Gartner has identified 10 strategic technology trends for 2027, highlighting the need for enterprises to strengthen AI governance, manage machine identities, improve security remediation and reduce dependence on critical technology providers as AI adoption accelerates.
The trends span AI models, software development, cybersecurity, data infrastructure and emerging computing architectures. Gartner said organisations must move beyond passively observing AI capabilities towards actively defining the boundaries between people, machines and organisational processes.
“The critical friction today is that AI systems operate in an architectural vacuum, generating software faster than humans can review it, creating unmanaged credential paths and binding processes to single-source vendor monopolies,” said Gene Alvarez, distinguished vice-president analyst at Gartner. He called for organisations to take a more active role in designing organisational, human and machine boundaries.
The 10 trends identified by Gartner are large quantitative models, speech reasoning models, world models, AI context platforms, agent coding harnesses, AI agent identity, autonomous exposure remediation, sovereign technology, disposable applications and software as a service.
AI models and context move into focus.
Large quantitative models (LQMs) are designed to process and analyse quantitative data using modular, hybrid neural network architectures. Gartner said these models could help enterprises move beyond the probabilistic outputs of general-purpose language models for numerical tasks, supporting applications such as autonomous forecasting in regulated sectors, including finance and healthcare.
Speech reasoning models are voice AI systems that reason directly from audio, tracking context and intent throughout a conversation to determine appropriate responses or actions. Gartner sees these models as a way to improve the automation of complex customer interactions, where conventional customer service automation has struggled to meet enterprise expectations for accuracy, speed and resolution.
World models use representations of physical environments to help machines understand space, time and causality. They allow autonomous agents to simulate possible future states and assess the consequences of actions before execution. Gartner identified robotics, autonomous vehicles and spatial computing as areas driving development in this field.
Another trend, AI context platforms, focuses on providing AI agents with the contextual knowledge needed to interpret information, make decisions and act in accordance with business objectives.
Gartner predicts that by 2027, organisations prioritising semantics in AI-ready data will increase agentic AI accuracy by up to 80% and reduce costs by up to 60%. It also warned that inadequate context can contribute to overprivileged agents, compliance failures, reduced trust and excessive token consumption.
Securing AI agents and software development
As enterprises deploy AI agents across business workflows, identity and access management are becoming more important. Gartner’s AI agent identity trend focuses on establishing accountability for agents that act independently or on behalf of multiple users.
Gartner predicts that by 2028, 25% of enterprise security breaches will be attributable to AI agent abuse stemming from unmanaged machine privileges and legacy credential practices.
Dynamic identity controls could help organisations replace static credentials with access governed by policies and granted when required. The approach links models, prompts, credentials and agent actions to strengthen accountability.
In software development, an agent coding harness is designed to govern autonomous coding agents across the software development lifecycle. The closed-loop control system aims to reduce the need for developers to manually verify machine-generated output while maintaining oversight of autonomous development activity.
Autonomous exposure remediation (AER) is another security-focused trend. It combines AI and automation to identify, prioritise and address vulnerabilities across an enterprise’s digital estate, including automatically testing and deploying patches or virtual patches into production environments.
Sovereignty and changing software models
Gartner’s sovereign technology trend addresses the risks associated with dependence on critical technology providers. Sovereign technology, or SovTech, encompasses hardware, software, databases and AI models designed to provide viable exit options from providers and support operational continuity.
Gartner predicts that by 2030, more than 75% of organisations based outside the United States will adopt digital sovereignty strategies, shifting critical workloads to reduce geopolitical and vendor lock-in risks.
Meanwhile, disposable applications are purpose-built software applications designed to be retired once their specific business purpose has been fulfilled or they are no longer relevant. The model could change how organisations procure, develop and budget for software, shifting application portfolios away from long-term investments towards more dynamic systems.
The tenth trend, Wetware as a Service, describes an emerging model that provides remote, cloud-based access to living or synthetic biological systems for computation. Gartner presents it as a potential alternative computing approach amid concerns about the environmental and energy demands of scaling conventional silicon-based infrastructure for enterprise AI.
Implications for enterprise technology leaders
The trends highlight a broader shift in enterprise technology planning, with AI adoption bringing new requirements for data quality, identity controls, software governance and operational resilience. They also point to growing attention on the ability to move workloads between providers and to assess emerging computing models.
For CIOs and technology leaders, the challenge will be to distinguish technologies that address immediate operational and security needs from those that remain at an early stage of development. Gartner said the trends are expected to drive significant disruption and opportunity for CIOs, IT leaders and technology providers over the next five years.