By 2026, AI is no longer just a standalone tool but a core part of infrastructure, workflows, and digital products. Companies are opting for solutions that are controllable, scalable, and safely integrated. Here’s an overview of the most relevant trends in practical AI adoption for business.
Trend #1: The era of Agentic AI
Businesses are moving beyond passive chatbots to autonomous AI agents that complete tasks independently. These agents not only respond to requests but also make decisions and take action, such as booking services, managing purchases, and auditing operations.
In large, fast-paced environments, a single agent isn’t enough, so multi-agent systems are used — networks of autonomous agents interacting without human input. For example, Siemens employs autonomous procurement agents to monitor suppliers, assess logistical risks, and adjust orders based on current prices and delivery times.
Trend #2: Hyper-personalization
Hyper-personalization uses user behavior analysis to tailor content, offers, and interfaces to individual needs. Websites and apps adjust not just banners and recommendations but also layouts, element visibility, and visual modules based on user type and interactions.
Marketing is increasingly focused on GEO — Generative Experience Optimization. As users turn to AI assistants instead of traditional search engines, businesses need to optimize content for queries and behavior on these platforms, not just for Google or standard SEO.
Trend #3: Industrial AI and Edge AI
AI is increasingly used in manufacturing and logistics. Businesses rely on local models (SLMs) running on their own servers or devices, enabling faster data processing and stronger security as sensitive information stays within the enterprise.
At the same time, spatial AI is driving robotization in factories and warehouses. Cameras and sensors map the environment, helping robots navigate, avoid obstacles, and work autonomously. Examples include Amazon, Ocado Technology, and ABB Robotics.
Trend #4: Multimodality by default
Multimodal AI systems are becoming standard, processing text, images, audio, and video in real time. With “invisible” interfaces, they respond to gestures, facial expressions, tone, and visual context without buttons or menus.
By combining multiple data formats, AI can adapt UI/UX to user behavior and automate information processing, integrating text, audio, and video for faster analysis and pattern recognition.
Trend #5: Energy efficiency and Green AI
Large AI models consume significant energy, so providers’ environmental impact is now a key consideration. Businesses choose systems trained on renewable energy or more compact solutions that use far fewer resources.
Three main approaches to green AI are commonly used:
🟢 Green-in AI — optimizing models and algorithms to cut energy use during training and inference;
🟢 Green-by AI — applying AI to reduce energy use and optimize resources in other sectors;
🟢 Green AI — a broader approach covering eco-friendly training, energy-efficient hardware, and minimizing carbon footprint across the model lifecycle.
AI now touches every aspect of business, from automating routine tasks and personalizing the customer experience to managing energy. Companies are embracing autonomous agents, multimodal systems, and energy-efficient solutions.
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