent. The talent coming up is a different set of talent than what historically existed in IT. What does this mean? More generalists, not specialists. The focus is on trying new things, like the prompt engineering approach, rather than requiring deep technical specialists.
Making Infrastructure Simple
The recommendation for vendors aligning with modern buyer expectations is straightforward: reduce friction, reduce complexity, and make it so a generalist can do the deployment. Then, automation comes next.
This approach accelerates business demands and business goals, helps organizations reach the service level objectives everyone is working toward, and meets business KPIs because teams can focus on business logic rather than infrastructure management.
Times have changed dramatically in IT and tech. The more AI and automation, and new tooling come into place, the more it changes what organizations are doing with their skillsets.
Self-service Is No Longer Optional
From the end user side, business KPIs no longer afford the ability to put in a help desk ticket and wait three days for someone to open it and look at it. Organizations that can enable a self-service model for end users to do their own deployments and manage their own environments enable better productivity.
Reducing friction for end users and lines of business to meet their business KPIs without the delay of IT tickets and working through bugs is critical. Sometimes the solution could be just flipping a switch and allocating storage or allocating compute. That needs to have self-service ability, which also means vendors need to be concerned about regulation, compliance, and governance as part of their deployment model.
“… The more you can enable a self-service model for your end users to do their own deployments and their own environment… Now you‘ve enabled your end users to be productive.”
Paul Nashawaty, Principal Analyst at The Cube Research
Infrastructure Decisions Are Slowing Down
Recent vendor instability has made organizations more cautious about long-term infrastructure commitments. Customers and partners have grown more careful in their evaluation process; they’re asking harder questions and demanding more visibility into vendor operations before making decisions.
“Most organizations lack the data maturity to leverage AI effectively… the cost impact is too great if the business benefits are not clear.”
Susan Odle, CEO, StorMagic for Disaster Recovery Journal
This caution is particularly evident in AI infrastructure investments. When organizations lack data maturity, they can’t leverage AI effectively immediately. Thus, when the business benefits are not clear, the cost impact becomes too great to justify large-scale investments. Organizations are taking their time to understand what they actually need before committing resources.
The Edge Is Regaining Strategic Importance
Cloud adoption remains strong, but organizations are rethinking over-centralization. It’s no secret that high-profile cloud outages aren’t uncommon. They’ve reminded everyone how risky it is to depend too heavily on centralized cloud infrastructure. By 2026, increased investment in on-premises hyperconverged infrastructure for edge and mission-critical workloads is expected.
Training large AI models in the cloud will continue because the scale and resources required make the cloud the logical choice for that workload. However, businesses are aware that real-time decision-making is better handled closer to where data is created. Processing data at the edge reduces latency, improves response times, and decreases dependency on centralized infrastructure that can fail.
Edge IT Infrastructure Decisions in 2026
What does this mean for your infrastructure decisions in 2026? It means you should prioritize flexibility over rigid architectures and choose platforms that can evolve as conditions change. Teams now focus on infrastructure that supports the people they already have, not specialists they hope to hire later, while still delivering the performance the business needs, whether workloads run in the cloud, at the edge, or somewhere in between.
Vendors also recognize that customers and partners are entering the new year with more caution. Organizations must justify every cost, and as infrastructure decision-making slows, teams make stronger and more deliberate choices. Recent vendor instability has pushed organizations to think carefully about long-term commitments and demand greater transparency into how vendors operate.
In 2026, strong infrastructure decisions will come from adaptability, clear value, and confidence in the partners you choose.
Learn more about these insights in our PodMagic episode, What Real-World IT Teams Want from Infrastructure with Paul Nashawaty.
