Artificial Intelligence trends to watch in 2026

Analysts at Gartner, Forrester, and IDC have described 2026 as the year of Agentic AI, where systems stop just answering questions and start executing complex workflows autonomously.

The most significant trend is the transition from chatbots to AI Agents. Unlike current LLMs, these agents can reason, plan multi-step tasks, and use software tools independently to achieve a goal.

Cisco and Microsoft predict 2026 will be the era of ‘Connected Intelligence’, where humans supervise agents rather than running the software themselves.

Gartner’s 2026 Strategic Trends highlights Multiagent Systems as a top priority. Google’s 2026 AI Business Report reveals how agents will handle routine tasks, saving employees roughly 40 minutes per interaction.

Gartner predicts a 25 percent drop in traditional search volume by 2026. This is giving rise to ‘Generative Engine Optimisation’ (GEO), where brands fight to be the source cited inside an AI’s answer.

Global AI spending is forecasted to exceed $300 billion in 2026. However, Forrester warns of ‘CX fatigue’ and a pragmatic reset where companies stop chasing every shiny tool.

Generative AI is expected to evolve beyond text. In 2026, analysts expect rapid growth in AI-generated video, audio and 3D content, transforming marketing, entertainment and digital media.

Companies are also turning to synthetic data generated by AI to train models more safely and efficiently, especially in regulated industries.

In Europe, the enforcement of the EU AI Act is expected to influence global standards, while companies worldwide prepare for stricter requirements on labelling AI-generated content and documenting model behaviour.

Read also: What’s next in AI: 7 trends to watch in 2026

Here are some key artificial intelligence trends expected to shape 2026. These trends are based on expert forecasts and emerging developments.

Agentic and Autonomous AI

Autonomous agents will manage workflows, make real-time decisions, and interact with software and services without constant human supervision.

These are AI systems that don’t just respond to prompts but plan, act, and complete tasks on their own.

AI embedded everywhere

AI will be deeply integrated across devices and environments. They are built directly into smartphones, browsers, cars, wearables, and household devices.

Edge AI are models running locally on devices for real-time responses, privacy, and offline use, and these advancements will make AI more responsive and personal.

Contextual, memory-driven AI

AI models will increasingly retain and utilise long-term context, remembering past interactions to deliver more personalised, coherent, and useful responses over time.

Generative AI matures

Generative AI will go beyond text to include video, audio, and immersive content, which will transform entertainment, marketing, and learning.

Regulation and trust-focused AI

Artificial Intelligence’s growing capabilities will make governance, transparency, and safety important to build public trust and reduce harms from misuse or bias.

There can be documentation of model behaviour, clear labelling of AI-generated content, privacy safeguards and compliance standards such as the EU AI Act becoming enforceable by mid-2026.

Read also: Managing the generational gap at work using artificial intelligence (AI) 

AI, Quantum and Advanced Infrastructure

Hybrid AI and quantum computing workflows are moving from labs into real-world use, especially for optimisation and scientific simulation tasks.

AI infrastructure will also shift toward efficiency, sustainability, and custom silicon, which makes powerful AI accessible without excessive energy demand.

AI in Cybersecurity

Artificial Intelligence threat hunting and automated incident response will become standard as AI will be a double-edged sword in security.

Attackers will use AI to craft highly targeted, adaptive attacks, while defenders will use AI to detect and respond to threats faster

Workforce Augmentation and Skill Shifts

AI will augment human work by creating new roles and emphasising skills such as prompt engineering, workflow design and AI oversight rather than simply replacing jobs.