Agentic AI: The Next Evolution of Artificial Intelligence

07.05.2025

Topic: AI and Machine Learning

Artificial Intelligence (AI) has made remarkable progress in recent years, especially through generative AI (GenAI), which can create content and respond to prompts. But a new shift is on the horizon: Agentic AI. This emerging technology is elevating AI to a whole new level—enabling systems not just to respond to instructions, but to make independent decisions, create plans, and execute actions.

So what exactly is Agentic AI, and how does it differ from traditional AI approaches?

What is Agentic AI?

Agentic AI refers to AI systems that act autonomously and are capable of pursuing goals independently. Unlike conventional AI systems that rely on direct inputs and perform predefined tasks, agentic systems introduce a new dimension of autonomy. They can analyze data, detect patterns, develop strategies, and implement them—often with little or no human supervision.

Core characteristics of Agentic AI include:

• Autonomy: The AI makes decisions independently and carries them out on its own.
• Adaptability: It can dynamically adjust to new conditions and learn from experience.
• Goal-orientation: It follows specific objectives and modifies its strategies accordingly.
• Environmental interaction: It can not only process data but also trigger physical and digital actions.

How is Agentic AI different from existing AI models?

Traditional AI technologies generally fall into two categories:

1. Rule-based systems & Robotic Process Automation (RPA): These operate based on fixed rules and cannot make independent decisions.
2. Generative AI & Large Language Models: These analyze input and generate output based on it, but only respond reactively to specific commands.

Agentic AI goes a step further—it doesn't just process instructions, it acts proactively. For example, while a standard AI might generate an email from a template, an agentic AI would recognize the need to send an email, write it, determine the best time to send it, and track the recipient’s response to follow up if needed.

Use Cases in Invoice Processing and Accounts Payable

Accounting is one of the key business functions poised to benefit significantly from Agentic AI. In particular, accounts payable (AP) and invoice processing stand to gain major automation boosts.

Potential applications include:

• Automated invoice processing: Agentic AI can recognize invoices in various formats, extract relevant data, match it to purchase orders and contract details, and independently approve payments—or trigger escalation workflows in case of discrepancies.
• Invoice prioritization: By analyzing due dates, early payment discounts, and supplier history, the AI can determine which invoices should be processed first to maximize financial benefits.
• Error management and fraud detection: Agentic AI can identify recurring issues in invoices and act accordingly—such as blocking error-prone suppliers or automatically requesting corrections.
• Dynamic cash flow planning: Drawing from historical data, current payment terms, and projected revenues, the AI can optimize liquidity planning by recommending the most strategic payment timing.
• Integration with financial systems: Agentic AI can independently interface with ERP systems and banking APIs to authorize payments, record transactions, and generate real-time financial reports.

Challenges and Risks

As promising as Agentic AI is, it comes with its own set of challenges:

• Governance & Ethics: How can we ensure autonomous AI acts responsibly?
• Security risks: How do we prevent misuse or faulty decision-making?
• Adoption & Trust: How can companies and employees build trust in Agentic AI?

To address these issues, clear regulations, transparent algorithms, strong security protocols, and employee engagement are critical.

Looking Ahead

Leading analysts predict that by 2028, one-third of all enterprise software will incorporate Agentic AI, and at least 15% of everyday business decisions will be made autonomously by AI. In finance and accounting especially, many manual tasks are expected to be largely automated. This evolution won’t just drive productivity—it will also pave the way for new business models and markets.

Organizations that embrace Agentic AI early stand to gain a significant competitive edge. The technology is on track to become a standard component of modern enterprise systems—reshaping how businesses operate, plan, and make decisions.

Agentic AI marks a fundamental shift in the evolution of AI systems. With the ability to act independently, it’s set to transform our relationship with technology. In accounts payable, this means not just processing invoices, but actively contributing to strategic financial planning. The future of AI is autonomous, adaptive, and goal-driven—and it's already beginning.