AI agents will become the primary way we interact with computers in the future. They will be able to understand our needs and preferences and proactively help us with tasks and decision making.Satya Nadella, CEO of Microsoft
Agentic Shift
Agentic AI is emerging as the bridge across this divide.
An Overview
Agentic AI represents far more than just an evolution of generative AI. It marks a fundamental shift in how organisations are designed, how work is carried out and how objectives are achieved.
This transformation is already happening. Gartner forecasts that by 2025, 70% of organisations will have operationalised AI built for autonomy. For businesses, Agentic AI in 2025 is no longer merely about automating individual tasks; it is about empowering systems to independently manage and optimise entire business functions.
Where BPM, RPA, traditional ML and generative AI introduced gradual improvements, Agentic AI establishes the foundation for organisations that are networked and self-directed. It goes beyond brute force computing towards systems capable of adaptation, collaboration and independent reasoning. In that sense, they resemble high-performing teams.
What is Agentic AI?
Agentic AI refers to artificial intelligence systems that operate with significant autonomy—taking initiative, making decisions and pursuing objectives with minimal human intervention. Unlike traditional AI, which primarily reacts to commands or processes data, Agentic AI actively engages its environment.
These systems rely on large language models (LLMs) and agent frameworks that enable real-time reasoning, planning and adaptation. Rather than passive tools, they act as proactive collaborators, shifting AI’s role from reactive assistant to autonomous partner.
Key characteristics include:
- Autonomy – Functions independently within set parameters.
- Goal-oriented behaviour – Strategically works towards defined outcomes.
- Contextual decision-making – Makes intelligent decisions based on real-time data and feedback.
Agentic AI marks a leap forward from simple process automation to intelligent autonomy, enabling systems that do more than follow instructions—they shape outcomes.
| Feature | Intelligent Automation | Agentic AI |
|---|---|---|
| Core Technologies | RPA, ML, rule-based systems | LLMs, agent frameworks |
| Decision-making | Predefined rules | Dynamic, contextual |
| Learning | Static or supervised | Continuous, adaptive |
| Initiative | Waits for input | Self-initiates actions |
While intelligent automation streamlines tasks using structured inputs, Agentic AI understands context, reasons through multiple steps and acts independently without prompts.
Use Case: Parloa is a leading platform allowing enterprises to deploy millions of autonomous AI agents for customer support and communication. These agents do more than respond—they act independently, solve problems and optimise customer interactions in real time.
Why It’s Transformative for Enterprises?
Agentic AI changes how enterprises operate by embedding intelligent autonomy into workflows. It boosts efficiency, reduces reliance on manual effort and expedites digital transformation.
Benefits include:
- Operational efficiency: Tasks start and finish without waiting for human input.
- Increase Employee productivity: Staff are freed from repetitive tasks, focusing on strategic priorities.
- Faster time-to-value: Transformation projects deliver results more quickly.
Real-World Scenario:
ADROSONIC has implemented Agentic AI to automate HR onboarding. Their AI agents manage form filling, access provisioning, system explanations and progress tracking. This approach has significantly reduced onboarding time and improved employee experience.
Functions such as procurement, compliance, knowledge management and customer operations stand to gain significantly from this shift.
Readiness for Implementation
To successfully adopt Agentic AI, organisations need strong foundations:
- Robust data architecture: Clean, accessible, secure data.
- Digital workflows: Well defined processes.
- AI governance: Ethical and operational oversight.
- System integration: ERP, CRM and cloud platform compatibility.
- Cross-functional taskforce: Collaboration between IT, operations and business units.
Strategic and Ethical Considerations
Agentic AI requires careful change management. Trust and transparency in AI-driven decisions are critical. Enterprises must ensure:
- Explainability: Decisions are comprehensible.
- Human oversight: Autonomy balanced with accountability.
- Ethical use: Built-in fairness, bias mitigation and compliance.
Strategic planning should align technological capability with organisational values.
From Assistants to Autonomous Agents
Agentic AI is not merely an upgrade—it is a fundamental shift. Enterprises that adopt it will unlock new levels of agility, intelligence and value. In today’s fast-moving market, where every decision counts, Agentic AI positions organisations to pivot quickly towards a smarter, more autonomous future.
