Topics In Demand
Notification
New

No notification found.

How Will Agentic AI Redefine Decision-Making in Enterprises?
How Will Agentic AI Redefine Decision-Making in Enterprises?

February 11, 2025

16

0

Authored by: Sameer Bhangale, Associate Director - Technology, Xoriant

Artificial Intelligence (AI) has long relied on human-created algorithms to analyze data and drive business decisions. Even Generative AI, with its deep learning capabilities, fundamentally mimics human-like reasoning by processing vast amounts of information.

As AI advances, expectations are shifting towards greater independence and decision-making capabilities. Enter Agentic AI—the next frontier in artificial intelligence. Unlike traditional AI models that require human oversight, Agentic AI is designed for full autonomy, enabling businesses to achieve strategic goals with minimal intervention. It represents a paradigm shift from mere automation to true autonomy.

What Sets Agentic AI Apart?

Unlike conventional AI, which primarily assists and responds to human inputs, Agentic AI takes a proactive approach by:

  • Identifying business needs independently

  • Setting objectives based on real-time insights

  • Executing actions to achieve targeted outcomes

This transition from a reactive to a proactive model marks a significant evolution in AI-driven decision-making. Let’s explore how Agentic AI is transforming enterprise functions.

The Role of Agentic AI in Modern Businesses

Agentic AI enhances traditional AI capabilities across multiple domains. Here’s how it’s making an impact:

1. Advanced Predictive Analytics

Traditional AI utilizes predictive analytics to anticipate trends, but Agentic AI elevates this capability by continuously analyzing diverse data sources and autonomously adjusting strategies. For example, in the financial industry, Agentic AI can detect fraudulent activities by monitoring transactional patterns in real-time, reducing risk exposure without human intervention.

2. Intelligent Workflow Automation

While traditional AI automates specific tasks, Agentic AI has the ability to oversee entire business workflows with minimal input. Key advantages include:

  • Critical reasoning and problem-solving: By analyzing real-time data, Agentic AI makes strategic decisions aligned with business objectives.

  • Adaptability: Unlike rigid automation, Agentic AI adapts to external changes, refining its actions based on new insights.

3. Strategic Business Planning

Agentic AI simplifies complex decision-making processes by breaking them into manageable steps. In manufacturing, for example, AI-driven systems can optimize maintenance operations by:

  • Predicting equipment failures using real-time data

  • Automating routine maintenance schedules

  • Enhancing resource utilization for increased efficiency

Core Technologies Behind Agentic AI

The power of Agentic AI stems from cutting-edge technologies, including:

1. Large Language Models (LLMs)

LLMs enable Agentic AI to comprehend and generate human-like text, enhancing applications such as virtual assistants, sentiment analysis, and automated content creation.

2. Self-Learning Frameworks

By leveraging machine learning models that improve through experience, Agentic AI refines its decision-making strategies dynamically. Industries like financial trading benefit from these capabilities, where AI systems optimize trading strategies in real time.

3. Seamless System Integration

Agentic AI can integrate with enterprise solutions such as CRM platforms and customer support tools, enhancing decision-making across multiple business functions.

Real-World Applications of Agentic AI

1. Smarter Supply Chain Management

Agentic AI reduces uncertainties in supply chain operations by analyzing historical data and predicting disruptions. This proactive approach helps businesses manage inventory, anticipate demand fluctuations, and mitigate risks effectively.

2. Proactive Customer Support

Unlike traditional AI chatbots that react to customer inquiries, Agentic AI-driven bots anticipate user needs, resolving issues before they escalate. This leads to enhanced customer satisfaction and efficiency in service delivery.

3. Enhanced Financial Risk Management

Financial institutions can leverage Agentic AI to monitor regulatory compliance, detect fraudulent transactions in real time, and automate risk assessments, ensuring operational security and accuracy.

Overcoming Adoption Challenges

Despite its potential, organizations must address several hurdles to implement Agentic AI effectively:

1. Complex Implementation

Developing and deploying Agentic AI requires skilled professionals with expertise in AI modeling and domain-specific knowledge. Additionally, enterprises must ensure data quality and consistency to enable accurate AI-driven decisions.

