AI Agents in 2026 – When AI Shifts from Assistant to Actor
If 2023 was the year of generative AI chatbots, 2024 was the era of "copilots," and 2025 was the breakthrough year for AI agents, 2026 is the year of agentic AI maturation. Organizations are moving from experimentation to production, and AI agents are becoming visible in an increasing number of work processes.
A traditional AI assistant – like ChatGPT or Claude in conversation mode – responds to user requests and produces answers. It's like a consultant you ask for advice. An AI agent, however, is a more autonomous actor: you can give it a goal, and it plans and executes the necessary steps to get there. It doesn't just advise – it acts.
What Are AI Agents in Practice?
An AI agent is an artificial intelligence system capable of autonomous reasoning, planning, and action. Unlike traditional chatbots that answer individual questions, or RPA (Robotic Process Automation) that follows rigid rules, AI agents can adapt to changing conditions, handle exceptions, and make intelligent decisions.
In practice, this means you can give an AI agent a multi-step task, and it will:
- Analyze the task and break it into components
- Plan the sequence of actions
- Use tools – such as software, APIs, and databases
- Execute the steps autonomously
- Verify results and correct errors
Concrete Examples
Customer Service
A traditional chatbot answers frequently asked questions and directs more complex cases to humans. An AI agent, however, can handle the entire customer service process: research the customer's history, analyze the problem, find a solution in the knowledge base, make necessary changes in the system, and communicate with the customer – all without human intervention.
Financial Administration
Financial AI agents can manage complete processes: receive an invoice, verify its details against contracts, record it in the accounting system, schedule payment, and update reports. The human's task becomes handling exceptions and strategic decision-making.
Software Development
Advanced coding agents can already receive a product requirement, break it down into technical tasks, write the code, run tests, fix bugs, and even deploy the application – all with minimal human oversight. The developer's role shifts from doer to reviewer and strategist.
Where Are We Now?
According to McKinsey's 2025 research, nearly nine out of ten companies are already using AI regularly. At the start of 2026, the situation has progressed significantly: more and more organizations have moved from the experimentation phase to actual production use. Gartner predicts that by the end of 2026, 40 percent of enterprise software will include task-specific AI agents.
In 2025, about 62 percent of organizations were experimenting with AI agents, but only 23 percent were scaling them more broadly. Now in early 2026, we're seeing a clear shift: early adopters' experiences have matured the market, and more organizations are taking steps toward broader adoption. In the best-case scenario, agent-based AI could account for up to 30 percent of enterprise software revenue by 2035.
Challenges and Concerns
Deploying AI agents is not without problems. Key challenges include:
- Trust and control: How to ensure the agent acts as expected? How to reverse erroneous actions?
- Security: An autonomously operating system can make mistakes with significant consequences
- Liability issues: Who is responsible when an AI agent makes an incorrect decision?
- Integration: Many organizations aren't ready yet – legacy systems and lack of APIs slow down adoption
According to Gartner's earlier survey, only 15 percent of IT leaders were considering, piloting, or deploying fully autonomous AI agents. In 2026, this number is growing, but caution remains justified – and that's sensible.
The Human Role Remains Central
While AI agents can automate entire processes, the human role doesn't disappear – it changes. In the future, people will act more as supervisors, strategists, and quality controllers than executors. Critical decisions, creative thinking, and ethical evaluations remain human responsibilities.
The most successful organizations understand that AI agents aren't replacements for humans but tools that free up time for more valuable work. The key is finding the right balance between automation and human oversight.
How to Prepare?
If you want to leverage AI agents in your own work or organization, consider starting with the following:
- Identify suitable processes: Which repetitive, time-consuming tasks could benefit from automation?
- Ensure data and API readiness: AI agents need access to systems and data to function
- Start small: Experiment with one process, measure results, and expand gradually
- Build oversight mechanisms: Define clear boundaries and ensure humans can intervene when necessary
Conclusion
The year 2026 is the time of AI agent maturation. While 2025 was the year of breakthroughs and experimentation, we now see the technology becoming part of everyday work processes. AI agents represent a transition from assistive AI to active AI – systems that don't just advise but act.
At the same time, we must remember that technology is a means, not an end. At their best, AI agents free people from routine work to focus on what human creativity, empathy, and judgment are irreplaceable for. The future isn't human versus machine – it's human and machine together.