Agentic AI - What It Means and Why It Matters Now

Violet Durand | 23 May 2025

The AI landscape is shifting. While generative AI has captured attention with tools like ChatGPT that produce text, code, and images on demand, a new paradigm is emerging: agentic AI. Unlike generative models that respond to prompts, agentic AI systems take initiative, make decisions, pursue goals, and execute complex workflows with minimal human input. This is a change that’s beginning to reshape how work is organized and how businesses operate.

What Is Agentic AI

Agentic AI refers to systems capable of independent reasoning, planning, and action to achieve predefined goals. These agents integrate large language models (LLMs), machine learning, and traditional programming to navigate dynamic environments, adapt to new data, and interact with external tools like APIs or IoT devices.

Key Characteristics:

  1. Autonomy: Operates without constant human input (e.g., self driving cars adjusting routes in real-time)
  2. Proactive Problem Solving: Breaks tasks into subtasks, delegates to specialized tools, and iterates based on feedback
  3. Contextual Awareness: Turns agents from rule-based executors into adaptive problem-solvers. They can anticipate needs, self-optimize (e.g., rerouting workflows around bottlenecks) or personalize interactions (e.g., tailoring software UX based on a user’s role).
  4. Multi-Agent Collaboration: Agentic systems often involve multiple agents working together; sharing information, delegating tasks, and resolving conflicts.

Why Agentic AI Matters Now

Agentic AI matters now because traditional automation can’t keep up with the complexity of today’s business challenges. Unlike traditional systems that follow predefined rules, agentic AI systems can understand goals, make decisions, and adapt their actions based on context. This shift unlocks entirely new possibilities for productivity. As businesses face increasing pressure to reduce operational costs, agentic AI provides a practical way to do so.

Human-AI Collaboration in Agentic Systems

In agentic systems, AI isn’t just working alongside humans, it’s working with them. For example, in Orpius, both AI agents and human users are treated as first-class participants. Tasks are dynamically delegated to either AI agents or human team members, depending on who is best suited for the job. The system is location-aware, taking into account time zones, availability, and context to ensure the right task goes to the right actor at the right time. It creates a flexible system where responsibilities shift dynamically based on context, not rigid rules.

Challenges and Risks

While the potential of agentic AI is substantial, it also introduces important challenges:

  • Trust and Oversight: Delegating decisions to agents raises issues of accountability and transparency. Systems must be built with oversight, explainability, and traceability at their core.

  • Safety and Misalignment: Agents can take unintended actions if goals are vague or the environment shifts in unexpected ways.

  • Integration Complexity: Incorporating autonomous agents into existing systems often requires major architectural changes and careful governance.

  • Human Readiness: The success of agentic AI depends not just on the technology, but on whether people and organizations are prepared to work alongside autonomous systems.

Addressing these challenges is essential to realizing the benefits of agentic AI without introducing new risks.

The Future of Agentic AI

The agentic paradigm is still in its early stages, but its trajectory is clear. As systems become more capable, interconnected, and context-aware, agentic AI will:

  • Become a core layer in digital infrastructure, powering decision-making, action, and adaptation across all parts of an organization.

  • Enable new forms of human-machine collaboration that scale insight and impact.

  • Serve as a foundation for intelligent ecosystems where agents, humans, and systems interact dynamically in real time.

Forward looking organizations are already laying the groundwork. The future will belong to those who embrace the shift early.

What We Are Doing with Orpius

We’re building Orpius for the agentic era. Our system doesn’t just support agentic workflows, it runs them. Orpius lets you define goals, then coordinates both AI and human participants to carry out multi-step, event-driven operations. It combines a multi-agent infrastructure with a built-in application layer, enabling complex processes to run out of the box. We’ve also opened up the system so developers can integrate advanced AI capabilities into new or existing applications quickly and with minimal code.

If you’re exploring how agentic AI could reshape your business, we invite you to join our pilot program. Let’s build what’s next together.