Barcelona / Madrid. — During its IT Symposium/Xpo 2025, Gartner unveiled the 10 strategic technology trends for 2026 that, in their view, will shape the next wave of digital disruption. The message for CIOs and IT leaders is clear: the pace of innovation accelerates, AI becomes systemic, and risk management — from agent security to data sovereignty — shifts into a core design element, not just an add-on.
“2026 will be a pivotal year,” Gartner anticipates: organizations acting now will not only withstand volatility but shape their sectors for years to come.
Below are the 10 key trends and why they matter.
1) AI Super Computing Platform: the model factory as the new “industrial plant”
Platforms combining CPU, GPU, AI ASICs, neuromorphic chips, and software orchestration to perform training, simulation, and analytics at scale. Gartner predicts that > 40% of major enterprises will adopt hybrid paradigm architectures in critical workflows by 2028 (today: 8%). It involves shifting from “buying power” to d designing in-house or sovereign AI factories, optimized for cost, energy, and latency.
Operational signal: govern capex/opex (energy, HBM, cooling) and time-to-model as KPIs for business success.
2) Multi-Agent Systems (MAS): AI’s teamwork in action
Sets of specialized agents that collaborate on complex goals, reusing proven solutions and scaling modularly. Gartner sees this as the practical way to automate processes, accelerate deliveries, and reduce risk. The key will be choreography (who does what and when) and controls to prevent “rogue actions” by agents.
Operational signal: define contracts between agents (inputs/outputs, boundaries) and ensure full end-to-end observability.
3) DSLMs (Domain-Specific Language Models): context over size
Domain-specific models — trained or fine-tuned with sector-specific/process data — outperform generic LLMs in accuracy, cost, and compliance. By 2028, over half of enterprise GenAI models will be DSLMs.
Operational signal: align truth sources (ERP, EHR, core banking, regulatory repositories) and guide RAG and fine-tuning with data traceability.
4) AI Security Platforms: the new layer of app and agent defense
Platforms that unify visibility, policies, and guards against AI-specific risks: prompt-injection, leaks, misused tools, or misaligned agents. Gartner expects that by 2028 more than 50% of companies will deploy such platforms.
Operational signal: integrate AppSec/DevSecOps with AISecOps, shifting from “best effort” controls to blocking controls in production.
5) AI-Native Development Platforms: small teams, big results
Platforms designed natively for AI that enable tiny teams (business-deployed engineers + functional experts) to build more software with built-in security guards and governance. By 2030, 80% of organizations will have transitioned from large engineering teams to agile cells augmented by AI.
Operational signal: productize templates, patterns, and scaffolds with security controls by default.
6) Confidential Computing: protecting “in use”
Isolate workloads in TEEs (Trusted Execution Environments) to keep data private during use, even from infrastructure owners. Critical for regulated industries, consortia, and inter-competitor collaborations. By 2029, over 75% of operations on “untrusted” infrastructure will be protected in use.
Operational signal: prioritize TEE for sensitive workflows, multi-country contracts, and collaborative work.
7) Physical AI: AI moves beyond the screen
Robots, drones, and devices that sense–decide–act safely and adaptively. Requires mixed IT/OT/engineering profiles, cultural shifts, and work management plans. Benefits include improvements in productivity, quality, and safety in manufacturing, logistics, energy, or healthcare.
Operational signal: pilot with digital twins, Synthetic Data, and safety-by-design validation.
8) Preemptive Cybersecurity: from reactive to preventative
Security spending shifting toward predictive capabilities, programmatic denial, and deception by 2029–2030, with IA in SecOps to enable “prediction = protection”.
Operational signal: map kill chains by sector, automate dissuasion/decoy, and evaluate MTTD/MTTR enhanced by AI.
9) Digital Provenance: verifiable origin, authorship, and integrity
With more third-party software, open source, and AI-generated content, digital provenance becomes vital. Tools like SBOMs, attestation registries, and watermarks will enable tracing assets throughout the supply chain. Those who don’t invest could face multimillion-dollar sanctions by 2029.
Operational signal: require SBOM and signatures in procurement, and deploy watermarks/verifiable metadata in content.
10) Geopatriation: sovereignty and geopolitical risk drive decisions
Relocate data and applications from global clouds to sovereign/regional options or private data centers due to geopolitical risk and compliance. By 2030, over 75% of companies in Europe and the Middle East will have “geopatriated” their workloads to lower-risk solutions, up from less than 5% today.
Operational signal: maintain a catalog of sovereign workloads, regional cloud policies, and selective repatriation plans that do not hinder innovation.
What it means for CIOs and practical advice (2025–2026)
1) Design your “AI factory” as a product.
Define core capabilities (computing, data, MLOps, security), SLOs, and funding; incorporate energy measurement and liquid designs if aiming for high densities.
2) Transition from copilots to multi-agent systems.
Start with narrow use cases (finance, healthcare, logistics), set hard limits on tools, and audit actions and decisions.
3) Prioritize DSLMs and RAG with trusted sources.
Precision and compliance outweigh “creative surprise” in core processes. Invest in data curation and lineage.
4) Put security at the forefront of AI.
Implement an AI security platform covering app-level, models, and agents, with telemetry and blocking responses.
5) Anticipate sovereignty and workload mobility.
Build on portable abstractions (containers, Kubernetes, decoupled data), and evaluate confidential computing and encryption at all phases.
6) Prepare your organization for Physical AI.
Develop IT/OT profiles, test with digital twins and Synthetic Data, and establish policies for functional security and ethics.
In a nutshell
The 2026 trends Gartner highlights are not shopping lists; they are operational patterns for an economy driven by AI factories, specialized agents, and data sovereignty, where security, provenance, and energy efficiency take center stage.
Source: Gartner, Top Strategic Technology Trends for 2026 (presented at Gartner IT Symposium/Xpo 2025).