{"id":12915,"date":"2022-01-19T15:53:13","date_gmt":"2022-01-19T15:53:13","guid":{"rendered":"https:\/\/dna325.com\/blog\/?p=12915"},"modified":"2026-01-26T12:49:38","modified_gmt":"2026-01-26T12:49:38","slug":"main-it-trends","status":"publish","type":"post","link":"https:\/\/dna325.com\/blog\/main-it-trends\/","title":{"rendered":"Complete Guide to the Main IT Trends for 2026"},"content":{"rendered":"

The IT industry moves fast, yet the past two years have changed the sector’s trajectory. AI has matured. Cyberattacks increased. Compliance requirements expanded. Remote teams have become the norm for product companies of all sizes. European firms advanced industry standards, while US companies adopted new engineering practices. As a result, 2026 arrives with <\/span>new IT trends<\/span>, which we\u2019ll cover in this guide.<\/span><\/p>\n

\"AI-native<\/p>\n

1. AI-native product development becomes the default<\/b><\/h2>\n

AI-native development reshapes how companies build software. Teams use AI throughout the feature lifecycle: planning, coding, testing, documentation, and quality control. This shift began in 2024, accelerated in 2025, and stabilized as a mainstream practice in 2026.<\/span><\/p>\n

According to the <\/span>2025 GitHub Octoverse report<\/span><\/a>, ~80% of new GitHub users activate GitHub Copilot within their first week, and more than 1.1M public repositories now include an LLM SDK, a 178% year-over-year increase. These patterns align with <\/span>current IT technology trends<\/span> that emphasize automation at scale.<\/span><\/p>\n

AI coding assistants no longer support simple prompts but work inside IDEs, CI pipelines, and documentation platforms. They map legacy code, explain complex components, produce refactoring plans, and track code consistency.<\/span><\/p>\n

This <\/span>IT trend<\/span> matters because companies compete on speed. Teams that adopt AI-native workflows build features faster, improve code quality, and reduce onboarding time. New hires learn the system through AI tools that explain architecture, test cases, and dependencies. Established teams reduce repetitive tasks and focus on strategic work.<\/span><\/p>\n

AI also becomes part of product strategy. Gartner reports that <\/span>40% of enterprise apps will feature task-specific AI agents<\/span><\/a> by 2026. This turns AI from an optional feature into a core requirement. Companies that ignore it lose competitiveness because users expect more innovative interfaces, predictive systems, and automated suggestions.<\/span><\/p>\n

\"Agentic<\/p>\n

2. Agentic automation reshapes engineering and operations<\/b><\/h2>\n

Agentic automation will expand quickly in 2026. This <\/span>trend in IT<\/span> refers to AI agents capable of performing multistep tasks without continuous human oversight.<\/span><\/p>\n

Forrester<\/span><\/a> reports that next year, enterprise software will shift from supporting human workers to working side-by-side with AI agents. Companies will need to decide how much of their processes they want these agents to run autonomously.<\/span><\/p>\n

Agentic tools perform tasks such as:<\/span><\/p>\n