What is Agentic AI?
Agentic AI is a form of artificial intelligence that can act autonomously within a defined scope. AI agents make independent decisions, perform tasks, and learn from their experiences. The term "Agentic" refers to agent-like behavior: virtual employees that take initiative on behalf of an organization.
In practice, this means AI agents can handle a wide range of tasks, from generating reports and answering customer inquiries to updating CRM systems with new order data.
Also read: Generative, Agentic and Predictive AI explained.
From Experimentation...
According to Sander, as of 2025, we are still in the experimental phase of Agentic AI. “Businesses are actively exploring what’s possible,” he explains. “The focus is currently on testing isolated use cases: one department, one process, or a small team experimenting with an AI agent.”
This phase is reminiscent of how organizations initially embraced personalization. “When personalization tools first emerged, marketers started with small adjustments, like product recommendations in emails. Over time, personalization became an integral part of the entire customer journey. The same will happen with Agentic AI: from experiments to structural deployment and, eventually, full integration.”
Companies using AI agents to answer customer inquiries or automate repetitive tasks are already saving time, working more flexibly, and delivering higher-quality service. However, this is still a phase of discovery and learning. “Organizations rolling out their first use cases are already seeing promising results,” says Sander. “But scaling up and entrusting AI with more responsibility still comes with some hesitation. That, too, is just a matter of time,” he continues. “As trust in the technology grows through successful cases, businesses will quickly scale up their use of Agentic AI.”
Toward Structural Adoption...
At the same time, we’re seeing a shift in consumer behavior. Customers increasingly expect seamless, natural communication with businesses—whether through chat, voice, or other interactive interfaces. Structural adoption of Agentic AI is therefore not only essential for optimizing processes or staying competitive but also for meeting these evolving customer expectations.
Once AI agents are deployed on a structural level and interaction through AI becomes a natural part of customer communication, the focus will shift from experimentation to efficiency, scalability, and growth. Businesses taking this step will build on their initial successes and eventually deploy AI agents across multiple departments.
“You can already see companies automating multiple processes simultaneously,” says Tom. “AI agents will soon collaborate with each other, provide consistent support to employees, and improve teamwork across departments. While they currently handle simpler tasks, their roles will become increasingly strategic, expanding to multiple departments or even organization-wide.”
The structural adoption of Agentic AI will have a significant impact on daily business operations, enabling:
Faster decision-making through real-time data processing.
Lower operational costs thanks to automated workflows.
Enhanced customer experiences through instant, personalized interactions.
Higher productivity as employees focus on strategic work.
Toward Full Integration
Over the next five years, we’ll move toward the full integration of Agentic AI. Businesses will be partially run by AI, with humans overseeing, correcting, and optimizing processes. Sander explains: “In the future, we won’t even think about using AI—it will simply be part of our daily work.”
The business impact of full adoption will be profound, influencing every aspect of operations:
Operationally, AI agents will optimize processes in real time.
Strategically, AI agents will make faster, data-driven decisions.
Culturally, roles and required skills for employees will evolve.
Customer interactions will also continue to transform. While we’re currently taking the first steps toward conversational interfaces (systems that allow customers to communicate with businesses in natural language), this will evolve into fully-fledged conversational commerce. Instead of searching through websites or filters, customers will engage in conversations with AI and make purchases within the same digital interaction—just as they would with a store employee, but fully digital, personalized, and automated.
Sander adds: “Businesses will increasingly structure their customer interactions as ongoing conversations, with AI responding in real time to the context and individual needs of consumers.”
HALO: The Foundation for the Next Phase of Agentic AI
HALO, CM.com’s AI platform, serves as the connecting link across all phases of Agentic AI—from experimentation to full integration. While companies like OpenAI and Gemini focus on developing AI models, HALO provides the infrastructure for businesses to build their first AI agents and gradually scale them into comprehensive AI solutions.
Sander explains: “We don’t build models; we build a platform that works with multiple models. This allows customers to choose the AI that best fits their use cases. Some models excel at coding, others at generating text or analyzing data. We help them select the right combination.”
HALO stands out for its:
Security and compliance: HALO meets European standards for data and governance.
Flexibility: The platform supports both customer-facing applications and internal process automation.
Scalability: Organizations can start with a single agent and easily expand to broader applications of Agentic AI.
Tom concludes: “Agentic AI is no longer a distant future. It’s the logical next step for organizations looking to work smarter, more humanly, and more efficiently. And those who start now will build a sustainable competitive advantage.
