What Is Agentic AI & Is It The Next Big Thing?

We’ve had Blockchain, we’ve had RPA, we’ve had Generative AI, but the next big thing appears to be “Agentic AI.” But is it a flash in the pan or worth spending time to understand? We spoke to Hendrik Leitner, partnerships and alliances director at autonomous finance experts Hypatos, to understand how Agentic AI differs from Gen AI, and how it can be applied in finance and shared services. 

What is Agentic AI?

Agentic AI refers to a class of artificial intelligence systems designed to act as autonomous agents, capable of performing tasks, making decisions, and interacting with their environments without requiring direct human intervention. Unlike traditional AI models that follow predefined rules or Generative AI that focuses on creating new content, Agentic AI emphasizes goal-oriented behavior and adaptive decision-making. These systems leverage advanced algorithms and sensory inputs to execute actions in real-time, often learning and optimizing their performance through continuous feedback. Applications of Agentic AI are diverse, spanning from robotics and autonomous vehicles to intelligent personal assistants and complex simulation environments, where they can independently manage tasks, respond to dynamic conditions, and achieve specified objectives efficiently and effectively.

How does it differ from Generative AI?

Agentic AI and Generative AI represent distinct paradigms within the field of artificial intelligence, each with unique functionalities and applications. Agentic AI focuses on creating autonomous agents that can perform tasks, make decisions, and interact with their environments independently, emphasizing goal-oriented behavior and adaptive responses. These systems are designed to carry out actions and solve problems without constant human oversight, making them ideal for applications like robotics, autonomous vehicles, and intelligent personal assistants. In contrast, Generative AI is centered on the creation of new content, such as text, images, or music, by learning patterns from existing data. It excels in producing creative outputs that mimic or innovate upon the examples it was trained on, evident in technologies like language models, art generation tools, and synthetic media creation. While Agentic AI is characterized by its decision-making and action-taking capabilities, Generative AI is distinguished by its ability to generate original content based on learned patterns.

How might finance and shared services use it in the future?

In the future, finance and shared services could harness the power of Agentic AI to revolutionize their operations through enhanced efficiency and intelligent decision-making. In finance, Agentic AI could autonomously manage investment portfolios, execute trades based on real-time market analysis, and identify fraud by continuously monitoring transactions and flagging anomalies. Shared services, such as human resources and customer support, could benefit from Agentic AI through the automation of routine tasks like payroll processing, invoice management, and employee onboarding. These AI agents could interact with various systems, learn from vast datasets, and adapt to changing business needs, providing timely responses and personalized solutions. By integrating Agentic AI, finance and shared services would not only streamline their workflows and reduce operational costs but also improve accuracy and responsiveness, ultimately enhancing overall service quality and client satisfaction.

Points for Consideration:

Advisory companies and Big 4 firms are poised to play pivotal roles in evaluating the transformative potential of Agentic AI in finance and shared services. Leveraging their expertise in finance, technology, and regulatory compliance, these firms will conduct rigorous assessments to gauge the benefits and risks of adopting Agentic AI.

Unlike Robotic Process Automation (RPA) and AI agents, which focus on automating specific tasks or providing rule-based decision support, Agentic AI represents a significant advancement. It operates autonomously, making complex decisions and taking actions based on continuous learning and analysis of vast datasets. This capability not only enhances operational efficiency and accuracy but also empowers organizations to navigate regulatory complexities and mitigate risks more effectively.

As Agentic AI evolves, collaboration with diverse stakeholders—from technology vendors and regulatory bodies to cybersecurity experts and change management consultants—will be crucial to maximize its potential impact on driving innovation and competitive advantage in modern business environments.

Potential applications are as follows:

5 Ways Agentic AI Can Be Used in Finance:

• Automated Financial Planning and Analysis:
  AI will continuously analyze data to provide real-time budgeting, forecasting, and scenario analysis, enabling more accurate and dynamic financial planning.
• Advanced Fraud Detection and Prevention:
  AI systems will autonomously monitor transactions, detect anomalies, and predict potential fraud with greater precision, reducing financial losses.
• Sophisticated Credit Risk Assessment:
  AI will assess creditworthiness and monitor borrower risk continuously, making lending processes faster and more reliable.
• Efficient Expense Management: AI will automate the entire expense management cycle, from processing reports to optimizing procurement strategies, ensuring compliance and reducing costs.
• Streamlined Regulatory Compliance: AI will monitor and ensure compliance with financial regulations, automatically generating necessary reports and alerts for discrepancies.

5 Ways Agentic AI Can Be Used in Broader Shared Services:

• Centralized Automated Financial Transactions: AI will handle payment processing and expense management across departments, ensuring accuracy and efficiency.
• Unified Customer Support: AI-powered chatbots and virtual assistants will provide consistent and immediate support for routine queries and issues across multiple departments.
• HR and Payroll Automation: AI will streamline recruitment, payroll processing, and benefits administration, improving accuracy and reducing administrative burden.
• Procurement and Supply Chain Optimization:
  AI will manage vendor relationships, optimize inventory, and automate reordering, reducing costs and ensuring supply continuity.
• Comprehensive Data Management and Analytics:
  AI will consolidate data from various sources, ensuring accuracy and providing advanced analytics for better decision-making.

To hear more from Hypatos join our webinar on August 27th to talk about The Impact of AI Agents on Your Workforce