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In a "year filled with chaos," Gartner analysts Gene Alvarez and Tori Paulman argue that businesses need three things: an architect to help with AI platforms and infrastructure; a synthesist who will help with AI applications and architectures; and a vanguard who will help with security, trust, and governance. All will face eight big strategic trends in the coming year, which Alvarez and Paulman outlined at this year's Gartner IT Symposium/Xpo 2026 conference.
1. AI-Native Development Platforms
The first trend is developing software when AI is a member of your team, Alvarez said. AI can ease the developer-productivity problem because they create software faster than their human counterparts. To make this work, you'll need platform teams, security guardrails, and an AI-first mindset, Alvarez said. This should be mature in less than five years.
2. AI Supercomputing Platforms
These are systems built for large-scale AI workloads. They combine accelerators, orchestration, and high-speed infrastructure to help developers create applications in real-time. Paulman said these systems can boost speed, efficiency and cost savings, so they can accelerate innovation and future-proof AI. They suggested that organizations need to identify high-impact compute cases, and that upskilling is just as important. This should be mature in three to five years.
(Credit: Gartner)3. Multiagent Systems
Three of the trends deal with the synthesist. Alvarez talked about having a modular architecture for multiple AI agents handling complex workloads, comparing individual agents to the different members of an F1 racing team. He said we'll first see these work on single platforms, then cross-platform (using MCP or A2A), and maybe later on an "internet of agents." Organizations should start small now with specific agents, according to Alvarez, who cautioned us not to think of them as people, but as tools that work alongside humans. This should be mature in less than three years.
4. Domain-Specific Language Models
Rather than general-purpose large language models (LLMs), Paulman talked about the advantages of domain-specific language models (DSLMs) that are specifically focused on the tasks you need to do, such as clinical studies in healthcare. They noted that there were 50,000 such studies done in the past year, and it would take 350 people all year to read them. A DSLM could search through them quickly giving, yielding better results.
"CIOs are sitting on a value goal mine," Paulman said, because you have the ability to build DSLMs as a digital service. The important thing, they said, is to be transparent about what the model does and doesn't know. This will require a context engineer to ensure the data up to data and a machine learning specialist who monitors for catastrophic forgetting. This should be mature in 3-5 years.
(Credit: Michael J. Miller)5. Physical AI
More AI will be designed to interact with the physical world, Alvarez said, including robots, drones, and smart devices. Such devices will deal with unpredictability, so they need to learn, which could be a complex process. This will require one to five years to reach maturity, depending on the type of object.
6. Preemptive Cybersecurity
The last three trends deal with the vanguard, which tries to keep you ahead of the curve. This includes AI-powered security operations (SecOps), which are predictive and preemptive, rather than most of today's reactive tools. Paulman described this as being like Tom Cruise in Minority Report, and suggested organizations pilot this mindset against the most critical systems and digital assets. Overall, Gartner predicts that by 2030, preemptive cyber security will make up 50% of the security vendor spend. This will require two to five years to reach maturity.
7. Digital Provenance
Alvarez described visiting New York and seeing street vendors hawking knock-off watches and wondering how we know assets are real. In an era where we rely on third-party providers, digital confidence is more important than ever, even as more nation-state hackers are creating digital assets. To solve this, he talked about the need to authenticate where things are coming from using bills of materials, attestation, and digital rights management. This will require less than a year to reach maturity.
8. Geopatriation
Geopatration, the intentional movement of applications and data to sovereign alternatives, is empowering organizations to explore a spectrum of local and global Solutions that allow them to address regulations, compliance, and resilience. In other words, many organizations may have to move their applications or their data to meet local requirements. Paulman said some cloud vendors will offer broad global coverage while others will focus on the specific needs of a single nation. They said that this will make local hyperscalers more economically viable. But this means being more intentional about choosing where your AI lives and who is protecting it. This will also require less than a year to reach maturity.