It is that time of year: a time for predictions about what is going to come in the year ahead. What will 2026 hold? No one can truly answer that question, but some can try. One organization that does every year is Gartner with its strategic technology trends list for the year ahead, which deserves a look each year.
Although as Peggy Smedley has often pointed out on her podcast and in her blog, the analysts don’t always get it right. Still, a look at some of the predictions can give at least a glimpse into what is to come in the year ahead. So, let’s take a few minutes to unpack Gartner’s top strategic technology trends for 2026.
One of the three lenses Gartner uses to group its trends is The Architect—which are technologies that help build secure, scalable, AI-ready foundations.
Trends in this category include:
AI-Native Development Platforms: platforms that embed generative AI into software creation, letting smaller, nimble teams build applications faster.
AI Supercomputing Platforms: combining CPUs, GPUs, AI-ASICs, neuromorphic, and other computing paradigms to handle the most data-intensive workloads.
Confidential Computing: protecting data even while it’s being used, via hardware-based trusted execution environments, which is critical for regulated industries and cross-cloud trust.
Technology investment is no longer just about doing more with less, but rather it’s about doing different. For the companies that move ahead of the curve, the infrastructure choices made now will impact tomorrow. Infrastructure, platforms, and governance are strategic imperatives.
The second cluster—The Synthesist—is about how we apply and integrate intelligence into real-world workflows.
MAS (Multiagent Systems): collections of collaborating AI agents that handle complex business processes, automate at scale, and enable new forms of human-AI teaming.
DSLMs (Domain-Specific Language Models): enterprise-tailored LLMs (large language models) trained for your industry, your processes, your context. Gartner predicts by 2028, more than half of gen-AI models used will be domain-specific.
Physical AI: moving intelligence into the physical world with robots, drones, smart devices, and equipment that sense, decide, and act.
The big takeaway here is we don’t just need more computing power or smarter apps, but rather we need smarter integration. It’s one thing to have an AI model; it’s another thing entirely to orchestrate agents, embed domain-context and make the intelligence part of operations. That’s where real competitive advantage lies.
The final theme—The Sentinel—addresses the often-overlooked dimension of modern tech: trust, risk, governance, and geopolitics, with key trends including:
Preemptive Cybersecurity: shifting from reactive defense to prediction and prevention, often powered by AI to anticipate threats before they strike.
Digital Provenance: verifying the origin, ownership, and integrity of software, data, media, and processes.
AI Security Platforms: platforms focused on guarding AI-specific risks (prompt injection, data leakage, rogue agents) as AI becomes core to business.
Geopatriation: shifting workloads to sovereign clouds, regional providers, or on-premises because of regulatory or geopolitical risk.
Businesses must be able to trust and govern all this technology. With all this in mind, companies must prioritize strategically, invest in training, reskilling, and upskilling, and build the foundation for truly spectacular digital transformation.
Want to tweet about this article? Use hashtags #construction #IoT #sustainability #AI #5G #cloud #edge #futureofwork #infrastructure #predictions