AI agents in 2026: predictions and 2025 takeaways
In 2025, AI agents stopped being a research curiosity and took the centre stage. According to Microsoft, the usage of agentic AI has doubled compared to last year. Across industries we saw how pilot projects graduated into production, platforms emerged to stitch agents into business workflows, and enterprise leaders became more open to implementing AI agents.
The first large-scale deployments of AI Agents have already emerged – for example, in retail banking customer service with AI operating on the first line of interaction. In such implementations, AI Agents are now able to handle 70% or more of customer inquiries without involving human operators.
Human-AI collaboration
One to two years ago, banks were hesitant to deploy AI Agents on the first line due to the risk of LLM hallucinations. By 2025, retail banks have begun actively using conversational AI for customer service. AI Agents have moved to the frontline, working with a large share of routine inquiries without compromising quality.
Effective human-AI collaboration still plays a crucial role in enterprises today. First-line AI requires seamless escalation to human agents when needed or upon customer request. Modern AI Agent platforms must therefore support advanced human-AI collaboration.
This includes smooth human takeover of live conversations and AI operation as a real-time co-pilot for human agents.
What can we expect from AI Agents in 2026?
We can outline three concrete predictions on what to expect from AI in an upcoming year:
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From one-off AI agents to continuous AI platforms
Companies that have experimented with building AI Agents will discover that it is not possible to purchase a pre-built AI Agent that universally fits their business needs. Instead, they will have to set up a continuous process to track performance, analyse effectiveness, and iteratively continuously improve their AI Agents. We will observe how organisations increasingly shift their focus from acquiring individual AI agents to adopting platforms that enable and support this continuous improvement lifecycle.
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Context is crucial to AI agent effectiveness
Businesses will learn that an agent’s effectiveness hinges on its ability to understand the customer’s context. That involves tracking previous conversations and understanding the customer’s products, which is essential for delivering personalised service. This is why businesses will increasingly seek solutions that provide these capabilities.
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From isolated agents to orchestrated AI ecosystems
There will be a shift from deploying AI Agents operating individually, typically within a single communication channel, to adopting platforms that support coordinated interaction of multiple AI Agents performing different tasks and engaging with customers across multiple communication channels simultaneously.
2025 was the year AI Agents became real for many businesses, and 2026 will continue this trend. The shift is irreversible, and in 2026 the enterprises that succeed will be the ones who manage to integrate AI in their process most seamlessly and effectively.
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