Agentic AI tools are already transforming the way teams work, enabling systems that can plan, make decisions, and act with minimal human input. As a complement to traditional automation, they’re built to adapt - monitoring context, adjusting strategy, and following through on goals.

According to Bain & Company, 95% of U.S. companies are using generative AI, with production use cases doubling in the past year. As more teams move from testing to real-world deployment, agentic AI is becoming essential infrastructure. At Make we're working hard to equip our customers with the right tools to capitalize on the rise of agentic automation. That's why we launched no-code AI Tools, AI Assistant, and Make AI Agents.

What are agentic AI tools?

Agentic AI tools are digital systems that can determine the next step without being explicitly instructed at every step.

They’re designed to work toward a goal, make decisions along the way, and adjust based on what’s happening - like a smart assistant that doesn’t just follow instructions, but understands the bigger picture and moves things forward on its own. This adaptability ensures that the system can respond to changing circumstances, providing reassurance in your investment.

Key characteristics of agentic AI tools:

• Goal-oriented - They pursue outcomes, not just outputs.

• Context-aware - They adapt based on changing inputs or states.

• Autonomous - Once deployed, they can operate without constant human oversight.

• Self-refining - Some tools include feedback loops to improve performance over time.

These tools often run on top of agentic frameworks, which provide the architecture, planning logic, and environment needed for these agents to function. An agentic framework is like the 'rules of the game' for the agentic AI tool. It sets the boundaries, tools, and strategies for the tool to operate effectively. While the framework provides the 'rules of the game,' the agentic AI tool is the player, moving forward, making decisions, and learning as it goes.