2. Ethical Considerations

Autonomous AI decision-making raises ethical concerns around transparency and accountability. Businesses must establish governance frameworks to monitor AI actions and mitigate unintended consequences.

3. Trust in AI-Driven Decisions

To foster confidence in AI-generated outcomes, organizations should focus on explainability—ensuring that stakeholders understand how AI reaches its conclusions. Providing clear insights into AI decision-making can enhance adoption and trust.

The Future of Agentic AI in Enterprises

As Agentic AI evolves, it is expected to gain more human-like capabilities, including:

  • Emotional intelligence for more natural interactions

  • Enhanced natural language processing for deeper understanding

  • The ability to interpret facial expressions and behavioral cues

A Deloitte report predicts that by 2027, half of enterprises using Generative AI will pilot Agentic AI initiatives. Industry-specific applications, such as AI-powered medical diagnostics and legal automation, will further solidify its role across sectors.

Getting Started: A Roadmap for Businesses

For enterprises looking to adopt Agentic AI, a structured approach is essential:

1. Assess Readiness

Evaluate infrastructure, data management capabilities, and AI expertise before implementation. Ensuring scalable computing resources and high-quality data is crucial for successful deployment.

2. Identify High-Impact Areas

Determine the most valuable use cases where Agentic AI can drive immediate improvements. This may involve automating customer interactions, streamlining operations, or enhancing decision-making in key business areas.

3. Develop a Long-Term Strategy

A phased implementation plan should include:

  • Intelligent data orchestration

  • Adaptive workflows

  • Human-AI collaboration for enhanced efficiency

Wrapping it Up

Agentic AI is transforming enterprise decision-making by enabling true autonomy. To maximize its potential, business leaders must establish clear success metrics—focusing on performance, scalability, autonomy, and proactivity. By doing so, enterprises can harness Agentic AI to drive sustained growth, enhance operational efficiency, and foster continuous innovation.

About Author:

Sameer Bhangale is the Associate Director of Technology at Xoriant. He is an innovative professional with a focus on Machine Learning, Natural Language Processing (NLP), and Artificial Intelligence. He is dedicated to promoting knowledge in these fields and actively participates in machine learning competitions. Sameer also has expertise in strategic thinking, data analysis, analytics, and leadership. His skills extend to cloud computing, predictive analytics, conversational AI, and software quality, underscoring his versatility and depth in the tech industry. Additionally, he has experience as an Agile/DevOps coach, blending technical expertise with leadership and team-building skills.


That the contents of third-party articles/blogs published here on the website, and the interpretation of all information in the article/blogs such as data, maps, numbers, opinions etc. displayed in the article/blogs and views or the opinions expressed within the content are solely of the author's; and do not reflect the opinions and beliefs of NASSCOM or its affiliates in any manner. NASSCOM does not take any liability w.r.t. content in any manner and will not be liable in any manner whatsoever for any kind of liability arising out of any act, error or omission. The contents of third-party article/blogs published, are provided solely as convenience; and the presence of these articles/blogs should not, under any circumstances, be considered as an endorsement of the contents by NASSCOM in any manner; and if you chose to access these articles/blogs , you do so at your own risk.


Xoriant is a Silicon Valley-headquartered digital product engineering, software development, and technology services firm with offices in the USA,UK, Ireland, Mexico, Canada and Asia. From startups to the Fortune 100, we deliver innovative solutions, accelerating time to market and ensuring our clients' competitiveness in industries like BFSI, High Tech, Healthcare, Manufacturing and Retail. Across all our technology focus areas-digital product engineering, DevOps, cloud, infrastructure, and security, big data and analytics, data engineering, management and governance -every solution we develop benefits from our product engineering pedigree. It also includes successful methodologies, framework components, and accelerators for rapidly solving important client challenges. For 30 years and counting, we have taken great pride in our long-lasting, deep relationships with our clients.

© Copyright nasscom. All Rights Reserved.